Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
DATAGYM empowers data scientists and machine learning professionals to annotate images at speeds that are ten times quicker than traditional methods. The use of AI-driven annotation tools minimizes the manual effort required, allowing for more time to refine machine learning models and enhancing the speed at which new products are launched. By streamlining data preparation, you can significantly boost the efficiency of your computer vision initiatives, reducing the time required by as much as half. This not only accelerates project timelines but also facilitates a more agile approach to innovation in the field.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon S3
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$19.00/month/user
Tiered Pricing Model with the Developer plan costing $0 a month.
Free Trial
No
Free Version
Yes
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
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
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
eForce21
Founded
2019
Country
Germany
Website
www.datagym.ai/
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
Data Analysis
Data Discovery
Yes
Data Visualization
Yes
High Volume Processing
Yes
Predictive Analytics
No
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No
Data Management
Customer Data
No
Data Analysis
Yes
Data Capture
Yes
Data Integration
Yes
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Data Visualization
Analytics
Yes
Content Management
Yes
Dashboard Creation
No
Filtered Views
No
OLAP
No
Relational Display
Yes
Simulation Models
No
Visual Discovery
Yes
Deep Learning
Convolutional Neural Networks
Yes
Document Classification
No
Image Segmentation
Yes
ML Algorithm Library
No
Model Training
Yes
Neural Network Modeling
Yes
Self-Learning
No
Visualization
Yes
Machine Learning
Deep Learning
Yes
ML Algorithm Library
No
Model Training
Yes
Natural Language Processing (NLP)
No
Predictive Modeling
Yes
Statistical / Mathematical Tools
No
Templates
No
Visualization
Yes