Advanced Artificial Intelligence Lecture 6: Convolutional Neural network
Advanced Artificial Intelligence Lecture 6: Convolutional Neural Network
Outline Convolutional neural Network Convolution Max Pooling CNN Forward Propagation CNN Backward Propagation CNN Architectures ■ LeNet-5、 AlexNet VGGNet GooqLeNet ■ ResNet
2 Outline ▪ Convolutional Neural Network ▪ Convolution ▪ Max Pooling ▪ CNN Forward Propagation ▪ CNN Backward Propagation ▪ CNN Architectures ▪ LeNet-5 、 AlexNet ▪ VGGNet ▪ GoogLeNet ▪ ResNet
[Zeiler, M. D, ECCV 2014 Why cnn for Image? Represente d as pixels The most basic Use 1st layer as module to Use 2nd layer as classifiers build classifiers module Can the network be simplified by considering the properties of images? Sourceoftheslidehttp://219.216.82.193/cache/8/03/speech.ee.ntu.edu.tw/43149163c97eb6be7590e3d8de445a67/cnn.pdf
3 Why CNN for Image? [Zeiler, M. D., ECCV 2014] Can the network be simplified by considering the properties of images? 1 x 2 x … … Nx … … … … … … … … … … … … The most basic classifiers Use 1st layer as module to build classifiers Use 2nd layer as module …… Represente d as pixels Source of the slide: http://219.216.82.193/cache/8/03/speech.ee.ntu.edu.tw/43149163c97eb6be7590e3d8de445a67/CNN.pdf
Why cnn for Image? Some patterns are much smaller than the whole Image Aneuron does not have to see the whole image to discover the pattern Connecting to small region with less parameters “ beak, detector Sourceoftheslidehttp://219.216.82.193/cache/8/03/speech.ee.ntu.edu.tw/43149163c97eb6be7590e3d8de445a67/cnn.pdf
4 Why CNN for Image? ▪ Some patterns are much smaller than the whole image A neuron does not have to see the whole image to discover the pattern. “beak” detector Connecting to small region with less parameters Source of the slide: http://219.216.82.193/cache/8/03/speech.ee.ntu.edu.tw/43149163c97eb6be7590e3d8de445a67/CNN.pdf
Why cnn for Image? The same patterns appear in different regions upper-left beak” detector Do almost the same thing They can use the same set of parameters middle beak” detector 5 Sourceoftheslidehttp://219.216.82.193/cache/8/03/speech.ee.ntu.edu.tw/43149163c97eb6be7590e3d8de445a67/cnn.pdf
5 Why CNN for Image? ▪ The same patterns appear in different regions. “upper-left beak” detector “middle beak” detector They can use the same set of parameters. Do almost the same thing Source of the slide: http://219.216.82.193/cache/8/03/speech.ee.ntu.edu.tw/43149163c97eb6be7590e3d8de445a67/CNN.pdf