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
Paessler: Easy to Use With Enterprise Power. Free Trial Icon
Paessler: Easy to Use With Enterprise Power. Free Trial

A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

You shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
Get Free Download
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