MatConvNetVLFeat
|
||||||
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
fastText is an open source, free, and lightweight library developed by Facebook's AI Research (FAIR) lab for efficient learning of word representations and text classification. It supports both unsupervised learning of word vectors and supervised learning for text classification tasks. A key feature of fastText is its ability to capture subword information by representing words as bags of character n-grams, which enhances the handling of morphologically rich languages and out-of-vocabulary words. The library is optimized for performance and capable of training on large datasets quickly, and the resulting models can be reduced in size for deployment on mobile devices. Pre-trained word vectors are available for 157 languages, trained on Common Crawl and Wikipedia data, and can be downloaded for immediate use. fastText also offers aligned word vectors for 44 languages, facilitating cross-lingual natural language processing tasks.
|
|||||
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
Supported
Linux
Supported
Cloud
Not 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
Language processing practitioners and researchers requiring a tool for learning word embeddings and building text classifiers
|
|||||
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
|||||
API
Offers API
Not Supported
|
API
Offers API
Supported
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
|
Pricing
Free
Free Version
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
Not Supported
In Person
Not Supported
|
|||||
Company InformationVLFeat
United States
www.vlfeat.org/matconvnet/
|
Company InformationfastText
fasttext.cc/
|
|||||
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
|
||||||
Integrations
Gensim
Not Supported
JavaScript
Not Supported
Python
Not Supported
WebAssembly
Not Supported
|
Integrations
Gensim
Supported
JavaScript
Supported
Python
Supported
WebAssembly
Supported
|
|||||
|
|
|