Advances in nano research

  • 제16권6호
  • /
  • Pages.531-548
  • /
  • 2024
  • /
  • 2287-237X(pISSN)
  • /
  • 2287-2388(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Combination of fuzzy models via economic management for city multi-spectral remote sensing nano imagery road target

  • Weihua Luo (Jiangxi Zhonggantou Survey & Design Co.,Ltd) ;
  • Ahmed H. Janabi (Computer Techniques Engineering Department, College of Engineering & Technology, Al-Mustaqbal University) ;
  • Joffin Jose Ponnore (Department of Mechanical Engineering, College of Engineering in Al-Kharj, Prince Sattam Bin Abdulaziz University) ;
  • Hanadi Hakami (Department of Software Engineering, College of Engineering, University of Business and Technology) ;
  • Hakim AL Garalleh (Department of Mathematical Science, College of Engineering, University of Business and Technology) ;
  • Riadh Marzouki (Department of Chemistry, College of Science, King Khalid University) ;
  • Yuanhui Yu (School of Civil and Environmental Engineering, Georgia Institute of Technology) ;
  • Hamid Assilzadeh (Institute of Research and Development, Duy Tan University)
  • 투고 : 2021.06.06
  • 심사 : 2022.02.13
  • 발행 : 2024.06.25
⟨ 이전 논문 다음 논문 ⟩

초록

The study focuses on using remote sensing to gather data about the Earth's surface, particularly in urban environments, using satellites and aircraft-mounted sensors. It aims to develop a classification framework for road targets using multi-spectral imagery. By integrating Convolutional Neural Networks (CNNs) with XGBoost, the study seeks to enhance the accuracy and efficiency of road target identification, aiding urban infrastructure management and transportation planning. A novel aspect of the research is the incorporation of quantum sensors, which improve the resolution and sensitivity of the data. The model achieved high predictive accuracy with an MSE of 0.025, R-squared of 0.85, RMSE of 0.158, and MAE of 0.12. The CNN model showed excellent performance in road detection with 92% accuracy, 88% precision, 90% recall, and an f1-score of 89%. These results demonstrate the model's robustness and applicability in real-world urban planning scenarios, further enhanced by data augmentation and early stopping techniques.

키워드

과제정보

This study is supported via funding from Prince Sattam Bin Abdulaziz University, (PSAU/2024/R/1445), AlKharj, Saudi Arabia. The authors extend their appreciation to the Al-Mustaqbal University for supporting this work under grant number (MUC - E- 0122).

참고문헌

  1. Abdikan, S., Sekertekin, A., Narin, O. G., Delen, A. and Balik Sanli, F. (2023), "A comparative analysis of SLR, MLR, ANN, XGBoost and CNN for crop height estimation of sunflower using Sentinel-1 and Sentinel-2", Adv. Space Res., 71(7), 3045-3059. https://doi.org/10.1016/j.asr.2022.11.046.
  2. Abdollahi, A., Pradhan, B., Sharma, G., Maulud, K.N.A. and Alamri, A. (2021), "Improving road semantic segmentation using generative adversarial network", IEEE Access, 9, 64381-64392. https://doi.org/10.1109/ACCESS.2021.3074545.
  3. Abdollahi, A., Pradhan, B. and Shukla, N. (2019), "Extraction of road features from UAV images using a novel level set segmentation approach", Int. J. Urban Sci., 23(3), 391-405. https://doi.org/10.1080/12265934.2019.1583280.
  4. Abdollahi, A., Pradhan, B., Shukla, N., Chakraborty, S. and Alamri, A. (2020), "Deep learning approaches applied to remote sensing datasets for road extraction: A state-of-the-art review", Remote Sens., 12(9), 1444. https://doi.org/10.3390/rs12091444.
  5. Afshar, A., Jahandari, S., Rasekh, H., Shariati, M., Afshar, A. and Shokrgozar, A. (2020), "Corrosion resistance evaluation of rebars with various primers and coatings in concrete modified with different additives", Constr. Build. Mater., 262, 120034. https://doi.org/10.1016/j.conbuildmat.2020.120034.
  6. Aghakhani, M., Suhatril, M., Mohammadhassani, M., Daie, M. and Toghroli, A. (2015), "A simple modification of homotopy perturbation method for the solution of Blasius equation in semi-infinite domains", Math. Probl. Eng., 2015. https://doi.org/10.1155/2015/671527.
  7. Alshehhi, R. and Marpu, P.R. (2017), "Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images", ISPRS J. Photogram. Remote Sens., 126, 245-260. https://doi.org/10.1016/j.isprsjprs.2017.02.010.
  8. Andrearczyk, V. and Whelan, P.F. (2016), "Using filter banks in convolutional neural networks for texture classification", Pattern Recog. Lett., 84, 63-69. https://doi.org/10.1016/j.patrec.2016.10.015.
  9. Arabnejad Khanouki, M.M., Ramli Sulong, N.H. and Shariati, M. (2010a), "Behavior of through beam connections composed of CFSST columns and steel beams by finite element studying", Adv. Mater. Res., 168-170, 2329-2333. https://doi.org/10.4028/www.scientific.net/AMR.168-170.2329.
  10. Arabnejad Khanouki, M.M., Ramli Sulong, N.H. and Shariati, M. (2010b), "Investigation of seismic behaviour of composite structures with concrete filled square steel tubular (CFSST) column by push-over and time-history analyses", Proceedings of the 4th International Conference on Steel & Composite Structures.
  11. Audebert, N., Le Saux, B. and Lefevre, S. (2017), "Segment-before-detect: Vehicle detection and classification through semantic segmentation of aerial images", Remote Sens., 9(4), 368. https://doi.org/10.3390/rs9040368.
  12. Badrinarayanan, V., Handa, A. and Cipolla, R. (2015), "Segnet: A deep convolutional encoder-decoder architecture for robust semantic pixel-wise labelling", arXiv preprint arXiv:1505.07293.
  13. Buslaev, A., Seferbekov, S., Iglovikov, V. and Shvets, A. (2018). Fully convolutional network for automatic road extraction from satellite imagery. Proceedings of the IEEE conference on computer vision and pattern recognition workshops.
  14. Casu, F., Manunta, M., Agram, P. and Crippen, R. (2017), "Big remotely sensed data: tools, applications and experiences", Remote Sens. Environ., 202(1), 1-2. https://doi.org/10.1016/j.rse.2017.04.032.
  15. Chen, C., Shi, L., Shariati, M., Toghroli, A., Mohamad, E.T., Bui, D. T. and Khorami, M. (2019), "Behavior of steel storage pallet racking connection-A review", Steel Compos. Struct., 30(5), 457-469. https://doi.org/10.12989/scs.2019.30.5.457
  16. Chen, G., Weng, Q., Hay, G.J. and He, Y. (2018), "Geographic object-based image analysis (GEOBIA): Emerging trends and future opportunities", GISci. Remote Sens., 55(2), 159-182. https://doi.org/10.1080/15481603.2018.1426092.
  17. Chen, H., Li, Z., Wu, J., Xiong, W. and Du, C. (2023), "Semi Road ExNet: A semi-supervised network for road extraction from remote sensing imagery via adversarial learning", ISPRS J. Photogram. Remote Sens., 198, 169-183. https://doi.org/10.1016/j.isprsjprs.2023.03.012.
  18. Chen, Z., Wang, C., Li, J., Xie, N., Han, Y. and Du, J. (2021), "Reconstruction bias U-Net for road extraction from optical remote sensing images", IEEE J. Select. Topics Appl. Earth Observ. Remote Sens., 14, 2284-2294. https://doi.org/10.1109/JSTARS.2021.3066187.
