Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
A hybrid front-end efficiently switches between Gluon eager imperative mode and symbolic mode, offering both adaptability and speed. The framework supports scalable distributed training and enhances performance optimization for both research and real-world applications through its dual parameter server and Horovod integration. It features deep compatibility with Python and extends support to languages such as Scala, Julia, Clojure, Java, C++, R, and Perl. A rich ecosystem of tools and libraries bolsters MXNet, facilitating a variety of use-cases, including computer vision, natural language processing, time series analysis, and much more. Apache MXNet is currently in the incubation phase at The Apache Software Foundation (ASF), backed by the Apache Incubator. This incubation stage is mandatory for all newly accepted projects until they receive further evaluation to ensure that their infrastructure, communication practices, and decision-making processes align with those of other successful ASF initiatives. By engaging with the MXNet scientific community, individuals can actively contribute, gain knowledge, and find solutions to their inquiries. This collaborative environment fosters innovation and growth, making it an exciting time to be involved with MXNet.
Description
VisionPro Deep Learning stands out as a premier software solution for image analysis driven by deep learning, specifically tailored for factory automation needs. Its robust algorithms, proven in real-world scenarios, are finely tuned for machine vision, featuring an intuitive graphical user interface that facilitates neural network training without sacrificing efficiency. This software addresses intricate challenges that traditional machine vision systems struggle to manage, delivering a level of consistency and speed that manual inspection cannot match. Additionally, when paired with VisionPro’s extensive rule-based vision libraries, automation engineers can readily select the most suitable tools for their specific tasks. VisionPro Deep Learning merges a wide-ranging machine vision toolset with sophisticated deep learning capabilities, all within a unified development and deployment environment. This integration significantly streamlines the process of creating vision applications that must adapt to variable conditions. Ultimately, VisionPro Deep Learning empowers users to enhance their automation processes while maintaining high-quality standards.
API Access
Has API
API Access
Has API
Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Cameralyze
Flower
GPUonCLOUD
Google Cloud Deep Learning VM Image
Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Cameralyze
Flower
GPUonCLOUD
Google Cloud Deep Learning VM Image
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
The Apache Software Foundation
Founded
1999
Country
United States
Website
mxnet.apache.org
Vendor Details
Company Name
Cognex
Founded
1981
Country
United States
Website
www.cognex.com/products/deep-learning/visionpro-deep-learning
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization