Models

What is ResNet 34?

A fast, simple convolutional neural network that gets the job done for many tasks, including classification.

About the model

Here is an overview of the

ResNet 34

model:

Date of Release Dec 10, 2015
Model Type Classification
Architecture
Framework Used Fast.ai v2
Annotation Format
Stars on GitHub +

What is Resnet34?

Resnet34 is a state-of-the-art image classification model, structured as a 34 layer convolutional neural network and defined in "Deep Residual Learning for Image Recognition". Restnet34 is pre-trained on the ImageNet dataset which contains 100,000+ images across 200 different classes.

However, RestNet is different from traditional neural networks in the sense that it takes residuals from each layer and uses them in the subsequent connected layers (similar to residual neural networks used for text prediction).

Restnet34 Architecture

Below. on the right-hand side, is Resnet34's architecture where the 34 layers and the residuals from one layer to another are visualized.

Restnet34 Architecture

Learn More

Learn how to use Resnet34 Custom Resnet34 Model for Image Classification using fastai and PyTorch: https://blog.roboflow.com/custom-resnet34-classification-model/

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Model Performance

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ResNet 34 Annotation Format

ResNet 34

uses the

annotation format. If your annotation is in a different format, you can use Roboflow's annotation conversion tools to get your data into the right format.

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