  19. Cheng, G., Wang, Y., Xu, S., Wang, H., Xiang, S. and Pan, C. (2017), "Automatic road detection and centerline extraction via cascaded end-to-end convolutional neural network", IEEE T. Geosci. Remote Sens., 55(6), 3322-3337. https://doi.org/10.1109/TGRS.2017.2669341.
  20. Chi, M., Plaza, A., Benediktsson, J. A., Sun, Z., Shen, J. and Zhu, Y. (2016), "Big data for remote sensing: Challenges and opportunities", Proceedings of the IEEE, 104(11), 2207-2219. https://doi.org/10.1109/JPROC.2016.2598228.
  21. Cira, C.I., Manso-Callejo, M.A ., Alcarria, R., Bordel Sanchez, B. and Gonzalez Matesanz, J. (2023), "State-level mapping of the road transport network from aerial orthophotography: an end-to-end road extraction solution based on deep learning models trained for recognition, semantic segmentation and post-processing with conditional generative learning", Remote Sensing, 15(8), 2099. https://doi.org/10.3390/rs15082099.
  22. Clevert, D.A., Unterthiner, T. and Hochreiter, S. (2015), "Fast and accurate deep network learning by exponential linear units (elus)", arXiv preprint arXiv:1511.07289.
  23. Daie, M., Jalali, A., Suhatril, M., Shariati, M., Khanouki, M. A. and Shariati, A. (2011), "A new finite element investigation on pre-bent steel strips as damper for vibration control", Int. J. Phys. Sci., 6(36), 8044-8050. https://doi.org/10.5897/IJPS11.1585.
  24. Das, S., Mirnalinee, T. and Varghese, K. (2011), "Use of salient features for the design of a multistage framework to extract roads from high-resolution multispectral satellite images", IEEE T. Geosci. Remote Sens., 49(10), 3906-3931. https://doi.org/10.1109/TGRS.2011.2158584.
  25. Davoodnabi, S.M., Mirhosseini, S.M. and Shariati, M. (2019), "Behavior of steel-concrete composite beam using angle shear connectors at fire condition", Steel Compos. Struct., 30(2), 141-147. https://doi.org/10.12989/scs.2019.30
  26. Davoodnabi, S.M., Mirhosseini, S.M. and Shariati, M. (2021), "Analyzing shear strength of steel-concrete composite beam with angle connectors at elevated temperature using finite element method", Steel and Composite Structures, 40(6), 853-868. https://doi.org/10.12989/scs.2021.40.6.853.
  27. De Almeida, D.R.A., Broadbent, E.N., Ferreira, M.P., Meli, P., Zambrano, A.M.A., Gorgens, E.B., Resende, A.F., de Almeida, C.T., Do Amaral, C.H. and Dalla Corte, A.P. (2021), "Monitoring restored tropical forest diversity and structure through UAV-borne hyperspectral and lidar fusion", Remote Sens. Environ., 264, 112582. https://doi.org/10.1016/j.rse.2021.112582.
  28. Demars, C., Roggemann, M. and Zulch, P. (2015), "Multi-spectral detection and tracking in cluttered urban environments", 2015 IEEE Aerospace Conference, IEEE.
  29. Demir, I., Koperski, K., Lindenbaum, D., Pang, G., Huang, J., Basu, S., Hughes, F., Tuia, D. and Raskar, R. (2018). "Deepglobe 2018: A challenge to parse the earth through satellite images", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops.
  30. Desai, S. and Ghose, D. (2022), "Active learning for improved semi-supervised semantic segmentation in satellite images", Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision.
  31. Dey, M., Prakash, P.S. and Aithal, B. H. (2024), "UnetEdge: A transfer learning-based framework for road feature segmentation from high-resolution remote sensing images", Remote Sensing Applications: Society and Environment, 34, 101160. https://doi.org/10.1016/j.rsase.2024.101160.
  32. Dong, H., Xu, X., Wang, L. and Pu, F. (2018), "Gaofen-3 PolSAR image classification via XGBoost and polarimetric spatial information", Sensors, 18(2), 611. https://doi.org/10.3390/s18020611.
  33. Ehsan Shahabi, J.J.K. and Barghi, M. (2023), "Innovative computational approaches to developing sustainable urban infrastructure: Optimizing green roof systems for enhanced water management and environmental benefits", Int. J. Civil Eng. Adv., 1(1), 20-29.
  34. Eismann, M.T., Stocker, A.D. and Nasrabadi, N.M. (2009), "Automated hyperspectral cueing for civilian search and rescue", Proceedings of the IEEE, 97(6), 1031-1055. https://doi.org/10.1109/JPROC.2009.2015713.
  35. Emad Toghroli, S.M., Moeini, F. and Maleki, S. (2023), "Utilizing advanced machine learning algorithms for predicting the fatigue life of steel-reinforced concrete structures under variable load conditions", Int. J. Civil Eng. Adv., 1(1), 40-48.
  36. Fan, W., Sun, S. and Wang, J. (2016), "Comparison of relative radiometric correction methods for multi-temporal remote sensing images", Remote Sens. Inform., 31(3), 142-149. https://doi.org/10.1016/j.rsi.2016.05.006.
  37. Hamidian, M., Shariati, M., Arabnejad, M. and Sinaei, H. (2011), "Assessment of high strength and light weight aggregate concrete properties using ultrasonic pulse velocity technique", Int. J. Phys. Sci., 6(22), 5261-5266. https://doi.org/10.5897/IJPS11.1081.
  38. He, K., Zhang, X., Ren, S. and Sun, J. (2016), "Deep residual learning for image recognition", Proceedings of the IEEE conference on computer vision and pattern recognition.
  39. He, Y., Wang, J., Liao, C., Shan, B. and Zhou, X. (2022), "ClassHyPer: ClassMix-based hybrid perturbations for deep semi-supervised semantic segmentation of remote sensing imagery", Remote Sens., 14(4), 879. https://doi.org/10.3390/rs14040879.
  40. Heydari, A. and Shariati, M. (2018), "Buckling analysis of tapered BDFGM nano-beam under variable axial compression resting on elastic medium", Struct. Eng. Mech., 66(6), 737-748. https://doi.org/10.12989/sem.2018.66.6.737.
  41. Hoang, N.T. and Koike, K. (2018), "Comparison of hyperspectral transformation accuracies of multispectral Landsat TM, ETM+, OLI and EO-1 ALI images for detecting minerals in a geothermal prospect area", ISPRS J. Photogram. Remote Sens., 137, 15-28. https://doi.org/10.1016/j.isprsjprs.2018.01.001.
  42. Hosseini, S. A. and Toghroli, A. (2021), "Effect of mixing Nano-silica and Perlite with pervious concrete for nitrate removal from the contaminated water", Adv. Concr. Constr., 11(6), 531-544. https://doi.org/10.12989/acc.2021.11.6.531.
  43. Hosseinpour, E., Baharom, S., Badaruzzaman, W.H.W., Shariati, M. and Jalali, A. (2018), "Direct shear behavior of concrete filled hollow steel tube shear connector for slim-floor steel beams", Steel Compos. Struct., 26(4), 485-499. https://doi.org/10.12989/scs.2018.26.4.485.
  44. Huadong, G. (2018), "Steps to the digital Silk Road", Nature Publishing Group.
  45. Ismail, M., Shariati, M., Awal, A.S.M.A., Chiong, C.E., Chahnasir, E.S., Porbar, A., Heydari, A. and Khorami, M. (2018), "Strengthening of bolted shear joints in industrialized ferrocement construction", Steel Compos Struct, 28(6), 681-690. https://doi.org/10.12989/scs.2018.28.6.681.
