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Introduction to Convolutional Neural Networks

Bleu (Jia-Huei Ren)
January 10, 2017
76

Introduction to Convolutional Neural Networks

A Beginner's Guide To Understanding Convolutional Neural Networks.

Refs:
http://colah.github.io/posts/2014-07-Understanding-Convolutions/
Large-Scale Visual Recognition With Deep Learning (Marc'Aurelio Ranzato , Google Inc)
A Beginner's Guide To Understanding Convolutional Neural Networks(Adit Deshpande, CS Undergrad at UCLA '19)
Video Object Detection using Faster R-CNN(Jun 20, 2016paper from Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun)
Tensorflow Days (c1mone)
CS231n Convolutional Neural Networks for Visual Recognition

Bleu (Jia-Huei Ren)

January 10, 2017
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Transcript

  1. Convolutional Neural Network Jia-Huei, Ren 2017/1/10

  2. CNN

  3. Convolution • Convolution – local receptive field • ReLU •

    Average Pooling • Max Pooling
  4. Convolution

  5. Local receptive field

  6. Local receptive field

  7. Local receptive field

  8. Local receptive field

  9. Fully Conneted Neural Net • Example: 1000x1000 image • 1M

    hidden units • 10^12 parameters!!!
  10. Locally Connected Neural Net • Example: 1000x1000 image • 1M

    hidden units • Filter size: 10x10 • 100M parameters
  11. Locally Connected Neural Net • Example: 1000x1000 image • 1M

    hidden units • Filter size: 10x10 • 100M parameters
  12. Convolutional Net • Share parameters • Learn multiple filters. •

    Example: 1000x1000 image • 100 Filters • Filter size: 10x10 • 10K parameters
  13. ReLU

  14. Max pooling & Average pooling

  15. Full connected layer

  16. Refs • http://colah.github.io/posts/2014-07-Understanding- Convolutions/ • Large-Scale Visual Recognition With Deep

    Learning (Marc'Aurelio Ranzato , Google Inc) • A Beginner's Guide To Understanding Convolutional Neural Networks(Adit Deshpande, CS Undergrad at UCLA '19) • Video Object Detection using Faster R-CNN(Jun 20, 2016 paper from Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun) • Tensorflow Days (c1mone) • CS231n Convolutional Neural Networks for Visual Recognition
  17. Thanks