참고문헌
- Argyros A., Georgiadis P., Trahanias P. and Tsakiris D.(2002), "Semi-autonomous navigation of a robotic wheelchair," Journal of Intelligent and Robotic Systems, vol. 34, no. 3, pp.315-329. https://doi.org/10.1023/A:1016371922451
- Bang S., Park S., Kim H. and Kim H.(2019), "Encoder-decoder network for pixel-level road crack detection in black-box images," Computer Aided Civil and Infrastructure Engineering, vol. 34, no. 8, pp.713-727. https://doi.org/10.1111/mice.12440
- Borowsky A., Shinar D. and Oron-Gilad T.(2010), "Age, skill, and hazard perception in driving," Accident Analysis & Prevention, vol. 42, no. 4, pp.1240-1249. https://doi.org/10.1016/j.aap.2010.02.001
- Buza E., Omanovic S. and Huseinovic A.(2013), "A pothole detection with image processing and spectral clustering," In Proc. the 2nd International Conference on Information Technology and Computer Networks, Antalya, Turkeys, pp.48-53.
- Chen L., Yang Z., Ma J. and Luo Z.(2018), "Driving scene perception network: Real-time joint detection, depth estimation and semantic segmentation," In Proc. 2018 IEEE Winter Conference on Applications of Computer Vision(WACV), Lake Tahoe, NV, USA, pp.1283-1291.
- Chen X., Kundu K., Zhu Y., Ma H., Fidler S. and Urtasun R.(2017), "3d object proposals using stereo imagery for accurate object class detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, pp.1259-1272. https://doi.org/10.1109/TPAMI.2017.2706685
- Dumoulin V. and Visin F.(2016), A guide to convolution arithmetic for deep learning, arXiv:1603.07285. Available at https://arxiv.org/abs/1603.07285
- Fayyad J., Jaradat M. A., Gruyer D. and Najjaran H.(2020), "Deep learning sensor fusion for autonomous vehicle perception and localization: A review," Sensors, vol. 20, no. 15, 4220. https://doi.org/10.3390/s20154220
- Feng D., Haase-Schuetz C., Rosenbaum L., Hertlein H., Glaeser C., Timm F., Wiesbeck W. and Dietmayer K.(2020), "Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges," IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 3, pp.1-20.
- Girshick R.(2015), "Fast r-cnn," In Proc. the IEEE International Conference on Computer Vision(ICCV), Sangtiago, Chile, pp.1440-1448.
- Glorot X. and Bengio Y.(2010), "Understanding the difficulty of training deep feedforward neural networks," In Proc. 13th International Conference on Artificial Intelligence and Statistics(AISTATS), Sardinia, Italy, pp.249-256.
- He K., Gkioxari G., Dollar P. and Girshick R.(2017), "Mask r-cnn," In Proc. the IEEE International Conference on Computer Vision(ICCV), Venice, Italy, pp.2961-2969.
- He K., Zhang X., Ren S. and Sun J.(2016), "Deep residual learning for image recognition," In Proc. the IEEE Conference on Computer Vision and Pattern Recognition(CVPR), Las Vegas, NV, 2016, pp.770-778.
- Ilas C.(2013), "Electronic sensing technologies for autonomous ground vehicles: A review," In Proc. 8th International Symposium on Advanced Topics in Electrical Engineering(ATEE), Bucharest, Romania, pp.1-6.
- Jenkins M. D., Carr T. A., Iglesias M. I., Buggy T. and Morison G.(2018), "A deep convolutional neural network for semantic pixel-wise segmentation of road and pavement surface cracks," In Proc. 26th European Signal Processing Conference(EUSIPCO), Rome, Italy, pp.2120-2124.
- Jo Y., Ryu S. K. and Kim Y. R.(2016), "Pothole detection based on the features of intensity and motion," Journal of the Transportation Research Board, no. 2595, pp.18-28.
- Kingma D. P. and Ba J.(2014), Adam: A method for stochastic optimization, arXiv:1412.6980. Available at https://arxiv.org/abs/1412.6980
- Kobayashi Y., Kinpara Y., Shibusawa T. and Kuno Y.(2009), "Robotic wheelchair based on observations of people using integrated sensors," In Proc. 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, USA, pp.2013-2018.
