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Description

The VLFeat open source library offers a range of well-known algorithms focused on computer vision, particularly for tasks such as image comprehension and the extraction and matching of local features. Among its various algorithms are Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, the agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, and large scale SVM training, among many others. Developed in C to ensure high performance and broad compatibility, it also has MATLAB interfaces that enhance user accessibility, complemented by thorough documentation. This library is compatible with operating systems including Windows, Mac OS X, and Linux, making it widely usable across different platforms. Additionally, MatConvNet serves as a MATLAB toolbox designed specifically for implementing Convolutional Neural Networks (CNNs) tailored for various computer vision applications. Known for its simplicity and efficiency, MatConvNet is capable of running and training cutting-edge CNNs, with numerous pre-trained models available for tasks such as image classification, segmentation, face detection, and text recognition. The combination of these tools provides a robust framework for researchers and developers in the field of computer vision.

Description

Mathematica represents the ultimate solution for contemporary technical computing. Over the past thirty years, it has set the benchmark for excellence in this field, serving as the primary computational framework for countless innovators, educators, students, and various professionals globally. Renowned for its impressive technical capabilities and user-friendly interface, Mathematica offers a unified, ever-evolving system that encompasses the full spectrum of technical computing. This powerful tool is conveniently accessible via any web browser in the cloud and is also available on all current desktop platforms. With a vibrant development process and a clear vision maintained for three decades, Mathematica distinguishes itself across numerous aspects, showcasing its unmatched support for the evolving needs of today’s technical computing environments and workflows, while continuing to adapt and grow with the demands of its users.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Cleo LMS No 
{CodeStore} No 

Integrations

Cleo LMS Yes 
{CodeStore} Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$1,520 per year
Free Trial Yes 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

VLFeat

Country

United States

Website

www.vlfeat.org/matconvnet/

Vendor Details

Company Name

Wolfram

Founded

1987

Country

United States

Website

www.wolfram.com/mathematica/

Product Features

Deep Learning

Convolutional Neural Networks Yes 
Document Classification Yes 
Image Segmentation Yes 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Product Features

Computer-Aided Engineering (CAE)

CAD/CAM Compatibility No 
Finite Element Analysis No 
Fluid Dynamics No 
Import / Export Files No 
Integrated 3D Modeling No 
Manufacturing Process Simulation No 
Mechanical Event Simulation No 
Multibody Dynamics No 
Thermal Analysis No 

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization Yes 

Embedded Analytics

Ad hoc Query No 
Application Development No 
Benchmarking No 
Dashboard No 
Interactive Reports No 
Mobile Reporting No 
Multi-User Collaboration No 
Self Service Analytics No 
Streaming Analytics No 
Visual Workflow Management No 

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