Convolutional Neural Networks

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2019-01-25 22:07:13
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视频源网站:https://www.coursera.org/learn/convolutional-neural-networks 说明:该视频没有语言双显,单独英文看不懂;单独中文,有时候会词不达意
视频选集
(22/43)
Part1: Computer Vision
05:45
Part1: Edge Detection Example
11:35
Part1: More Edge Detection
08:02
Part1: Padding
09:51
Part1: Strided Convolutions
09:04
Part1: Convolutions Over Volume
10:47
Part1: One Layer of a Convolutional Network
16:14
Part1: Simple Convolutional Network Example
08:36
Part1: Pooling Layers
10:32
Part1: CNN Example
11:42
Part1: Why Convolutions
09:44
Part1: Yann LeCun Interview
27:52
Part2: Why look at case studies
03:20
Part2: Classic Networks
18:22
Part2: ResNets
07:12
Part2: Why ResNets Work
09:16
Part2: Networks in Networks and 1x1 Convolutions
06:44
Part2: Inception Network Motivation
10:18
Part2: Inception Network
08:50
Part2: Using Open-Source Implementation
05:02
Part2: Transfer Learning
08:52
Part2: Data Augmentation
09:36
Part2: State of Computer Vision
12:41
Part3: Object Localization
11:57
Part3: Landmark Detection
06:00
Part3: Object Detection
05:51
Part3: Convolutional Implementation of Sliding Windows
11:11
Part3: Bounding Box Predictions
14:35
Part3: Intersection Over Union
04:22
Part3: Non-max Suppression
08:07
Part3: YOLO Algorithm
07:05
Part3: (Optional) Region Proposals
06:31
Part4: What is face recognition
04:41
Part4: One Shot Learning
04:44
Part4: Siamese Network
04:55
Part4: Triplet Loss
15:33
Part4: Face Verification and Binary Classification
06:08
Part4: What is neural style transfer
02:16
Part4: What are deep ConvNets learning
08:08
Part4: Cost Function
04:05
Part4: Content Cost Function
03:42
Part4: Style Cost Function
17:04
Part4: 1D and 3D Generalizations
09:11
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