Pattern Recognition (Fall 2017)

Administrative Matters

Instructor: Dr. Ying Shen (沈莹) (yingshen@tongji.edu.cn)

Evaluation: assignments(30%), project (65%), participation (5%)

Latest Notices

Submission deadline of the final project: Jan. 14, 2018. (Send your zip file to pattern_recognition@outlook.com)

Each team has 5 minutes for presentation.

Lecture Slides

	Slides	Related Materials
	Introduction Data Tutorial 01 Tutorial 02	1. UCI Machine Learning Repository 2. A tutorial on Principal Components Analysis 3. Feature selection techniques in bioinformatics
	Model evaluation and selection
	Linear model Tutorial 03 Lab 1 Assignment 1 due date: Nov. 1	fisherLDAExperiment.m
	Decision Tree Tutorial 04	Decision tree implemented in matlab code Source codes directory
	Neural network
	SVM Lab 2
	Ensumble Learning
	Clustering Analysis Tutorial 05 Assignment 3 due date: Jan. 2
	Dimension Reduction
	Basics for Machine Learning and A Special Emphasis on CNN Assignment 2 due date: Nov. 29，2017 (For problem 1, send your solution to the 'Assignment Email'; for problem 2, I will check your results personally in our lecture time.)	Demo for linear regression Demo for softmax regression An easy tutorial for understanding backpropagation Caffe: The most widely used deep learning framework Windows Caffe, Installation Guide Digit classification demo. Classify an image with a digit using your trained LeNet. (For instructions, refer to Installation Guide) Cifar10 test demo. Classify an image using your trained Cifar10 network. (For instructions, refer to Installation Guide) Self Data Training. This ZIP file contains all the necessary files to conduct self-data training mentioned in Installation Guide. K. He et al., Deep Residual Learning for Image Recognition, CVPR 2016 G. Huang et al., Densely Connected Convolutional Networks, CVPR 2017 J. Redmon et al., Yolo: 9000 better faster stronger, CVPR 2017 Learn to configure YoloV2 and try to solve your own detection task, https://github.com/AlexeyAB/darknet
	Applications of CNNs	Linshen Li and Lin Zhang* et al.,., Vision-based parking-slot detection: A benchmark and a learning-based approach, ICME, 2017 Z. Cao et al., Realtime multi-person 2D pose estimation using part affinity fields, CVPR 2017 CMU OpenPose Libary, https://github.com/CMU-Perceptual-Computing-Lab/openpose
	GANs and Their Applications in Image Generation	I.J. Goodfellow et al., Generative adversarial nets, NIPS, 2014 A. Radford et al., Unsupervised representation learning with deep convolutional generative adversarial networks, ICLR, 2016 M. Arjovsky et al., Towards principled methods for training generative adversarial networks, ICLR, 2017 M. Arjovsky et al., Wasserstein GAN, arXiv, 2017 I. Gulrajani et al., Improved training of Wasserstein GANs, arXiv, 2017 P. Isola, J. Zhu, T. Zhou, and A.A. Efros, Image-to-image translation with conditional adversarial networks, CVPR, 2017 J. Zhu et al., Unpaired image-to-image translation using cycle-consistent adversarial networks, arXiv, 2017 C. Ledig et al., Photo-realistic single image super-resolution using a generative adversarial network, CVPR, 2017 A. Shrivastava et al., Learning from simulated and unsupervised images through adversarial training, CVPR, 2017
	*Matlab Tutorial Examples for Matlab Tutorial	A matlab tutorial document