  46. Jalali, A., Daie, M., Nazhadan, S.V.M., Kazemi-Arbat, P. and Shariati, M. (2012), "Seismic performance of structures with pre-bent strips as a damper", Int. J. Phys. Sci., 7(26), 4061-4072. https://doi.org/10.5897/IJPS11.1324.
  47. Katebi, J., Shoaei-parchin, M., Shariati, M., Trung, N.T. and Khorami, M. (2019), "Developed comparative analysis of metaheuristic optimization algorithms for optimal active control of structures", Eng. Comput., 1-20. https://doi.org/10.1007/s00366-019-00796-5.
  48. Kendall, A., Badrinarayanan, V. and Cipolla, R. (2015), "Bayesian segnet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding", arXiv preprint arXiv:1511.02680.
  49. Khanouki, M.M.A., Ramli Sulong, N.H., Shariati, M. and Tahir, M.M. (2016), "Investigation of through beam connection to concrete filled circular steel tube (CFCST) column", J. Constr. Steel Res., 121, 144-162. https://doi.org/10.1016/j.jcsr.2016.01.002.
  50. Khorami, M., Khorami, M., Motahar, H., Alvansazyazdi, M., Shariati, M., Jalali, A. and Tahir, M.M. (2017a), "Seismic performance evaluation of buckling restrained braced frames (BRBF) using incremental nonlinear dynamic analysis method (IDA)", Earthq. Struct., 13(6), 531-538. https://doi.org/10.12989/eas.2017.13.6.531.
  51. Khorami, M., Khorami, M., Motahar, H., Alvansazyazdi, M., Shariati, M., Jalali, A. and Tahir, M.M. (2017b), "Evaluation of the seismic performance of special moment frames using incremental nonlinear dynamic analysis", Struct. Eng. Mech., 63(2), 259-268. https://doi.org/10.12989/sem.2017.63.2.259.
  52. Khorramian, K., Maleki, S., Shariati, M., Jalali, A. and Tahir, M. M. (2017), "Numerical analysis of tilted angle shear connectors in steel-concrete composite systems", Steel Compos. Struct., 23(1), 67-85. https://doi.org/10.12989/scs.2017.23.1.067.
  53. Khorramian, K., Maleki, S., Shariati, M. and Ramli Sulong, N.H. (2015), "Behavior of tilted angle shear connectors", PLoS One, 10(12), e0144288. https://doi.org/10.1371/journal.pone.0144288.
  54. Kirthika, A. and Mookambiga, A. (2011). Automated road network extraction using artificial neural network. 2011 International Conference on Recent Trends in Information Technology (ICRTIT), IEEE.
  55. Kumar, M., Singh, R., Raju, P. and Krishnamurthy, Y. (2014), "Road network extraction from high resolution multispectral satellite imagery based on object oriented techniques", ISPRS Annals Photogram. Remote Sens. Spatial Inform. Sci., 2(8), 107-112. https://doi.org/10.5194/isprsannals-II-8-107-2014.
  56. Lak, A.M., Zoej, M.J.V. and Mokhtarzade, M. (2016), "A new method for road detection in urban areas using high-resolution satellite images and Lidar data based on fuzzy nearest-neighbor classification and optimal features", Arab. J. Geosci., 9(5), 358. https://doi.org/10.1007/s12517-016-2331-7.
  57. Li, D.Y., Toghroli, A., Shariati, M., Sajedi, F., Bui, D.T., Kianmehr, P., Mohamad, E.T. and Khorami, M. (2019a), "Application of polymer, silica-fume and crushed rubber in the production of pervious concrete", Smart Struct. Syst., 23(2), 207-214. https://doi.org/10.12989/sss.2019.23.2.207.
  58. Li, J., Sun, B., Li, S. and Kang, X. (2021), "Semisupervised semantic segmentation of remote sensing images with consistency self-training", IEEE Transact. Geosci. Remote Sens., 60, 1-11. https://doi.org/10.1109/TGRS.2021.3076721.
  59. Li, N., Wang, R., Zhao, H. and Wei, W. (2019b), "An improved feature extraction method based on context features for multi-spectral remote sensing imagery", 2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP), IEEE.
  60. Liang, P., Shi, W., Ding, Y., Liu, Z. and Shang, H. (2021), "Road extraction from high resolution remote sensing images based on vector field learning", Sensors, 21(9). https://doi.org/10.3390/s21093152.
  61. Lin, C., Chen, S.Y., Chen, C.C. and Tai, C.H. (2018), "Detecting newly grown tree leaves from unmanned-aerial-vehicle images using hyperspectral target detection techniques", ISPRS J. Photogram. Remote Sens., 142, 174-189. https://doi.org/10.1016/j.isprsjprs.2018.05.002.
  62. Lin, T.Y., Dollar, P., Girshick, R., He, K., Hariharan, B. and Belongie, S. (2017), "Feature pyramid networks for object detection", Proceedings of the IEEE Conference on Computer Vision And Pattern Recognition.
  63. Liu, C. and Sziranyi, T. (2022), "Road condition detection and emergency rescue recognition using on-board UAV in the wilderness", Remote Sens., 14. https://doi.org/10.3390/rs14174355.
  64. Liu, P., Wang, Q., Yang, G., Li, L. and Zhang, H. (2022), "Survey of road extraction methods in remote sensing images based on deep learning", PFG J. Photogram. Remote Sens. Geoinform. Sci., 90(2), 135-159. https://doi.org/10.1007/s41064-021-00176-1.
  65. Liu, Y., Yao, J., Lu, X., Xia, M., Wang, X. and Liu, Y. (2018), "RoadNet: Learning to comprehensively analyze road networks in complex urban scenes from high-resolution remotely sensed images", IEEE T. Geosci. Remote Sens., 57(4), 2043-2056. https://doi.org/10.1109/TGRS.2018.2852063.
  66. Long, J., Shelhamer, E. and Darrell, T. (2015), "Fully convolutional networks for semantic segmentation", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
  67. Luo, Z.Y., Sinaei, H., Ibrahim, Z., Shariati, M., Jumaat, Z., Wakil, K., Pham, B.T., Mohamad, E.T. and Khorami, M. (2019), "Computational and experimental analysis of beam to column joints reinforced with CFRP plates", Steel Compos. Struct., 30(3), 271-280. https://doi.org/10.12989/scs.2019.30.3.271.
  68. Mansouri, I., Safa, M., Ibrahim, Z., Kisi, O., Tahir, M.M., Baharom, S. and Azimi, M. (2016), "Strength prediction of rotary brace damper using MLR and MARS", Struct. Eng. Mech., 60(3), 471-488. https://doi.org/10.12989/sem.2016.60.3.471.
  69. Marcu, A.E. (2016), "A local-global approach to semantic segmentation in aerial images", arXiv preprint arXiv:1607.05620.
  70. Mehrabi, P., Shariati, M., Kabirifar, K., Jarrah, M., Rasekh, H., Trung, N.T., Shariati, A. and Jahandari, S. (2021), "Effect of pumice powder and nano-clay on the strength and permeability of fiber-reinforced pervious concrete incorporating recycled concrete aggregate", Constr. Build. Mater., 287, 122652. https://doi.org/10.1016/j.conbuildmat.2021.122652.
  71. Mei, J., Li, R.J., Gao, W. and Cheng, M.M. (2021), "CoANet: Connectivity attention network for road extraction from satellite imagery", IEEE T. Image Proc., 30, 8540-8552. https://doi.org/10.1109/TIP.2021.3117076.
