MatConvNetVLFeat
|
Predictive SuitePredictive Dynamix
|
|||||
Related Products
|
||||||
About
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.
|
About
Automated variable selection identifies key variables & variable interactions. Insightful visualization of data and model dynamics. Execution of batch commands. SQL queries and dataset browsing. Pre & post-processing for creating variables, constraining outputs, etc. Models easily deployed via ActiveX (i.e., OCX) controls or DLLs. Powerful modeling algorithms include regression, neural networks, self-organizing maps, dynamic clustering, decision trees, fuzzy logic, genetic algorithms. Predictive Dynamix provides computational intelligence software for forecasting, predictive modeling, pattern recognition, classification, and optimization applications, across all industries. Modern neural network technology are powerful computational structure for solving difficult problems involving forecasting and pattern recognition. Multi-layer perceptron neural networks have an architecture that allows multiple coefficients per input variable.
|
|||||
Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
|||||
Audience
Anyone in need of a deep learning software
|
Audience
Organization searching for a statistical and graphical data analysis solution providing state-of-the-art predictive modeling
|
|||||
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
|
|||||
API
Offers API
Not Supported
|
API
Offers API
Not Supported
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
|
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
|
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
|
|||||
Company InformationVLFeat
United States
www.vlfeat.org/matconvnet/
|
Company InformationPredictive Dynamix
Founded: 1999
predictivedynamix.com/dmsuite.htm
|
|||||
Alternatives |
Alternatives |
|||||
|
|
|
|||||
|
|
||||||
|
|
||||||
|
|
||||||
Categories |
Categories |
|||||
Deep Learning Features
Convolutional Neural Networks
Supported
Document Classification
Supported
Image Segmentation
Supported
ML Algorithm Library
Not Supported
Model Training
Not Supported
Neural Network Modeling
Not Supported
Self-Learning
Not Supported
Visualization
Not Supported
|
Statistical Analysis Features
Analytics
Not Supported
Association Discovery
Supported
Compliance Tracking
Supported
File Management
Not Supported
File Storage
Supported
Forecasting
Supported
Multivariate Analysis
Not Supported
Regression Analysis
Supported
Statistical Process Control
Not Supported
Statistical Simulation
Supported
Survival Analysis
Not Supported
Time Series
Not Supported
Visualization
Supported
|
|||||
Integrations
No info available.
|
Integrations
No info available.
|
|||||
|
|
|