References
- V. Vartanian, R. Attota, H. Park, G. Orji, R. A. Allen, "TSV reveal height and dimension metrology by the TSOM method" Proc. SPIE 8681, 10.1117/12.2012609, 2012
- R. Attota, R. G. Dixson, J. A. Kramar, J. E. Potzick, A. E. Vladar, B. Bunday, E. Novak, A. Rudack, "TSOM method for semiconductor metrology", Proc. SPIE 7971, doi: 10.1117/12.881620, 2011
- R. Attota, R. Silver, and R. Dixson, "Linewidth measurement technique using through-focus optical images," Appl. Opt. 47(4), 495-503 (2008). https://doi.org/10.1364/AO.47.000495
- S. Usha, P. V Shashikumar, G. C. Mohankumar, and S. S. Rao, "Through Focus Optical Imaging Technique To Analyze Variations In Nano-Scale Indents," J. Biomed. Opt. 23(07), 1-100 (2018).
- Y. Qu, J. Hao, and R. Peng, "Machine-learning models for analyzing TSOM images of nanostructures," Opt. Express 27(23), 33978 (2019). https://doi.org/10.1364/oe.27.033978
- H Nie, R Peng, J Ren, Y Qu, "A through-focus scanning optical microscopy dimensional measurement method based on deep-learning classification model," Journal of Microscopy, 2021
- He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 770-778). Piscataway, New Jersey: IEEE.
- Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017). Densely connected convolutional networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4700-4708). Piscataway, New Jersey: IEEE.
- Arceo, A., Bunday, B., and Attota, R., "Use of TSOM for sub-11nm node pattern defect detection and HAR features," Proc. SPIE 8681, 86812G (2013)
- Lee, J. H., Park, J. H., Jeong, D., Shin, E. J. and Park, C., "Tip/tilt-compensated through-focus scanning optical microscopy," Proc. SPIE 10023, 100230P (2016).
- http://www.nextinsol.com/
- I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. Cambridge, MA, USA: MIT Press, 2016.
- Selvaraju, Ramprasaath R., Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra. "Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization." In ICCV, pp. 618-626. 2017
- Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong, and Richard Socher. A closer look at deep learning heuristics: Learning rate restarts, warmup and distillation. arXiv preprint arXiv:1810.13243, 2018.
- Kingma, Diederik P and Ba, Jimmy Lei. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980, 2014.
- Siddharth Mahendran, Haider Ali, and Rene Vidal. A mixed classification-regression framework for 3D pose estimation from 2D images. In British Machine Vision Conference (BMVC), 2018.
- Z. Niu, M. Zhou, L. Wang, X. Gao, G. Hua, Ordinal regression with multiple output cnn for age estimation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 4920-4928.
- Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: CVPR (2016)
- O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, et al, "Imagenet large scale visual recognition challenge," International Journal of Computer Vision, Vol 15, No 3, pp. 211-252, 2015
- Sung Joo Kim, and Kim Gyung Bum, "A Study on the Classification of Surface Defect Based on Deep Convolution Network and Transfer-learning," Journal of the Semiconductor & Display Technology, Vol. 20, No. 1. March 2021.
- Sung-jin Hwang, and Seok-woo Hong, Jong-seo Yoon, Heemin Park, Hyun-chul Kim, "Deep Learning-based Pothole Detection System," Journal of the Semiconductor & Display Technology, Vol. 20, No. 1. March 2021.
- Song-Yeon Lee, and Yong Jeong Huh, "A Study on Shape Warpage Defect Detecion Model of Scaffold Using Deep Learning Based CNN," Journal of the Semiconductor & Display Technology, Vol. 20, No. 1. March 2021.