  72. Miao, Z., Wang, B., Shi, W. and Zhang, H. (2014), "A semi-automatic method for road centerline extraction from VHR images", IEEE Geosci. Remote Sens. Lett., 11(11), 1856-1860. https://doi.org/10.1109/LGRS.2014.2326820.
  73. Milovancevic, M., Marinovic, J.S., Nikolic, J., Kitic, A., Shariati, M., Trung, N.T., Wakil, K. and Khorami, M. (2019), "UML diagrams for dynamical monitoring of rail vehicles", Physica A, 531, 121169. https://doi.org/10.1016/j.physa.2019.121169.
  74. Mnih, V. (2013), "Machine learning for aerial image labeling", University of Toronto, Canada.
  75. Mnih, V. and Hinton, G. E. (2010), "Learning to detect roads in high-resolution aerial images", Computer Vision-ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September.
  76. Mohammad, M., Arabnejad, K. and Toghroli, A. (2023), "Advanced computational techniques for the assessment of wind load impact on high-rise building structures", Int. J. Civil Eng. Adv., 1(1), 49-57.
  77. Mohammadhassani, M., Akib, S., Shariati, M., Suhatril, M. and Khanouki, M.M.A. (2014a), "An experimental study on the failure modes of high strength concrete beams with particular references to variation of the tensile reinforcement ratio", Eng. Fail. Anal., 41, 73-80. https://doi.org/10.1016/j.engfailanal.2013.08.014.
  78. Mohammadhassani, M., Nezamabadi-Pour, H., Suhatril, M. and Shariati, M. (2013a), "Identification of a suitable ANN architecture in predicting strain in tie section of concrete deep beams", Struct. Eng. Mech., 46(6), 853-868. https://doi.org/10.12989/sem.2013.46.6.853.
  79. Mohammadhassani, M., Nezamabadi-pour, H., Suhatril, M. and Shariati, M. (2014b), "An evolutionary fuzzy modelling approach and comparison of different methods for shear strength prediction of high-strength concrete beams without stirrups", Smart Struct. Syst., 14(5), 785-809. https://doi.org/10.12989/sss.2014.14.5.785.
  80. Mohammadhassani, M., Saleh, A.M.D., Suhatril, M. and Safa, M. (2015), "Fuzzy modelling approach for shear strength prediction of RC deep beams", Smart Struct. Syst., 16(3), 497-519. https://doi.org/10.12989/sss.2015.16.3.497.
  81. Mohammadhassani, M., Suhatril, M., Shariati, M. and Ghanbari, F. (2013b), "Ductility and strength assessment of HSC beams with varying of tensile reinforcement ratios", Struct. Eng. Mech., 48(6), 833-848. https://doi.org/10.12989/sem.2013.48.6.833.
  82. Morteza Shariati, Shariati, M.H. and Pour, A.M. (2023), "Evaluating the use of recycled glass in concrete mixtures: A comprehensive strength and durability analysis using neural networks for mix ratio optimization", Int. J. Civil Eng. Adv., 1(1), 30-39.
  83. Muruganandham, S. (2016), "Semantic segmentation of satellite images using deep learning", Independent Thesis, Department of Computer Science, Lulea University of Technology,
  84. Naghipour, M., Niak, K.M., Shariati, M. and Toghroli, A. (2020a), "Effect of progressive shear punch of a foundation on a reinforced concrete building behavior", Steel Compos. Struct., 35(2), 279-294. https://doi.org/10.12989/scs.2020.35.2.279.
  85. Naghipour, M., Yousofizinsaz, G. and Shariati, M. (2020b), "Experimental study on axial compressive behavior of welded built-up CFT stub columns made by cold-formed sections with different welding lines", Steel Compos. Struct., 34(3), 347-359. https://doi.org/10.12989/scs.2020.34.3.347.
  86. Nasrollahi, S., Maleki, S., Shariati, M., Marto, A. and Khorami, M. (2018), "Investigation of pipe shear connectors using push out test", Steel Compos. Struct., 27(5), 537-543. https://doi.org/10.12989/scs.2018.27.5.537.
  87. Noh, H., Hong, S. and Han, B. (2015), "Learning deconvolution network for semantic segmentation", Proceedings of the IEEE International Conference on Computer Vision.
  88. Nosrati, A., Zandi, Y., Shariati, M., Khademi, K., Aliabad, M.D., Marto, A., Mu'azu, M., Ghanbari, E., Mandizadeh, M.B., Shariati, A. and Khorami, M. (2018), "Portland cement structure and its major oxides and fineness", Smart Struct. Syst., 22(4), 425-432. https://doi.org/10.12989/sss.2018.22.4.425.
  89. Nouri, K., Ramli Sulong, N.H., Ibrahim, Z. and Shariati, M. (2021), "Behaviour of novel stiffened angle shear connectors at ambient and elevated temperatures", Adv. Steel Constr., 17(1), 28-38. https://doi.org/10.18057/Ijasc.2021.17.1.4.
  90. Paknahad, M., Shariati, M., Sedghi, Y., Bazzaz, M. and Khorami, M. (2018), "Shear capacity equation for channel shear connectors in steel-concrete composite beams", Steel Compos. Struct., 28(4), 483-494. https://doi.org/10.12989/scs.2018.28.4.483.
  91. Pandey, D. and Tiwari, K. (2020), "Extraction of urban built-up surfaces and its subclasses using existing built-up indices with separability analysis of spectrally mixed classes in AVIRIS-NG imagery", Adv. Space Res., 66(8), 1829-1845. https://doi.org/10.1016/j.asr.2020.06.009.
  92. Parsa, A.B., Movahedi, A., Taghipour, H., Derrible, S. and Mohammadian, A.K. (2020), "Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis", Accident Anal. Prevent., 136, 105405. https://doi.org/10.1016/j.aap.2019.105405.
  93. Phung, V.H. and Rhee, E.J. (2019), "A high-accuracy model average ensemble of convolutional neural networks for classification of cloud image patches on small datasets", Appl. Sci., 9, 4500. https://doi.org/10.3390/app9214500.
  94. Previtali, M., Barazzetti, L. and Scaioni, M. (2020), "Automated road information extraction from high resolution aerial LiDAR data for smart road applications", 24th ISPRS Congress, International Society for Photogrammetry and Remote Sensing.
  95. Rahimzadegan, M., Sadeghi, B., Masoumi, M. and Taghizadeh Ghalehjoghi, S. (2015), "Application of target detection algorithms to identification of iron oxides using ASTER images: A case study in the north of Semnan province, Iran", Arab. J. Geosci., 8, 7321-7331. https://doi.org/10.1007/s12517-014-1490-4.
  96. Raichura, M., Chothani, N. and Patel, D. (2021), "Efficient CNN-XGBoost technique for classification of power transformer internal faults against various abnormal conditions", IET Generat. Transmiss. Distrib., 15(5), 972-985. https://doi.org/10.1049/gtd2.12050.
  97. Razavian, L., Naghipour, M., Shariati, M. and Safa, M. (2020), "Experimental study of the behavior of composite timber columns confined with hollow rectangular steel sections under compression", Struct. Eng. Mech., 74(1), 145-156. https://doi.org/10.12989/sem.2020.74.1.145.
  98. Roessner, S., Segl, K., Bochow, M., Heiden, U., Heldens, W. and Kaufmann, H. (2011), "Potential of hyperspectral remote sensing for analyzing the urban environment", Proceedings of the IEEE, 97(6), 1031-1055. https://doi.org/10.1109/JPROC.2011.2123810.