- Koch C. and Brilakis I.(2011), "Pothole detection in asphalt pavement images," Advanced Engineering Information, vol. 25, no. 1, pp.507-515. https://doi.org/10.1016/j.aei.2011.01.002
- Li P. and Qin T.(2018), "Stereo vision-based semantic 3d object and ego-motion tracking for autonomous driving," In Proc. the European Conference on Computer Vision(ECCV), Munich, Germany, pp.646-661.
- Li P., Chen X. and Shen S.(2019), "Stereo r-cnn based 3d object detection for autonomous driving," In Proc. the IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), Long Beach, CA, USA, pp.7644-7652.
- Liu W., Anguelov D., Erhan D., Szegedy C., Reed S., Fu C. Y. and Berg A. C.(2016), "Ssd: Single shot multibox detector," In Proc. European Conference on Computer Vision (ECCV), Amsterdam, Netherlands, pp.21-37.
- Madli R., Hebbar S., Pattar P. and Golla V.(2015), "Automatic detection and notification of potholes and humps on roads to aid drivers," IEEE Sensors Journal, vol. 15, no. 8, pp.4313-4318. https://doi.org/10.1109/JSEN.2015.2417579
- Maeda H., Sekimoto Y., Seto T., Kashiyama T. and Omata H.(2018), "Road damage detection and classification using deep neural networks with smart phone images," Computer-Aided Civil and Infrastructure Engineering, vol. 33, no. 12, pp.1127-1141. https://doi.org/10.1111/mice.12387
- Muramatsu N. and Akiyama H.(2011), "Japan: Super-aging society preparing for the future," The Gerontologist, vol. 51, no. 4, pp.425-432. https://doi.org/10.1093/geront/gnr067
- Nakane J. and Farevaag M.(2004), "Elder care in Japan," Perspectives(Gerontological Nursing Association(Canada)), vol. 28, no. 1, pp.17-24.
- Redmon J. and Farhadi A.(2018), Yolov3: An incremental improvement, arXiv:1804.02767. Available at https://arxiv.org/abs/1804.02767
- Ren S., He K., Girshick R. and Sun J.(2015), Faster r-cnn: Towards real-time object detection with region proposal networks, arXiv:1506.01497. Available at https://arxiv.org/abs/1506.01497
- Ronneberger O., Fischer P. and Brox T.(2015), "U-net: Convolutional networks for biomedical image segmentation," In Proc. International Conference on Medical Image Computing and Computer-Assisted Intervention(MICCAI), Munich, Germany, pp.234-241.
- Shi Y., Cui L., Qi Z., Meng F. and Chen Z.(2016), "Automatic road crack detection using random structured forests," IEEE Transactions on Intelligent Transportation Systems, vol. 17, no. 12, pp.3434-3445. https://doi.org/10.1109/TITS.2016.2552248
- Shim S. and Cho G. C.(2020), "Lightweight semantic segmentation for road-surface damage recognition based on multiscale learning," IEEE Access, vol. 8, pp.102680-102690. https://doi.org/10.1109/access.2020.2998427
- Singh S.(2015), "Critical reasons for crashes investigated in the national motor vehicle crash causation survey," Traffic Safety Facts Crash Stats. Report No. DOT HS 812 115; National Center for Statistics and Analysis, Washington, DC, USA.
- Sistu G., Leang I. and Yogamani S.(2019), Real-time joint object detection and semantic segmentation network for automated driving, arXiv:1901.03912. Available at https://arxiv.org/abs/1901.03912
- Tinnila M. and Kalli J.(2015), "Impact of future trends on personal mobility services," International Journal of Automotive Technology and Management, vol. 15, no. 4, pp.401-417. https://doi.org/10.1504/IJATM.2015.072876
- Zhang S., Wen L., Bian X., Lei Z. and Li S. Z.(2018), "Single-shot refinement neural network for object detection," In Proc. the IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), Salt Lake City, UT, USA, pp.4203-4212.
- Zhao Q., Sheng T., Wang Y., Tang Z., Chen Y., Cai L. and Ling H.(2019), "M2det: A single-shot object detector based on multi-level feature pyramid network," In Proc. the AAAI Conference on Artificial Intelligence, Honolulu, HI, USA, vol. 33, no. 1, pp.9259-9266.
- Zou Q., Zhang Z., Li Q., Qi X., Wang Q. and Wang S.(2019), "DeepCrack: Learning hierarchical convolutional features for crack detection," IEEE Transactions on Image Processing, vol. 28, no. 3, pp.1498-1512. https://doi.org/10.1109/tip.2018.2878966