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Understanding Deep Learning

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Chapter 10 - CNNs

Chapter 10 - CNNs

Sep 30, 20241 min read

  • deeplearning

Chapter 10 - CNNs

 

Invariance

  • A function f[x] of an image is invariant to a transform t[x] if f(t(x))=f(x)
  • covariant if f(t(x))=t(f(x))

Convolution

  • Conv
  • Padded Conv
  • Strided
  • Kernel Filters
  • Atrous Convolution
  • Channels
  • Receptive field
  • Downsampling
  • Pooling
  • Transposed Conv
  • 1x1 conv

Image Classification

  • Alex Net
  • Relu
  • Vgg
  • Res Net

Object Detection

  • YOLO
  • Non Maxima Supression

Semantic Segmentation

  • Vgg
  • DeconvNet

Extras

  • ImageNet
  • Le Net
  • Inception
  • Depthwise Separable
  • PixelShuffle
  • Xavier Initialization
  • Cutout
  • Unet
  • Mixup
  • Batch Normalization

Graph View

  • Chapter 10 - CNNs
  • Invariance
  • Convolution
  • Image Classification
  • Object Detection
  • Semantic Segmentation
  • Extras

Backlinks

  • _Index_of_Understanding-Deep-Learning
  • Understanding Deep Learning

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