ResNet : Convolution Neural Network

ResNet : Convolution Neural Network

ResNet, also known as residual neural network, refers to the idea of ​​adding residual learning to the traditional convolutional neural network,

ResNet, also known as residual neural network, refers to the idea of ​​adding residual learning to the traditional convolutional neural network, which solves the problem of gradient dispersion and accuracy degradation (training set) in deep networks, so that the network can get more and more The deeper, both the accuracy and the speed are controlled.

*The problem caused by increasing depth *:

  • The first problem brought by increasing depth is the problem of gradient explosion / dissipation . This is because as the number of layers increases, the gradient of backpropagation in the network will become unstable with continuous multiplication, and become particularly large or special. small. Among them , the problem of gradient dissipation often occurs. i.e effect of the weight decreases.

ai deep-learning convolution-neural-net resnet50 cnn

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