- Lecture 1: Course Overview
Monday 23 August 2021
Whiteboard
- Lecture 2: Automatic Differentiation---I
A.G. Baydin, B.A. Pearlmutter, A.A. Radul, and J.M. Siskind, `Automatic differentiation in machine learning: a survey,' Journal of Machine Learning Research (JMLR), 18(153):1-43, 2018.
Wednesday 25 August 2021
Whiteboard
- Lecture 3: Automatic Differentiation---II
Friday 27 August 2021
Whiteboard
forward_mode.py
newton_raphson.py
- Lecture 4: Automatic Differentiation---III
Monday 30 August 2021
Whiteboard
- Lecture 5: Automatic Differentiation---IV
Wednesday 1 September 2021
Whiteboard
- Lecture 6: Automatic Differentiation---V
Friday 3 September 2021
Whiteboard
- Lecture 7: Automatic Differentiation---VI
B.A. Pearlmutter and J.M. Siskind, `Reverse-Mode AD in a functional framework: Lambda the Ultimate Backpropagator,' ACM Transactions on Programming Languages and Systems (TOPLAS), 30(2):1-36, 2008.
Wednesday 8 September 2021
Whiteboard
- Lecture 8: Automatic Differentiation---VII
J.M. Siskind and B.A. Pearlmutter, `Nesting forward-mode AD in a functional framework,' Higher-Order and Symbolic Computation (HOSC), 21(4):361-376, 2008.
Friday 10 September 2021
Whiteboard
- Lecture 9: Automatic Differentiation---VIII
Monday 13 September 2021
Whiteboard
- Lecture 10: Automatic Differentiation---IX
Wednesday 15 September 2021
Whiteboard
- Lecture 11: Automatic Differentiation---X
Friday 17 September 2021
Whiteboard
tracing.py
reverse_mode.py
- Lecture 12: Automatic Differentiation---XI
Monday 20 September 2021
Whiteboard
gui.py
linear_classifier.py
linear_classifier_gui.py
linear_classifier_pytorch_gui.py
two_layer_perceptron.py
two_layer_perceptron_gui.py
two_layer_perceptron_pytorch_gui.py
- Lecture 13: Model-Based Vision
D.G. Lowe, `Three-dimensional object recognition from single two-dimensional images,' Artificial Intelligence (AIJ), 31(3):355-395, 1987.
Wednesday 22 September 2021
Whiteboard
- Lecture 14: Histograms of Oriented Gradients
N. Dalal and B. Triggs, `Histograms of oriented gradients for human detection,' Computer Vision and Pattern Recognition (CVPR), pp. 886-893, 2005.
Friday 24 September 2021
Whiteboard
- Lecture 15: Deformable Part Models
P.F. Felzenszwalb, R.B. Girshick, D. McAllester, and D Ramanan, `Object detection with discriminatively trained part-based models,' IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 32(9):1627-1645, 2010.
Monday 27 September 2021
Whiteboard
- Lecture 16: AlexNet
A. Krizhevsky, I. Sutskever, and G.E. Hinton, `ImageNet classification with deep convolutional neural networks,' Advances in Neural Information Processing Systems (NeurIPS), pages 1097-1105, 2012.
Wednesday 29 September 2021
Whiteboard
- Lecture 17: VGG-16
K. Simonyan and A. Zisserman, `Very deep convolutional networks for large-scale image recognition,' International Conference on Learning Representations (ICLR), 2015.
Friday 1 October 2021
Whiteboard
- Lecture 18: Inception v1
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, `Going deeper with convolutions,' Computer Vision and Pattern Recognition (CVPR), 2015.
Monday 4 October 2021
Whiteboard
- Lecture 19: Batch Normalization
S. Ioffe and C. Szegedy, `Batch normalization: accelerating deep network training by reducing internal covariate shift,' International Conference on Machine Learning (ICML), pp. 448-456, 2015.
Wednesday 6 October 2021
Whiteboard
- Lecture 20: ResNet
K. He, X. Zhang, S. Ren, and J. Sun, `Deep residual learning for image recognition,' Computer Vision and Pattern Recognition (CVPR), pp. 770-778, 2016.
