Machine Learning (Fall 2020)

Administrative Matters

Instructor: Lin ZHANG (张林)

TA: Tianjun ZHANG 1911036@tongji.edu.cn

 

Office: RM408L, Jishi Building, Jiading Campus

 

Lecture Slides

 

Slides

Reading Materials

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Introduction

 

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AdaBoost and Cascade Structure

1. P. Viola and M.J. Jones, Robust real-time face detection, IJCV' 04

2. Y. Freund and R.E. Schapire, A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting, Journal of Computer and System Sciences,1995
 

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Principal Component Analysis

1. M. Turk and A. Pentland, Eigenfaces for recognition, Journal of Cognitive Neuroscience' 91

2. PCADemo: a matlab program used in our lectures to demonstrate the basic concepts related to PCA
3. FaceRecByEigenFace: a matlab demo composed by me to illustrate how to make use of the eigen-face approach to perform face recognition. Very simple and straightforward. (You need to run "training.m" at first)

Sparse Representation based Classification

1. J. Wright et al., Robust face recognition via sparse representation, IEEE PAMI' 09
2. L. Zhang et al., Sparse representation or collaborative representation: which helps face recognition?, ICCV' 11
3. Implementations of several l1-minization solvers, provided by Allen Yang (EECS, Berkeley)
4. CRC_RLS: a matlab demo program implementing the CRC_RLS based face recognition method.

Linear Models

 

Neural Networks and CNN

1. K. He et al., Deep Residual Learning for Image Recognition, CVPR 2016

2. G. Huang et al., Densely Connected Convolutional Networks, CVPR 2017

3. J. Redmon et al., Yolo: 9000 better, faster, stronger, CVPR 2017

4. N. Ma et al., ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design, ECCV 2018

5. Learn to configure YoloV2 and try to solve your own detection task, https://github.com/AlexeyAB/darknet.

6. 典型卷积神经网络模型结构的演进

Least Squares

 

Visual Perception Practices in Autonomous Driving

1.  Lin Zhang et al., Vision-based parking-slot detection: A benchmark and a learning-based approach, Symmetry 10 (3) 64:1-18, 2018.

2.  Lin Zhang et al., "Vision-based parking-slot detection: A DCNN-based approach and a large-scale benchmark dataset"IEEE Trans. Image Processing, vol. 27, no. 11, pp. 5350-5364, 2018.

3.  Xuan Shao, Xiao Liu, Lin Zhang*, et al., Revisit surround-view camera system calibration, in Proc. ICME, 2019

Gaussian Mixture Model and Expectation Maximization

 

GANs and Their Applications in Image Generation

1.   I.J. Goodfellow et al., Generative adversarial nets, NIPS, 2014

2.   A. Radford et al., Unsupervised representation learning with deep convolutional generative adversarial networks, ICLR, 2016

3.   M. Arjovsky et al., Towards principled methods for training generative adversarial networks, ICLR, 2017

4.   M. Arjovsky et al., Wasserstein GAN, arXiv, 2017

5.   I. Gulrajani et al., Improved training of Wasserstein GANs, arXiv, 2017

6.   P. Isola, J. Zhu, T. Zhou, and A.A. Efros, Image-to-image translation with conditional adversarial networks, CVPR, 2017

7.   J. Zhu et al., Unpaired image-to-image translation using cycle-consistent adversarial networks, arXiv, 2017

8.   C. Ledig et al., Photo-realistic single image super-resolution using a generative adversarial network, CVPR, 2017

9.   A. Shrivastava et al., Learning from simulated and unsupervised images through adversarial training, CVPR, 2017

 

Assignments

Notes:

1. Compress all files into a .rar file whose name is composed of student name and ID.

2. For the programming assignments, please use Matlab or C++ and make sure your program can successfully run on TA's machine.

3. All the documents you hand in, including comments in the source codes, should be in English.

4. Please send your solutions to TA  and confirm with TA that she has received your email successfully.

 

1. Assignment 1 (Due: Oct. 25, 2020) marks

2. Assignment 2 (Due: Dec. 06, 2020) marks

2. Assignment 3 (Due: Dec. 27, 2020) test_video

 

Created on: Sep. 12, 2020

Last updated on: Dec. 23, 2020