Overview

What is ResNet-32?

ResNet-32 is a convolutional neural network backbone that is based off alternative ResNet networks such as ResNet-34, ResNet-50, and ResNet-101. As its name implies, ResNet-32 is has 32 layers. It addresses the problem of vanishing gradient with the identity shortcut connection that skips one or more layers. The ResNet backbone can be ported into many applications including image classification as it is used here. This implementation of ResNet-32 is created with fastai, a low code deep learning framework.

ResNet-32 Architecture

ResNet-32's Architecture is largely inspired by the architecture of ResNet-34. Below, on the right-hand side, is Resnet34's architecture where the 34 layers and the residuals from one layer to another are visualized.

Performance

Use This Model

Label Data Automatically with ResNet 32

You can automatically label a dataset using ResNet 32 with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use ResNet 32 to train a computer vision model.

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