This repository contains the original MATLAB implementation of R-CNN (Regions with Convolutional Neural Networks), a pioneering deep learning-based object detection framework. Developed by Ross Girshick, R-CNN combines region proposals with convolutional neural networks to detect objects in images. It was one of the first approaches to significantly improve performance on object detection benchmarks like PASCAL VOC.

Features

  • Implements R-CNN object detection using MATLAB
  • Uses region proposals and CNN feature extraction
  • Trains SVM classifiers on extracted features
  • Compatible with pretrained Caffe CNNs
  • Evaluates performance on PASCAL VOC datasets
  • Demonstrates pipeline from region proposal to final detection

Project Samples

Project Activity

See All Activity >

License

BSD License

Follow Rcnn

Rcnn Web Site

Other Useful Business Software
$300 Free Credits to Build on Google Cloud Icon
$300 Free Credits to Build on Google Cloud

New to Google Cloud? Get $300 in credits to explore Compute Engine, BigQuery, Cloud Run, Gemini Enterprise Agent Platform, and more.

Start your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
Claim $300 Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of Rcnn!

Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

MATLAB

Related Categories

MATLAB Computer Vision Libraries

Registered

2025-07-24