  99. Ronneberger, O., Fischer, P. and Brox, T. (2015a), "U-net: Convolutional networks for biomedical image segmentation", International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer.
  100. Ronneberger, O., Fischer, P. and Brox, T. (2015b), "U-net: Convolutional networks for biomedical image segmentation", Medical Image Computing and Computer-Assisted Intervention-MICCAI 18th International Conference, Munich, Germany, October.
  101. Sadeghipour Chahnasir, E., Zandi, Y., Shariati, M., Dehghani, E., Toghroli, A., Mohamed, E. T., Shariati, A., Safa, M., Wakil, K. and Khorami, M. (2018), "Application of support vector machine with firefly algorithm for investigation of the factors affecting the shear strength of angle shear connectors", Smart Struct. Syst., 22(4), 413-424. https://doi.org/10.12989/sss.2018.22.4.413.
  102. Safa, M., Ahmadi, M., Mehrmashadi, J., Petkovic, D., Mohammadhassani, M., Zandi, Y. and Sedghi, Y. (2020a), "Selection of the most influential parameters on vectorial crystal growth of highly oriented vertically aligned carbon nanotubes by adaptive neuro-fuzzy technique", Int. J. Hydromechatron., 3(3), 238-251. https://doi.org/10.1504/IJHM.2020.108873.
  103. Safa, M., Sari, P.A., Shariati, M., Suhatril, M., Trung, N.T., Wakil, K. and Khorami, M. (2020b), "Development of neuro-fuzzy and neuro-bee predictive models for prediction of the safety factor of eco-protection slopes", Physica A, 550, 124046. https://doi.org/10.1016/j.physa.2019.124046.
  104. Safa, M., Shariati, M., Ibrahim, Z., Toghroli, A., Baharom, S. and Nor, N. M. (2016), "Potential of adaptive neuro fuzzy inference system for evaluating the factors affecting steel-concrete composite beam's shear strength", Steel Compos. Struct., 21(3), 679-688. https://doi.org/10.12989/scs.2016.21.3.679.
  105. Saito, S., Yamashita, T. and Aoki, Y. (2016a), "Multiple object extraction from aerial imagery with convolutional neural networks", Electronic Imaging, 2016(10), 1-9. https://doi.org/10.2352/ISSN.2470-1173.2016.10.IPP
  106. Saito, S., Yamashita, T. and Aoki, Y. (2016b), "Multiple object extraction from aerial imagery with convolutional neural networks", Electr. Image, 28, 1-9. https://doi.org/10.2352/ISSN.2470-1173.2016.10.IPP
  107. Sajedi, F. and Shariati, M. (2019), "Behavior study of NC and HSC RCCs confined by GRP casing and CFRP wrapping", Steel Compos. Struct., 30(5), 417-432. https://doi.org/10.12989/scs.2019.30.5.417.
  108. Samma, H., Suandi, S. A., Ismail, N. A., Sulaiman, S. and Ping, L. L. (2021), "Evolving pre-trained CNN using two-layers optimizer for road damage detection from drone images", IEEE Access, 9, 158215-158226. https://doi.org/10.1109/ACCESS.2021.3128100.
  109. Sari, P.A., Suhatril, M., Osman, N., Mu'azu, M.A., Dehghani, H., Sedghi, Y., Safa, M., Hasanipanah, M., Wakil, K. and Khorami, M. (2019), "An intelligent based-model role to simulate the factor of safe slope by support vector regression", Eng. Comput., 35(4), 1521-1531. https://doi.org/10.1007/s00366-018-0677-4.
  110. Sedghi, Y., Zandi, Y., Shariati, M., Ahmadi, E., Azar, V.M., Toghroli, A., Safa, M., Mohamad, E.T., Khorami, M. and Wakil, K. (2018), "Application of ANFIS technique on performance of C and L shaped angle shear connectors", Smart Struct. Syst., 22(3), 335-340. https://doi.org/10.12989/sss.2018.22.3.335.
  111. Selvi Sundarapandi, A.M., Alotaibi, Y., Thanarajan, T. and Rajendran, S. (2024), "Archimedes optimisation algorithm quantum dilated convolutional neural network for road extraction in remote sensing images", Heliyon, 10(5), e26589. https://doi.org/10.1016/j.heliyon.2024.e26589.
  112. Sghaier, M.O. and Lepage, R. (2015), "Road extraction from very high resolution remote sensing optical images based on texture analysis and beamlet transform", IEEE J. Select.Topics Appl. Earth Observ. Remote Sens., 9(5), 1946-1958. https://doi.org/10.1109/JSTARS.2015.2442211.
  113. Shah-Hosseini, R., Safari, A. and Homayouni, S. (2017), "Natural hazard damage detection based on object-level support vector data description of optical and SAR Earth observations", Int. J. Remote Sens., 38(11), 3356-3374. https://doi.org/10.1080/01431161.2017.1302113.
  114. Shah, S.A.A., Manzoor, M.A. and Bais, A. (2020), "Canopy height estimation at Landsat resolution using convolutional neural networks", Machine Learn. Knowl. Extract., 2(1), 3-21. https://doi.org/10.3390/make2010001.
  115. Shah, S.N.R., Ramli Sulong, N.H., Jumaat, M.Z. and Shariati, M. (2016a), "State-of-the-art review on the design and performance of steel pallet rack connections", Eng. Fail. Anal., 66, 240-258. https://doi.org/10.1016/j.engfailanal.2016.04.017.
  116. Shah, S.N.R., Ramli Sulong, N.H., Khan, R., Jumaat, M.Z. and Shariati, M. (2016b), "Behavior of industrial steel rack connections", Mech. Syst. Signal Pr., 7071, 725-740. https://doi.org/10.1016/j.ymssp.2015.08.026.
  117. Shah, S.N.R., Ramli Sulong, N.H., Jumaat, M.Z. and Shariati, M. (2015), "Steel rack connections: Identification of most influential factors and a comparison of stiffness design methods", PLoS One, 10(10), e0139422. https://doi.org/10.1371/journal.pone.0139422.
  118. Shah, S.N.R., Ramli Sulong, N.H., Khan, R., Jumaat, M.Z. and Shariati, M. (2016c), "Behavior of steel pallet rack beam-to-column connections at elevated temperatures", Thin Wall. Struct., 106, 471-483. https://doi.org/10.1016/j.tws.2016.05.021.
  119. Shahabi, S.E.M., Ramli Sulong, N.H., Shariati, M., Mohammadhassani, M. and Shah, S.N.R. (2016a), "Numerical analysis of channel connectors under fire and a comparison of performance with different types of shear connectors subjected to fire", Steel Compos. Struct., 20(3), 651-669. https://doi.org/10.12989/scs.2016.20.3.651.
  120. Shahabi, S.E.M., Ramli Sulong, N.H., Shariati, M. and Shah, S.N.R. (2016b), "Performance of shear connectors at elevated temperatures-A review", Steel Compos. Struct., 20(1), 185-203. https://doi.org/10.12989/scs.2016.20.1.185.
  121. Shariat, M., Shariati, M., Madadi, A. and Wakil, K. (2018), "Computational Lagrangian Multiplier Method by using for optimization and sensitivity analysis of rectangular reinforced concrete beams", Steel Compos. Struct., 29(2), 243-256. https://doi.org/10.12989/scs.2018.29.2.243.
  122. Shariati, A., Ramli Sulong, N.H., Suhatril, M. and Shariati, M. (2012a), "Various types of shear connectors in composite structures: A review", Int. J. Phys. Sci., 7(22), 2876-2890. https://doi.org/10.5897/IJPSx11.004.
