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Accord.NET Framework

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  Analyzed 1 day ago

The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications. A comprehensive set ... [More] of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details. [Less]

2.2M lines of code

15 current contributors

over 3 years since last commit

20 users on Open Hub

Inactive
5.0
 
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PyBrain

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  Analyzed 3 days ago

PyBrain is a modular Machine Learning Library for Python. It's goal is to offer flexible, easy-to-use yet still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test and compare your algorithms. PyBrain is short for Python-Based Reinforcement Learning ... [More] , Artificial Intelligence and Neural Network Library. It's the Swiss army knife for machine learning and neural networking. [Less]

37.1K lines of code

0 current contributors

over 6 years since last commit

6 users on Open Hub

Inactive
5.0
 
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deeplearning4j

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  Analyzed 3 days ago

Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library; designed to be used in business environments. Deeplearning4j aims to be cutting-edge plug and play, more convention than configuration, which allows for fast prototyping for non-researchers. Vast ... [More] support of scale out: Hadoop, Spark and Akka + AWS et al It includes both a distributed, multi-threaded deep-learning framework and a normal single-threaded deep-learning framework. Iterative reduce net training. First framework adapted for a micro-service architecture. A versatile n-dimensional array class. GPU integration [Less]

1.1M lines of code

17 current contributors

3 months since last commit

5 users on Open Hub

Low Activity
4.0
   
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eANN

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  Analyzed 2 days ago

eANN is an implementation of several kind of neural networks written with the intention of providing a (hopefully) easy to use, and easy to modify, OOP source code. It is possible to have several different sized networks running simultaneously, each functioning independently of the others or ... [More] acting as inputs between them. It also easy to modify the structure so that neurons (or even whole layers) can be created/pruned during simulation allowing dynamic expansion/contraction of the network. Networks Implemented: * Multi Layer Neural Network with Backpropagation * Competitive Neural Network * Radial Basis Neural Network * Progressive Radial Neural Network * Progressive Learning Neural Network [Less]

17.5K lines of code

1 current contributors

about 5 years since last commit

1 users on Open Hub

Inactive
0.0
 
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coconet

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  Analyzed about 14 hours ago

Coconet is a program that generate and evolve feedfoward neural networks for classification problems.

5.34K lines of code

0 current contributors

over 3 years since last commit

1 users on Open Hub

Inactive
0.0
 
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Lumeer

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  Analyzed about 12 hours ago

Lumeer changes the way we work with our business data by leveraging state of the art technologies.

309K lines of code

4 current contributors

21 days since last commit

1 users on Open Hub

Moderate Activity
5.0
 
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Savant

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  No analysis available

Python Computer Vision & Video Analytics Framework With Batteries Included

0 lines of code

0 current contributors

0 since last commit

0 users on Open Hub

Activity Not Available
0.0
 
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Mostly written in language not available
Licenses: apache_v2

MocapNET

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  Analyzed 3 days ago

We present MocapNET, an ensemble of SNN encoders that estimates the 3D human body pose based on 2D joint estimations extracted from monocular RGB images. MocapNET provides BVH file output which can be rendered in real-time or imported without any additional processing in most popular 3D animation ... [More] software. The proposed architecture achieves 3D human pose estimations at state of the art rates of 400Hz using only CPU processing. [Less]

33.2K lines of code

0 current contributors

about 1 month since last commit

0 users on Open Hub

Very Low Activity
0.0
 
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Licenses: No declared licenses

NeuroCrypto

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  Analyzed 1 day ago

This is a C++ implementation of the concept of Neural Cryptography, which is a communication of two tree parity machines for agreement on a common key over a public channel. This exchanged public key is utilized to encrypt a sensitive message to be transmitted over an insecure channel using Rijndael ... [More] cipher. This is a new potential source for public key cryptography schemes which are not based on number theoretic functions, and have small time and memory complexities. This is a proof-of-concept demo of how such a neural key exchange protocol in conjugation with AES encryption can be implemented in C++, which could be further extended in higher-level applications. Both CLI and GUI implementations of the software were created using Visual C++ (.NET framework). [Less]

1.27K lines of code

0 current contributors

almost 13 years since last commit

0 users on Open Hub

Inactive
0.0
 
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