Deep Learning - Introduction Part 5

 

Deep Learning - Introduction Part 5   This video introduces the topic of Deep Learning and presents the course's requirements, grading procedures, and summarises the first unit.   Video References: Lex Fridman's Channel   References
[1] David Silver, Julian Schrittwieser, Karen Simonyan, et al. “Mastering the game of go without human knowledge”. In: Nature 550.7676 (2017), p. 354.
[2] David Silver, Thomas Hubert, Julian Schrittwieser, et al. “Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm”. In: arXiv preprint arXiv:1712.01815 (2017).
[3] M. Aubreville, M. Krappmann, C. Bertram, et al. “A Guided Spatial Transformer Network for Histology Cell Differentiation”. In: ArXiv e-prints (July 2017). arXiv: 1707.08525 [cs.CV].
[4] David Bernecker, Christian Riess, Elli Angelopoulou, et al. “Continuous short-term irradiance forecasts using sky images”. In: Solar Energy 110 (2014), pp. 303–315.
[5] Patrick Ferdinand Christ, Mohamed Ezzeldin A Elshaer, Florian Ettlinger, et al. “Automatic liver and lesion segmentation in CT using cascaded fully convolutional neural networks and 3D conditional random fields”. In: International Conference on Medical Image Computing and Computer-Assisted Springer. 2016, pp. 415–423.
[6] Vincent Christlein, David Bernecker, Florian Hönig, et al. “Writer Identification Using GMM Supervectors and Exemplar-SVMs”. In: Pattern Recognition 63 (2017), pp. 258–267.
[7] Florin Cristian Ghesu, Bogdan Georgescu, Tommaso Mansi, et al. “An Artificial Agent for Anatomical Landmark Detection in Medical Images”. In: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016. Athens, 2016, pp. 229–237.
[8] Jia Deng, Wei Dong, Richard Socher, et al. “Imagenet: A large-scale hierarchical image database”. In: Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference IEEE. 2009, pp. 248–255.
[9] A. Karpathy and L. Fei-Fei. “Deep Visual-Semantic Alignments for Generating Image Descriptions”. In: ArXiv e-prints (Dec. 2014). arXiv: 1412.2306 [cs.CV].
[10] Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. “ImageNet Classification with Deep Convolutional Neural Networks”. In: Advances in Neural Information Processing Systems 25. Curran Associates, Inc., 2012, pp. 1097–1105.
[11] Joseph Redmon, Santosh Kumar Divvala, Ross B. Girshick, et al. “You Only Look Once: Unified, Real-Time Object Detection”. In: CoRR abs/1506.02640 (2015).
[12] J. Redmon and A. Farhadi. “YOLO9000: Better, Faster, Stronger”. In: ArXiv e-prints (Dec. 2016). arXiv: 1612.08242 [cs.CV].
[13] Joseph Redmon and Ali Farhadi. “YOLOv3: An Incremental Improvement”. In: arXiv (2018).
[14] Frank Rosenblatt. The Perceptron–a perceiving and recognizing automaton. 85-460-1. Cornell Aeronautical Laboratory, 1957.
[15] Olga Russakovsky, Jia Deng, Hao Su, et al. “ImageNet Large Scale Visual Recognition Challenge”. In: International Journal of Computer Vision 115.3 (2015), pp. 211–252.
[16] David Silver, Aja Huang, Chris J. Maddison, et al. “Mastering the game of Go with deep neural networks and tree search”. In: Nature 529.7587 (Jan. 2016), pp. 484–489.
[17] S. E. Wei, V. Ramakrishna, T. Kanade, et al. “Convolutional Pose Machines”. In: CVPR. 2016, pp. 4724–4732.
[18] Tobias Würfl, Florin C Ghesu, Vincent Christlein, et al. “Deep learning computed tomography”. In: International Conference on Medical Image Computing and Computer-Assisted Springer International Publishing. 2016, pp. 432–440.   Further Reading A gentle Introduction to Deep Learning