  123. Shariati, A., Shariati, M., Ramli Sulong, N.H., Suhatril, M., Khanouki, M.M.A. and Mahoutian, M. (2014a), "Experimental assessment of angle shear connectors under monotonic and fully reversed cyclic loading in high strength concrete", Constr. Build. Mater., 52, 276-283. https://doi.org/10.1016/j.conbuildmat.2013.11.036.
  124. Shariati, A., Sulong, N., Suhatril, M. and Shariati, M. (2012b), "Investigation of channel shear connectors for composite concrete and steel T-beam", Int. J. Phys. Sci., 7(11), 11828-11831. https://doi.org/10.5897/IJPS11.1604.
  125. Shariati, M. (2008), "Assessment building using none-destructive test techniques (ultrasonic pulse velocity and Schmidt rebound hammer)", Universiti Putra Malaysia.
  126. Shariati, M. (2013), "Behaviour of C-shaped shear connectors in steel concrete composite beams", Jabatan Kejuruteraan Awam, Fakulti Kejuruteraan, Universiti Malaya.
  127. Shariati, M., Faegh, S.S., Mehrabi, P., Bahavarnia, S., Zandi, Y., Masoom, D.R., Toghroli, A., Trung, N.T. and Salih, M.N.A. (2019a), "Numerical study on the structural performance of corrugated low yield point steel plate shear walls with circular openings", Steel Compos. Struct., 33(4), 569-581. https://doi.org/10.12989/scs.2019.33.4.569.
  128. Shariati, M., Ghorbani, M., Naghipour, M., Alinejad, N. and Toghroli, A. (2020a), "The effect of RBS connection on energy absorption in tall buildings with braced tube frame system", Steel Compos. Struct., 34(3), 393-408. https://doi.org/10.12989/scs.2020.34.3.393.
  129. Shariati, M., Grayeli, M., Shariati, A. and Naghipour, M. (2020b), "Performance of composite frame consisting of steel beams and concrete filled tubes under fire loading", Steel Compos. Struct., 36(5), 587-602. https://doi.org/10.12989/scs.2020.36.5.587.
  130. Shariati, M., Heyrati, A., Zandi, Y., Laka, H., Toghroli, A., Kianmehr, P., Safa, M., Salih, M.N.A. and Poi-Ngian, S. (2019b), "Application of waste tire rubber aggregate in porous concrete", Smart Struct. Syst., 24(4), 553-566. https://doi.org/10.12989/sss.2019.24.4.553.
  131. Shariati, M., Lagzian, M., Maleki, S., Shariati, A. and Trung, N.T. (2020c), "Evaluation of seismic performance factors for tension-only braced frames", Steel Compos. Struct., 35(4), 599-609. https://doi.org/10.12989/scs.2020.35.4.599.
  132. Shariati, M., Mafipour, M.S., Ghahremani, B., Azarhomayun, F., Ahmadi, M., Trung, N.T. and Shariati, A. (2020d), "A novel hybrid extreme learning machine-grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement", Eng. Comput., 1-23. https://doi.org/10.1007/s00366-020-01081-0.
  133. Shariati, M., Mafipour, M.S., Haido, J.H., Yousif, S.T., Toghroli, A., Trung, N.T. and Shariati, A. (2020e), "Identification of the most influencing parameters on the properties of corroded concrete beams using an adaptive neuro-fuzzy inference system (ANFIS)", Steel Compos. Struct., 34(1), 155-170. https://doi.org/10.12989/scs.2020.34.1.155.
  134. Shariati, M., Mafipour, M.S., Mehrabi, P., Ahmadi, M., Wakil, K., Trung, N.T. and Toghroli, A. (2020f), "Prediction of concrete strength in presence of furnace slag and fly ash using hybrid ANN-GA (Artificial Neural Network-Genetic Algorithm)", Smart Struct. Syst., 25(2), 183-195. https://doi.org/10.12989/sss.2020.25.2.183.
  135. Shariati, M., Mafipour, M.S., Mehrabi, P., Bahadori, A., Zandi, Y., Salih, M.N.A., Nguyen, H., Dou, J., Song, X. and Poi-Ngian, S. (2019c), "Application of a hybrid artificial neural network-particle swarm optimization (ANN-PSO) model in behavior prediction of channel shear connectors embedded in normal and high-strength concrete", Appl. Sci., 9(24), 5534. https://doi.org/10.3390/app9245534.
  136. Shariati, M., Mafipour, M.S., Mehrabi, P., Toghroli, A., Trung, N. T. and Salih, M.N.A. (2020g), "A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques", Eng. Comput., 1-21. https://doi.org/10.1007/s00366-019-00930-x.
  137. Shariati, M., Mafipour, M.S., Mehrabi, P., Zandi, Y., Dehghani, D., Bahadori, A., Shariati, A., Trung, N.T., Salih, M.N.A. and Poi-Ngian, S. (2019d), "Application of extreme learning machine (ELM) and genetic programming (GP) to design steel-concrete composite floor systems at elevated temperatures", Steel Compos. Struct., 33(3), 319-332. https://doi.org/10.12989/scs.2019.33.3.319.
  138. Shariati, M., Naghipour, M., Yousofizinsaz, G., Toghroli, A. and Tabarestani, N.P. (2020h), "Numerical study on the axial compressive behavior of built-up CFT columns considering different welding lines", Steel Compos. Struct., 34(3), 377-391. https://doi.org/10.12989/scs.2020.34.3.377.
  139. Shariati, M., Rafie, S., Zandi, Y., Fooladvand, R., Gharehaghaj, B., Mehrabi, P., Shariat, A., Trung, N.T., Salih, M.N.A. and Poi-Ngian, S. (2019e), "Experimental investigation on the effect of cementitious materials on fresh and mechanical properties of self-consolidating concrete", Adv. Concr. Constr., 8(3), 225-237. https://doi.org/10.12989/acc.2019.8.3.225.
  140. Shariati, M., Ramli Sulong, N.H. and Khanouki, M.M.A. (2012d), "Experimental assessment of channel shear connectors under monotonic and fully reversed cyclic loading in high strength concrete", Mater. Des., 34, 325-331. https://doi.org/10.1016/j.matdes.2011.08.008.
  141. Shariati, M., Ramli Sulong, N.H., Suhatril, M., Shariati, A., Khanouki, M.M.A. and Sinaei, H. (2012e), "Behaviour of C-shaped angle shear connectors under monotonic and fully reversed cyclic loading: An experimental study", Mater. Des., 41, 67-73. https://doi.org/10.1016/j.matdes.2012.04.039.
  142. Shariati, M., Ramli Sulong, N.H., Suhatril, M., Shariati, A., Khanouki, M.M.A. and Sinaei, H. (2013), "Comparison of behaviour between channel and angle shear connectors under monotonic and fully reversed cyclic loading", Constr. Build. Mater., 38, 582-593. https://doi.org/10.1016/j.conbuildmat.2012.07.050.
  143. Shariati, M., Tahir, M.M., Wee, T.C., Shah, S.N.R., Jalali, A., Abdullahi, M.M. and Khorami, M. (2018), "Experimental investigations on monotonic and cyclic behavior of steel pallet rack connections", Eng. Fail. Anal., 85, 149-166. https://doi.org/10.1016/j.engfailanal.2017.08.014.
  144. Shariati, M., Tahmasbi, F., Mehrabi, P., Bahadori, A. and Toghroli, A. (2020i), "Monotonic behavior of C and L shaped angle shear connectors within steel-concrete composite beams: an experimental investigation", Steel Compos. Struct., 35(2), 237-247. https://doi.org/10.12989/scs.2020.35.2.237.
