Resnet-32 vs. Faster R-CNN

Both ResNet 32 and Faster R-CNN are commonly used in computer vision projects. Below, we compare and contrast ResNet 32 and Faster R-CNN.

Models

ResNet 32

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

Learn more about ResNet 32

Faster R-CNN

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server.

Learn more about Faster R-CNN

Model Type

Classification

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

Frameworks

Fast.ai v2

TensorFlow 1.5

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

32+

7.5k+

License

MIT

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare Resnet-32 vs. Faster R-CNN

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.

Resnet-32 vs. Faster R-CNN

Models

ResNet 32

Faster R-CNN

Compare ResNet 32 and Faster R-CNN with Autodistill

Compare Resnet-32 vs. Faster R-CNN