Overview

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ResNet-50 is a popular deep-learning image classification model. Version 1.5 of the Residual Neural Networks family of models, ResNet-50 is a 50-layer convolutional neural network (CNN). Released in 2015, it has remained a notable, powerful option for image classification models, well into a decade after its release.

ResNet-50 has high adaptability, making it the perfect model for transfer learning. In fact, recent models years after ResNet-50 such as Mask R-CNN used ResNet-50 as its backbone architecture.

Deploy Resnet-50 using Roboflow here.

Overall, ResNet-50’s unique combination of residual learning, deep yet manageable architecture, and wide adoption makes it a standout model in the field of deep learning and computer vision.

Performance

Use This Model

Label Data Automatically with ResNet-50

You can automatically label a dataset using ResNet-50 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-50 to train a computer vision model.

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