  145. Shariati, M., Toghroli, A., Jalali, A. and Ibrahim, Z. (2017), "Assessment of stiffened angle shear connector under monotonic and fully reversed cyclic loading", Proceedings og the Fifth International Conference on Advances in Civil, Structural and Mechanical Engineering-CSM 2017.
  146. Shariati, M., Trung, N.T., Wakil, K., Mehrabi, P., Safa, M. and Khorami, M. (2019f), "Moment-rotation estimation of steel rack connection using extreme learning machine", Steel Compos. Struct., 31(5), 427-435. https://doi.org/10.12989/scs.2019.31.5.427.
  147. Sharifuzzaman Sagar, A.S.M., Chen, Y., Xie, Y. and Kim, H.S. (2024), "MSA R-CNN: A comprehensive approach to remote sensing object detection and scene understanding", Expert Syst. Appl., 241, 122788. https://doi.org/10.1016/j.eswa.2023.122788.
  148. Shi, W., Miao, Z., Wang, Q. and Zhang, H. (2013), "Spectral-spatial classification and shape features for urban road centerline extraction", IEEE Geosci. Remote Sens. Lett., 11(4), 788-792. https://doi.org/10.1109/LGRS.2013.2280618.
  149. Shvets, A.A., Rakhlin, A., Kalinin, A.A. and Iglovikov, V.I. (2018), "Automatic instrument segmentation in robot-assisted surgery using deep learning", Proceedings of the 2018 17th IEEE international conference on machine learning and applications (ICMLA), IEEE.
  150. Sinaei, H., Jumaat, M.Z. and Shariati, M. (2011), "Numerical investigation on exterior reinforced concrete beam-column joint strengthened by composite fiber reinforced polymer (CFRP)", Int. J. Phys. Sci., 6(28), 6572-6579. https://doi.org/10.5897/IJPS11.1225.
  151. Sinaei, H., Shariati, M., Abna, A.H., Aghaei, M. and Shariati, A. (2012), "Evaluation of reinforced concrete beam behaviour using finite element analysis by ABAQUS", Sci. Res. Essays, 7(21), 2002-2009. https://doi.org/10.5897/SRE11.1393.
  152. Song, M. and Civco, D. (2004), "Road extraction using SVM and image segmentation", Photogram. Eng. Remote Sens., 70(12), 1365-1371. https://doi.org/10.14358/PERS.70.12.1365.
  153. Sun, J. and Vu, T.T. (2016), "Distributed and hierarchical object-based image analysis for damage assessment: A case study of 2008 Wenchuan earthquake, China", Geomatics, Natural Hazard Risk, 7(6), 1962-1972. https://doi.org/10.1080/19475705.2016.1160302.
  154. Szegedy, C., Ioffe, S., Vanhoucke, V. and Alemi, A. (2017). "Inception-v4, inception-resnet and the impact of residual connections on learning", Proceedings of the AAAI conference on artificial intelligence.
  155. Tahmasbi, F., Maleki, S., Shariati, M., Ramli Sulong, N.H. and Tahir, M.M. (2016), "Shear capacity of C-shaped and L-shaped angle shear connectors", PLoS One, 11(8), e0156989. https://doi.org/10.1371/journal.pone.0156989.
  156. Thongsuwan, S., Jaiyen, S., Padcharoen, A. and Agarwal, P. (2021), "ConvXGB: A new deep learning model for classification problems based on CNN and XGBoost", Nucl. Eng. Technol., 53(2), 522-531. https://doi.org/10.1016/j.net.2020.07.025.
  157. Tiana, T. and Thiagi, S.J. (2023), "Comprehensive predictive modeling of earthquake resilience in multi-story buildings utilizing advanced machine learning techniques", Int. J. Civil Eng. Adv., 1(1), 10-19.
  158. Tiwari, K.C., Arora, M.K. and Singh, D. (2011), "An assessment of independent component analysis for detection of military targets from hyperspectral images", Int. J. Appl. Earth Observ. Geoinform., 13(5), 730-740. https://doi.org/10.1016/j.jag.2011.05.009.
  159. Toghroli, A. (2015), "Applications of the ANFIS and LR models in the prediction of shear connection in composite beams", Jabatan Kejuruteraan Awam, Fakulti Kejuruteraan, Universiti Malaya.
  160. Toghroli, A., Darvishmoghaddam, E., Zandi, Y., Parvan, M., Safa, M., Abdullahi, M.M., Heydari, A., Wakil, K., Gebreel, S.A.M. and Khorami, M. (2018a), "Evaluation of the parameters affecting the Schmidt rebound hammer reading using ANFIS method", Comput. Concr., 21(5), 525-530. https://doi.org/10.12989/cac.2018.21.5.525.
  161. Toghroli, A., Mehrabi, P., Shariati, M., Trung, N. T., Jahandari, S. and Rasekh, H. (2020), "Evaluating the use of recycled concrete aggregate and pozzolanic additives in fiber-reinforced pervious concrete with industrial and recycled fibers", Constr. Build. Mater., 252, 118997. https://doi.org/10.1016/j.conbuildmat.2020.118997.
  162. Toghroli, A., Mohammadhassani, M., Suhatril, M., Shariati, M. and Ibrahim, Z. (2014), "Prediction of shear capacity of channel shear connectors using the ANFIS model", Steel Compos. Struct., 17(5), 623-639. https://doi.org/10.12989/scs.2014.17.5.623.
  163. Toghroli, A., Shariati, M., Karim, M.R. and Ibrahim, Z. (2017). "Investigation on composite polymer and silica fume-rubber aggregate pervious concrete", Proceedings of the Fifth International Conference on Advances in Civil, Structural and Mechanical Engineering - CSM 2017, Zurich, Switzerland.
  164. Toghroli, A., Shariati, M., Sajedi, F., Ibrahim, Z., Koting, S., Mohamad, E.T. and Khorami, M. (2018b), "A review on pavement porous concrete using recycled waste materials", Smart Struct. Syst., 22(4), 433-440. https://doi.org/10.12989/sss.2018.22.4.433.
  165. Toghroli, A., Suhatril, M., Ibrahim, Z., Safa, M., Shariati, M. and Shamshirband, S. (2016), "Potential of soft computing approach for evaluating the factors affecting the capacity of steel-concrete composite beam", J. Intell. Manuf., 29(8), 1793-1801. https://doi.org/10.1007/s10845-016-1217-y.
  166. Troya-Galvis, A., Gancarski, P., Passat, N. and Berti-Equille, L. (2015), "Unsupervised quantification of under-and over-segmentation for object-based remote sensing image analysis", IEEE J. Select. Topics Appl. Earth Observ. Remote Sens., 8(5), 1936-1945. https://doi.org/10.1109/JSTARS.2015.2418616.
  167. Trung, N.T., Alemi, N., Haido, J.H., Shariati, M., Baradaran, S. and Yousif, S.T. (2019a), "Reduction of cement consumption by producing smart green concretes with natural zeolites", Smart Struct. Syst., 24(3), 415-425. https://doi.org/10.12989/sss.2019.24.3.415.
  168. Trung, N.T., Shahgoli, A.F., Zandi, Y., Shariati, M., Wakil, K., Safa, M. and Khorami, M. (2019b), "Moment-rotation prediction of precast beam-to-column connections using extreme learning machine", Struct. Eng. Mech., 70(5), 639-647. https://doi.org/10.12989/sem.2019.70.5.639.
  169. Unsalan, C. and Sirmacek, B. (2012), "Road network detection using probabilistic and graph theoretical methods", IEEE T. Geosci. Remote Sens., 50(11), 4441-4453. https://doi.org/10.1109/TGRS.2012.2194158.
