You can find a selection of articles, blog posts, models, and other resources about deep learning on this page.


Deep Architectures

A comprehensive overview of deep learning architectures can be found at: Towards Data Science. It covers all the important architectures, such as:

  • LeNet
  • AlexNet
  • VGG
  • GoogLeNet
  • Inception
  • ResNet
  • ENet
  • Xception
  • MobileNets

DeepLabv3+


Batch Size

Batch sizes over 32 are not useful to increase performance, "…the best performance has been consistently obtained for mini-batch sizes between m=2 and m=32 , which contrasts with recent work advocating the use of mini-batch sizes in the thousands."


Res-Net


Fully Convolutional Networks (FCN)


U-Net


Segmentation Networks


Optimization Methods


Batch Normalization


Nearest Neighbor Upsampling

Deconvolution/Transposed convolution can lead to checkerboard patterns especially in strong colors because of kernels overlapping and maybe because of gradient artifacts.


Domain Adaptation / Transfer Learning

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