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Description
DL4J leverages state-of-the-art distributed computing frameworks like Apache Spark and Hadoop to enhance the speed of training processes. When utilized with multiple GPUs, its performance matches that of Caffe. Fully open-source under the Apache 2.0 license, the libraries are actively maintained by both the developer community and the Konduit team. Deeplearning4j, which is developed in Java, is compatible with any language that runs on the JVM, including Scala, Clojure, and Kotlin. The core computations are executed using C, C++, and CUDA, while Keras is designated as the Python API. Eclipse Deeplearning4j stands out as the pioneering commercial-grade, open-source, distributed deep-learning library tailored for Java and Scala applications. By integrating with Hadoop and Apache Spark, DL4J effectively introduces artificial intelligence capabilities to business settings, enabling operations on distributed CPUs and GPUs. Training a deep-learning network involves tuning numerous parameters, and we have made efforts to clarify these settings, allowing Deeplearning4j to function as a versatile DIY resource for developers using Java, Scala, Clojure, and Kotlin. With its robust framework, DL4J not only simplifies the deep learning process but also fosters innovation in machine learning across various industries.
Description
Irisity IRIS+ offers advanced video analytics solutions that leverage a range of patented technologies along with specialized expertise in software architecture, computer vision, deep learning, and artificial intelligence. Central to Irisity IRIS+'s technology is its innovative distributed architecture, which efficiently allocates video processing tasks between an edge device and a central server, thus optimizing the use of processing resources while minimizing bandwidth requirements and hardware expenses. The deep learning framework utilized by Irisity IRIS+ ensures that the cost per camera for hardware is the most competitive when compared to alternative software solutions available in the market. Furthermore, this versatile architecture supports deployment in both public cloud environments and private networks, making it adaptable to various use cases. Beyond its classification capabilities, Irisity IRIS+ has also created an extensive suite of video analytics features, including real-time event detection based on rules, autonomous anomaly identification, video forensic analysis, and comprehensive statistical evaluations, all integrated within a single software platform. This holistic approach enhances the overall effectiveness of video surveillance systems, catering to diverse operational needs across different sectors.
API Access
Has API
API Access
Has API
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
Deeplearning4j
Founded
2019
Country
Japan
Website
deeplearning4j.org
Vendor Details
Company Name
Irisity
Country
Sweden
Website
irisity.com
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization