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vlfeat/matconvnet

version 1.1.0.0 (1.99 MB) by Andrea Vedaldi
MatConvNet: CNNs for MATLAB

7.4K Downloads

Updated 21 Jun 2018

From GitHub

View license on GitHub

Please refer to the homepage (http://www.vlfeat.org/matconvnet) for releases, data, and documentation.
MatConvNet is a MATLAB toolbox implementing Convolutional Neural Networks (CNNs) for computer vision applications. It is simple, efficient (integrating MATLAB GPU support), and can run and learn state-of-the-art CNNs, similar to the ones achieving top scores in the ImageNet challenge. Several example CNNs are included to classify and encode images.
An important feature of MatConvNet is making available the CNN building blocks as easy-to-use MATLAB commands. This allows prototyping new CNN architectures and learning algorithms as well as recycling fast convolution code for sliding window object detection and other applications.

MatConvNet is developed by a team of computer vision scientists in Oxford and other research institutions.

Cite As

Andrea Vedaldi (2021). vlfeat/matconvnet (https://github.com/vlfeat/matconvnet), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2014a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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examples

examples/+solver

examples/cifar

examples/custom_imdb

examples/fast_rcnn

examples/fast_rcnn/+dagnn

examples/fast_rcnn/bbox_functions

examples/fast_rcnn/datasets

examples/imagenet

examples/mnist

examples/spatial_transformer

examples/vggfaces

matlab

matlab/+dagnn

matlab/+dagnn/@DagNN

matlab/compatibility/parallel

matlab/simplenn

matlab/xtest

matlab/xtest/suite

utils

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.