Computer Vision Course Tsinghua University Wang Mingzhe

This course is a youth AI self-improvement project - computer vision course. The main organizers, speakers, and participants are all students, solving practical problems for students: bridging the gap between "technical novices" and "teachers think you understand" The gap between "textbook" and "practice" is bridged, and the problem that general academic articles/resources are difficult to read is solved. This course mainly consists of 8 lectures and 1 transformation challenge task. The lectures are held every other week. Each lecture will use easy-to-understand language to guide everyone to master AI-related knowledge points, including AI bird's-eye view and advanced guide, introduction to machine learning, classic neural networks, deep neural networks, convolutional neural networks, classification tasks, and detection tasks. , examples and parameter adjustment methods, and finally lead everyone to practice through transformation challenge tasks, etc.

• Chapter 1：Course Introduction & Teaching Philosophy (17 minutes and 7 seconds)

• Chapter 2：AI Bird's Eye View-Perception (10 minutes and 6 seconds)

• Chapter 3：AI bird's eye view-cognition (11 minutes and 21 seconds)

• Chapter 4：AI Bird's Eye View-Feedback Output & Summary (12 minutes and 59 seconds)

• Chapter 5：Advanced guide for experts (16 minutes and 28 seconds)

• Chapter 6：Homework instructions (11 minutes and 19 seconds)

• Chapter 7：Preface and introduction (11 minutes and 7 seconds)

• Chapter 8：Data representation & visual normalization & decision boundary representation (11 minutes and 51 seconds)

• Chapter 9：sigmoid function & loss function (9 minutes and 25 seconds)

• Chapter 10：gradient descent method (17 minutes and 27 seconds)

• Chapter 11：Overfitting&Regularization&Summary (7 minutes and 48 seconds)

• Chapter 12：Preface & Background Introduction & Linear Model Fitting MNIST (9 minutes and 43 seconds)

• Chapter 13：Feedforward propagation (Part 1) (14 minutes and 49 seconds)

• Chapter 14：Feedforward Propagation (Part 2) & Master Hinton (13 minutes and 15 seconds)

• Chapter 15：Back propagation & knowledge extension & NN vs MNIST (13 minutes and 58 seconds)

• Chapter 16：Ending & Second Lecture Homework Instructions (12 minutes and 29 seconds)

• Chapter 17：Preface & DNN Overview (13 minutes and 48 seconds)

• Chapter 18：Introduction to data sets and knowledge review (6 minutes and 24 seconds)

• Chapter 19：gradient disappears (12 minutes and 56 seconds)

• Chapter 20：Gradient explosion and activation function (6 minutes and 1 seconds)

• Chapter 21：Overfitting and its solutions (5 minutes and 58 seconds)

• Chapter 22：Tips & Epilogue for handling big data (10 minutes and 58 seconds)

• Chapter 23：Introduction & CNN Overview (11 minutes and 16 seconds)

• Chapter 24：Limitations of standard DNN & brief explanation of convolution operation (14 minutes and 50 seconds)

• Chapter 25：Brief explanation of pooling operation & introduction to data sets (5 minutes and 5 seconds)

• Chapter 26：Detailed explanation of convolution & pooling (9 minutes and 55 seconds)

• Chapter 27：Overall analysis and conclusion of network structure (15 minutes and 42 seconds)

• Chapter 28：Q&A after class (7 minutes and 25 seconds)

• Chapter 29：Instructions for the third and fourth assignments (7 minutes and 57 seconds)

• Chapter 30：Initial classification task (7 minutes and 36 seconds)

• Chapter 31：Convolution knowledge review (7 minutes and 33 seconds)

• Chapter 32：AlexNet & ZFNet (6 minutes and 7 seconds)

• Chapter 33：VGG & GoogleNet (Part 1) (8 minutes and 27 seconds)

• Chapter 34：GoogleNet (Part 2) & model degradation problem (7 minutes and 2 seconds)

• Chapter 35：ResNet & SENet (7 minutes and 48 seconds)

• Chapter 36：Summary & Model Compression (9 minutes and 34 seconds)

• Chapter 37：MobileNet & Epilogue (7 minutes and 22 seconds)

• Chapter 38：Chapter 5 Homework Instructions (3 minutes and 54 seconds)

• Chapter 39：Basic knowledge of detection tasks (9 minutes and 34 seconds)

• Chapter 40：Pioneer work: R-CNN (9 minutes and 10 seconds)

• Chapter 41：Fast & Faster R-CNN (9 minutes and 34 seconds)

• Chapter 42：YOLO basics (7 minutes and 32 seconds)

• Chapter 43：YOLO Advanced & Ending (8 minutes and 19 seconds)