Audience

Anyone in need of a deep learning software

About MatConvNet

The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching. Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. MatConvNet is a MATLAB toolbox implementing Convolutional Neural Networks (CNNs) for computer vision applications. It is simple, efficient, and can run and learn state-of-the-art CNNs. Many pre-trained CNNs for image classification, segmentation, face recognition, and text detection are available.

Integrations

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Company Information

VLFeat
United States
www.vlfeat.org/matconvnet/

Videos and Screen Captures

MatConvNet Screenshot 1
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Product Details

Platforms Supported
Windows
Mac
Linux
Training
Documentation
Support
Online

MatConvNet Frequently Asked Questions

Q: What kinds of users and organization types does MatConvNet work with?
Q: What languages does MatConvNet support in their product?
Q: What kind of support options does MatConvNet offer?
Q: What type of training does MatConvNet provide?

MatConvNet Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization