MatConvNet

MatConvNet

VLFeat
+

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About

Deep learning frameworks such as TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have contributed to the popularity of deep learning by reducing the effort and skills needed to design, train, and use deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) provides a consistent way to run these deep-learning frameworks as a service on Kubernetes. The FfDL platform uses a microservices architecture to reduce coupling between components, keep each component simple and as stateless as possible, isolate component failures, and allow each component to be developed, tested, deployed, scaled, and upgraded independently. Leveraging the power of Kubernetes, FfDL provides a scalable, resilient, and fault-tolerant deep-learning framework. The platform uses a distribution and orchestration layer that facilitates learning from a large amount of data in a reasonable amount of time across compute nodes.

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

Wing Python IDE was designed from the ground up for Python, to bring you a more productive development experience. Type less and let Wing worry about the details. Get immediate feedback by writing your Python code interactively in the live runtime. Easily navigate code and documentation. Avoid common errors and find problems early with assistance from Wing's deep Python code analysis. Keep code clean with smart refactoring and code quality inspection. Debug any Python code. Inspect debug data and try out bug fixes interactively without restarting your app. Work locally or on a remote host, VM, or container. Wingware's 21 years of Python IDE experience bring you a more Pythonic development environment. Wing was designed from the ground up for Python, written in Python, and is extensible with Python. So you can be more productive.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Neural networks experts looking for a solution to run deep-learning frameworks as a service on Kubernetes

Audience

Anyone in need of a deep learning software

Audience

Python developers seeking a tool to build applications

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 3.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 1.0 / 5
support 4.0 / 5

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

IBM
Founded: 1911
United States
developer.ibm.com/open/projects/fabric-for-deep-learning-ffdl/

Company Information

VLFeat
United States
www.vlfeat.org/matconvnet/

Company Information

Wingware
Founded: 1999
United States
wingware.com

Alternatives

Alternatives

Alternatives

LiveLink for MATLAB

LiveLink for MATLAB

Comsol Group
DataMelt

DataMelt

jWork.ORG
MATLAB

MATLAB

The MathWorks

Categories

Categories

Categories

Deep Learning Features

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

Application Development Features

Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development

Integrations

Amazon Web Services (AWS)
Apache Subversion
C
C++
Django
Emacs
Flask
Git
Google App Engine
Kubernetes
MATLAB
Mercurial
PyTorch
Raspberry Pi OS
TensorFlow
Torch
Vagrant
Visual Studio
Visual Studio Code
Xcode

Integrations

Amazon Web Services (AWS)
Apache Subversion
C
C++
Django
Emacs
Flask
Git
Google App Engine
Kubernetes
MATLAB
Mercurial
PyTorch
Raspberry Pi OS
TensorFlow
Torch
Vagrant
Visual Studio
Visual Studio Code
Xcode

Integrations

Amazon Web Services (AWS)
Apache Subversion
C
C++
Django
Emacs
Flask
Git
Google App Engine
Kubernetes
MATLAB
Mercurial
PyTorch
Raspberry Pi OS
TensorFlow
Torch
Vagrant
Visual Studio
Visual Studio Code
Xcode
Claim Fabric for Deep Learning (FfDL) and update features and information
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