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Lecture 9: CNN Architectures

Fei-Fei Li & Justin Johnson & Serena YeungLecture 9 -May 2, 2017 Fei-Fei Li & Justin Johnson & Serena YeungLecture 9 -May 2, 20171 Lecture 9:CNN ArchitecturesFei-Fei Li & Justin Johnson & Serena YeungLecture 9 -May 2, 20172 AdministrativeA2 due Thu May 4 Midterm: In-class Tue May 9. Covers material through Thu May 4 session: Tue June 6, 12-3pmFei-Fei Li & Justin Johnson & Serena YeungLecture 9 -May 2, 2017 Last time: Deep learning frameworks3 Caffe (UC Berkeley)Torch (NYU / Facebook)Theano (U Montreal)TensorFlow (Google)Caffe2 (Facebook)PyTorch (Facebook)CNTK (Microsoft)Paddle (Baidu)MXNet (Amazon)Developed by U Washington, CMU, MIT, Hong Kong U, etc but main framework of choice at AWSAnd Li & Justin Johnson & Serena YeungLecture 9 -May 2, 20174(1)Easily build big computational graphs(2)Easily compute gradients in computational graphs(3)Run it all efficiently on GPU (wrap cuDNN, cuBLAS, etc)Last time.

ImageNet Large Scale Visual Recognition Challenge (ILSVRC) winners Deeper Networks. Fei-Fei Li & Justin Johnson & Serena Yeung Lecture 9 - May 2, 2017 Case Study: VGGNet 26 3x3 conv, 128 Pool 3x3 conv, 64 3x3 conv, 64 Input 3x3 conv, 128 Pool 3x3 conv, 256 3x3 conv, 256 Pool 3x3 conv, 512 3x3 conv, 512 Pool 3x3 conv, 512 3x3 conv, 512 Pool FC 4096

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