Search Results for "neural network visualiser"

Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)...

...PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models. ...

Real-ESRGAN ncnn Vulkan is an optimized, cross-platform implementation of Real-ESRGAN using the ncnn neural network inference engine and Vulkan for hardware acceleration. Unlike the standard PyTorch-based Real-ESRGAN code, this variant is written in C/C++ and designed to run efficiently on many platforms (including Windows, Linux, and possibly Android) without requiring heavy frameworks like CUDA or Python. It provides command-line tools for upscaling images with selected models, allowing users to specify input/output paths, scaling factors, tile sizes, and model names from a compressed model set, which is particularly helpful for larger images or automated workflows. ...

Consistent Depth is a research project developed by Facebook Research that presents an algorithm for reconstructing dense and geometrically consistent depth information for all pixels in a monocular video. The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. During inference, the model fine-tunes itself to align with the geometric constraints of a specific input video, ensuring stable and realistic depth maps even in less-constrained regions. This approach achieves improved geometric consistency and visual stability compared to prior monocular reconstruction methods. ...

...It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. The algorithms are optimized with using of different SIMD CPU extensions. In particular the library supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. ...

OpenANN is a basic artificial neural network toolset. It is not being actively maintained. For performance neural networking, consider an alternative (such as https://sourceforge.net/projects/openann-project or https://www.tensorflow.org)

The NeuroSolutions: Formula Generator utility converts the weights file of a default MLP breadboard (1-hidden layer with a TanhAxon in the hidden layer and either a TanhAxon or BiasAxon in the output layer) into a usable formula that can be copied and pasted into your own programs to compute the output of the trained neural network.

[Open Artificial Intelligence Library]. This library main goal is to provide a tool box to those who want to use algorithm such as neural network or genetics Algorithm and all algorithms that are commonly within the Artificial Intelligence field.

Syntactic is a simple C++ library for constructing general Neural networks. For now the library supports creation of multi layered networks for the Feedforward Backpropagation algorithm as well as Time Series Networks. More will be implemented soon.

SPLITNEURON is a completely new approach to large-scale, biologically plausible, neural-network simulation library based on data structures and methods directly coded into database and conceived to explicitly share load on multiple machines.

The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover

Todbot is an AI addon to the gamestool virtual machine. The aim is to create an evolving neural network topology that should be capable of creating the optimal topology and network weighting to solve any problem given it.

Neural Network class library: Its a C/C++ implementation that provides following three neural architecture - Feed-forward network, Radial Basis function network, multi-layer perceptron and Self-Organizing Maps.

This project is goaled a r-language wrap of Artificial Neural Network library libfann. also known as R-binding libfann

Turn-based strategy game for developers/technical experienced users, based on neural networks, algorithmic programming languages and other techniques.

PHPNN Is an open source, GPL licensed, PHP class library for the easy creation and manipulation of Neural Network based artificial intelligence. This library is intended for use in experimentation, games, quality control, or any other purpose.

OpenNeuron is a neural networks implementation written in Java. Currently supports only Kohonen Network model, but API is designed to be easily extended to model other network types. This implementation was used for face thermal pictures recognition.

OpenDiscreteDynamicProgrammingTemplate : founds optimal constrainted parameters of a discrete controls with second order optimization template replacing Hessian with directional derivatives and backpropagation for digital filter(as neural network)

‘intelliworm’ is a prototype simulation of a Intelligent Species of a common earth worm,which inherits human like decision making capabilities through Neural Network intelligence representation,all developed by integrating .NET with Lisp and Yacc.

This project uses massively parallel Graphics Processing Units(GPU) for neural network(Backpropagation) purposes.

A Neural network based, handwriting recognition software who's aim is to have a cursive OCR software. Although it is used in handwriting recognition, it can be used as well for creating Neural Networks and learning of those networks.

Neural network libraries in many different languages compatible with each other, such that neural networks can be trained on one platform and utilised on another.

A neural net module written in python. The aim of the project is to provide a large set of neural network types accessed by an API that is easy to use and powerful.

Integer Singular Value Decomposition Genetic Algorithm Function Fitter. This is an optimization algorithm that performs a similar role to a neural network.