General Information

Lectures: M,W,F 9:30am - 10:20am, PHYS 111

Instructor: Jeffrey Mark Siskind, BHEE313e, 765/496-3197, qobi@purdue.edu
Office Hours: T 5:00pm - 6:00pm, BHEE313e

ece49595cv-students-list@ecn.purdue.edu
ece49595cv-staff-list@ecn.purdue.edu

Syllabus

Brightspace

BibTeX file for papers we will cover in this course

github repository

Web site for Fall 2020 offering of a similar course

Web site for Fall 2021 offering of a similar course

image and video retrieval

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• Homework 1
  Due 5:00pm ET Friday 29 September 2023
  

• Homework 2
  Due 5:00pm ET Friday 27 October 2023
  

• Homework 3
  Due 5:00pm ET Friday 24 November 2023
  

• Lecture 1: Course Overview
  Monday 21 August 2023
  

• 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 23 August 2023
  Whiteboard
  code_w23aug2023a.py
  code_w23aug2023b.py
  

• Lecture 3: Automatic Differentiation---II
  Friday 25 August 2023
  Whiteboard
  complex.py
  

• Lecture 4: Automatic Differentiation---III
  Monday 28 August 2023
  Whiteboard
  forward_mode.py
  newton_raphson.py
  

• Lecture 5: Automatic Differentiation---IV
  Wednesday 30 August 2023
  Whiteboard
  

• Lecture 6: Automatic Differentiation---V
  Friday 1 September 2023
  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 6 September 2023
  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 8 September 2023
  Whiteboard
  

• Lecture 9: Automatic Differentiation---VIII
  Monday 11 September 2023
  Whiteboard
  

• Lecture 10: Automatic Differentiation---IX
  Wednesday 13 September 2023
  Whiteboard
  

• Lecture 11: Automatic Differentiation---X
  Friday 15 September 2023
  Whiteboard
  tracing.py
  reverse_mode.py
  

• Lecture 12: Automatic Differentiation---XI
  Monday 18 September 2023
  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 20 September 2023
  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 22 September 2023
  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 25 September 2023
  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 27 September 2023
  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 29 September 2023
  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 2 October 2023
  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 4 October 2023
  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 6 October 2023
  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 11 October 2023
  Whiteboard
  

• Lecture 22: TBD
  Friday 13 October 2023
  Whiteboard
  

• 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 16 October 2023
  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 18 October 2023
  Whiteboard
  

• Lecture 25: Fast R-CNN
  R. Girshick, `Fast R-CNN,' Computer Vision and Pattern Recognition (CVPR), pp. 1440-1448, 2015.
  Friday 20 October 2023
  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 23 October 2023
  Whiteboard
  neural_network.py
  xor.py
  alexnet.py
  vgg19.py
  ilsvrc.py
  ilsvrc_batch.py
  

• 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 25 October 2023
  Whiteboard
  

• Lecture 28: TBD
  Friday 27 October 2023
  Whiteboard
  

• 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 30 October 2023
  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 1 November 2023
  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 3 November 2023
  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 6 November 2023
  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 8 November 2023
  Whiteboard
  

• Lecture 34: TBD
  Friday 10 November 2023
  Whiteboard
  

• Lecture 35: TBD
  Monday 13 November 2023
  Whiteboard
  

• Lecture 36: TBD
  Wednesday 15 November 2023
  Whiteboard
  

• Lecture 37: TBD
  Friday 17 November 2023
  Whiteboard
  

• Lecture 38: TBD
  Monday 20 November 2023
  Whiteboard
  

• Lecture 39: TBD
  Monday 27 November 2023
  Whiteboard
  

• Lecture 40: TBD
  Wednesday 29 November 2023
  Whiteboard
  

• Lecture 41: TBD
  Friday 1 December 2023
  Whiteboard
  

• Lecture 42: TBD
  Monday 4 December 2023
  Whiteboard
  

• Lecture 43: TBD
  Wednesday 6 December 2023
  Whiteboard
  

• Lecture 44: TBD
  Friday 8 December 2023
  Whiteboard
  

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