  170. Van Engelen, J. E. and Hoos, H. H. (2020), "A survey on semi-supervised learning", Machine Learn., 109(2), 373-440. https://doi.org/10.1007/s10994-019-05855-6.
  171. Van, E.A., Lindenbaum, D. and Bacastow, T. (2018), "Spacenet: A remote sensing dataset and challenge series", arXiv preprint arXiv:1807.01232.
  172. Visin, F., Ciccone, M., Romero, A., Kastner, K., Cho, K., Bengio, Y., Matteucci, M. and Courville, A. (2016), "Reseg: A recurrent neural network-based model for semantic segmentation", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops.
  173. Volpi, M. and Ferrari, V. (2015), "Semantic segmentation of urban scenes by learning local class interactions", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops.
  174. Wang, J., Qin, Q., Yang, X., Wang, J., Ye, X. and Qin, X. (2014), "Automated road extraction from multi-resolution images using spectral information and texture", 2014 IEEE Geoscience and Remote Sensing Symposium, IEEE.
  175. Wang, J., Song, J., Chen, M. and Yang, Z. (2015), "Road network extraction: A neural-dynamic framework based on deep learning and a finite state machine", Int. J. Remote Sens., 36(12), 3144-3169. https://doi.org/10.1080/01431161.2015.1054047.
  176. Wang, M. and Luo, C. (2005), "Extracting roads based on Gauss Markov random field texture model and support vector machine from high-resolution RS image", IEEE T. Geosci. Remote Sens., 9, 271-276. https://doi.org/10.1109/TGRS.2005.848660.
  177. Wang, M., Tan, K., Jia, X., Wang, X. and Chen, Y. (2020), "A deep siamese network with hybrid convolutional feature extraction module for change detection based on multi-sensor remote sensing images", Remote Sens., 12(2), 205. https://doi.org/10.3390/rs12020205.
  178. Wang, Q., Wan, J., Nie, F., Liu, B., Yan, C. and Li, X. (2018), "Hierarchical feature selection for random projection", IEEE Transact. Neural Netw. Learn. Syst., 30(5), 1581-1586. https://doi.org/10.1109/TNNLS.2018.2879547.
  179. Wang, S., Guan, K., Zhang, C., Lee, D., Margenot, A. J., Ge, Y., Peng, J., Zhou, W., Zhou, Q. and Huang, Y. (2022), "Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing", Remote Sens. Environ., 271, 112914. https://doi.org/10.1016/j.rse.2021.112914.
  180. Wang, W., Yang, N., Zhang, Y., Wang, F., Cao, T. and Eklund, P. (2016), "A review of road extraction from remote sensing images", J. Traffic Transp. Eng., 3(3), 271-282. https://doi.org/10.1016/j.jtte.2016.05.005.
  181. Wei, X., Shariati, M., Zandi, Y., Pei, S.L., Jin, Z.B., Gharachurlu, S., Abdullahi, M.M., Tahir, M.M. and Khorami, M. (2018), "Distribution of shear force in perforated shear connectors", Steel Compos. Struct., 27(3), 389-399. https://doi.org/10.12989/scs.2018.27.3.389.
  182. Wei, Y., Wang, Z. and Xu, M. (2017), "Road structure refined CNN for road extraction in aerial image", IEEE Geosci. Remote Sens. Lett., 14(5), 709-713. https://doi.org/10.1109/LGRS.2017.2678380.
  183. Xie, Q., Sinaei, H., Shariati, M., Khorami, M., Mohamad, E.T. and Bui, D.T. (2019), "An experimental study on the effect of CFRP on behavior of reinforced concrete beam column connections", Steel Compos. Struct., 30(5), 433-441. https://doi.org/10.12989/scs.2019.30.5.433.
  184. Xin, J., Zhang, X., Zhang, Z. and Fang, W. (2019), "Road extraction of high-resolution remote sensing images derived from DenseUNet", Remote Sens., 11(21), 2499. https://doi.org/10.3390/rs11212499.
  185. Xu, C.H., Zhang, X.L., Haido, J.H., Mehrabi, P., Shariati, A., Mohamad, E.T., Nguyen, H. and Wakil, K. (2019), "Using genetic algorithms method for the paramount design of reinforced concrete structures", Struct. Eng. Mech., 71(5), 503-513. https://doi.org/10.12989/sem.2019.71.5.503.
  186. Xu, R. (2016), "A multistage method for road extraction from optical remotely sensed imagery", J. Inform. Hid. Multimed. Signal Proc., 7(2), 438-447.
  187. Xu, Y., Xie, Z., Feng, Y. and Chen, Z. (2018), "Road extraction from high-resolution remote sensing imagery using deep learning", Remote Sens., 10, 1461. https://doi.org/10.3390/rs10091461.
  188. Yang, L., Zhuo, W., Qi, L., Shi, Y. and Gao, Y. (2022), "St++: Make self-training work better for semi-supervised semantic segmentation", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.
  189. Yang, S., Feng, Q., Liang, T., Liu, B., Zhang, W. and Xie, H. (2018), "Modeling grassland above-ground biomass based on artificial neural network and remote sensing in the Three-River Headwaters Region", Remote Sens. Environ., 204, 448-455. https://doi.org/10.1016/j.rse.2017.11.018.
  190. Yazdani, M., Kabirifar, K., Frimpong, B.E., Shariati, M., Mirmozaffari, M. and Boskabadi, A. (2020), "Improving construction and demolition waste collection service in an urban area using a simheuristic approach: A case study in Sydney, Australia", J. Clean. Prod., 280, 124138. https://doi.org/10.1016/j.jclepro.2020.124138.
  191. Yousef Z.A.S.A. and Ramezani, M. (2023), "Advanced integration of IoT and neural networks for real-time structural health monitoring and assessment of bridges", Int. J. Civil Eng. Adv., 1(1), 1-9.
  192. Zandi, Y., Shariati, M., Marto, A., Wei, X., Karaca, Z., Dao, D. K., Toghroli, A., Hashemi, M.H., Sedghi, Y., Wakil, K. and Khorami, M. (2018), "Computational investigation of the comparative analysis of cylindrical barns subjected to earthquake", Steel Compos. Struct., 28(4), 439-447. https://doi.org/10.12989/scs.2018.28.4.439.
  193. Zhang, X. and Han, L. (2023), "A generic self-supervised learning (SSL) framework for representation learning from spectra-spatial feature of unlabeled remote sensing imagery", arXiv preprint arXiv:2306.15836. 2306
  194. Zhang, Y., Wang, X., Tan, H., Xu, C., Ma, X. and Xu, T. (2019), "Region merging method for remote sensing spectral image aided by inter-segment and boundary homogeneities", Remote Sens., 11(12), 1414. https://doi.org/10.3390/rs11121414.
  195. Zhang, Z., Liu, Q. and Wang, Y. (2018), "Road extraction by deep residual U-net", IEEE Geosci. Remote Sens. Lett., 15(5), 749-753. https://doi.org/10.1109/LGRS.2018.2802944.
  196. Zhou, J., Bischof, W.F. and Caelli, T. (2006), "Road tracking in aerial images based on human-computer interaction and Bayesian filtering", ISPRS J. Photogramm. Remote Sens., 61(2), 108-124. https://doi.org/10.1016/j.isprsjprs.2006.08.003.
  197. Ziaei-Nia, A., Shariati, M. and Salehabadi, E. (2018), "Dynamic mix design optimization of high-performance concrete", Steel Compos. Struct., 29(1), 67-75. https://doi.org/10.12989/scs.2018.29.1.067.