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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 Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache Spark Yes 
Hadoop Yes 
SureView No 

Integrations

Apache Spark No 
Hadoop No 
SureView Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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

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 No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

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