Friday 8 October 2021
Whiteboard
- Lecture 21: Inception v3
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna, `Rethinking the Inception architecture for computer vision,' Computer Vision and Pattern Recognition (CVPR), pp. 2818-2826, 2016.
Wednesday 13 October 2021
Whiteboard
- Lecture 22: No class
Friday 15 October 2021
- Lecture 23: DenseNet
G. Huang, Z. Liu, L. Van Der Maaten, and K.Q. Weinberger, `Densely connected convolutional networks,' Computer Vision and Pattern Recognition (CVPR), pp. 4700-4708, 2017.
Monday 18 October 2021
Whiteboard
- Lecture 24: R-CNN
R. Girshick, J. Donahue, T. Darrell, and J. Malik, `Rich feature hierarchies for accurate object detection and semantic segmentation,' Computer Vision and Pattern Recognition (CVPR), pp. 580-587, 2014.
Wednesday 20 October 2021
Whiteboard
- Lecture 25: Fast R-CNN
R. Girshick, `Fast R-CNN,' Computer Vision and Pattern Recognition (CVPR), pp. 1440-1448, 2015.
Friday 22 October 2021
Whiteboard
- Lecture 26: Faster R-CNN
S. Ren, K. He, R. Girshick, and J. Sun, `Faster R-CNN: Towards real-time object detection with region proposal networks,' Advances in Neural Information Processing Systems (NeurIPS), pp. 91-99, 2015.
Monday 25 October 2021
Whiteboard
- Lecture 27: YOLO
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, `You only look once: Unified, real-time object detection,' Computer Vision and Pattern Recognition (CVPR), pp. 779-788, 2016.
Wednesday 27 October 2021
Whiteboard
- Lecture 28: No class
Friday 29 October 2021
- Lecture 29: SSD
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A.C. Berg, `SSD: Single shot multibox detector,' European Conference on Computer Vision (ECCV), pp. 21-37, 2016.
Monday 1 November 2021
Whiteboard
- Lecture 30: Mask R-CNN
K. He, G. Gkioxari, P. Dollar, and R. Girshick, `Mask R-CNN,' International Conference on Computer Vision (ICCV), pp. 2961-2969, 2017.
Wednesday 3 November 2021
Whiteboard
- Lecture 31: FPN
T.-Y. Lin, P. Dollar, R. Girshick, K. He, B. Hariharan, and S. Belongie, `Feature pyramid networks for object detection,' Computer Vision and Pattern Recognition (CVPR), pp. 2117-2125, 2017.
Friday 5 November 2021
Whiteboard
- Lecture 32: YOLO v2
J. Redmon and A. Farhadi, `YOLO9000: better, faster, stronger,' Computer Vision and Pattern Recognition (CVPR), pp. 7263-7271, 2017.
Monday 8 November 2021
Whiteboard
- Lecture 33: DeepVideo
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei, `Large-scale video classification with convolutional neural networks,' Computer Vision and Pattern Recognition (CVPR), pp. 1725-1732, 2014.
Wednesday 10 November 2021
Whiteboard
- Lecture 34: Student Presentations
Friday 12 November 2021
Whiteboard
- Lecture 35: No class
Monday 15 November 2021
- Lecture 36: Student Presentations
Wednesday 17 November 2021
Whiteboard
- Lecture 37: Student Presentations
Friday 19 November 2021
Whiteboard
- Lecture 38: Student Presentations
Monday 22 November 2021
Whiteboard
- Lecture 39: Student Presentations
Monday 29 November 2021
Whiteboard
- Lecture 40: Student Presentations
Wednesday 1 December 2021
Whiteboard
- Lecture 41: Student Presentations
Friday 3 December 2021
Whiteboard
- Lecture 42: Student Presentations
Monday 6 December 2021
Whiteboard
- Lecture 43: Student Presentations
Wednesday 8 December 2021
Whiteboard
- Lecture 44: Student Presentations
Friday 10 December 2021
Whiteboard
ECE59500CV | Elmore Family ECE | Purdue College of Engineering | Purdue University
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