Resnets have surged in popularity in recent years, due to its fantastic ability to handle many convolutional layers. ”Resnet“ is the short form for residual network. A residual neural network is a model that tweaks its weights to learn residual functions given an input.
The main idea is that if we make the model focus on learning the difference between the input image and a target image, we can lower resource use to improve efficiency.
Credit: rupert ai
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