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Artificial vision library. Objectives are to make an OCR, fingerprint and face identification as some applications through a general purpose learning and pattern relationships algorithm (Currently performs very basic identification).
ChNIDAQ allows user programs to use the NI-DAQ C library and run interpretively without compilation. It is an ideal solution for teaching and learning data acquisition, prototyping, and web-based remote data acquisition.
FLPD is an automatic learningsystem based on fuzzy prototypes, composed of a C++ library for machine learning and fuzzy logic and an experimentation framework.
The TreeQ package is a set of C-language applications that implement a
automatic machine learning algorithm based on a tree-structured classifier. This approach is particularly effective for high-dimensional continuous data such as audio and video.
Net.py is a tool for learning about neural nets. Currently, it only allows the user to experiment with a Hopfield net. I am now extending it to cover the Kohonen net. I'd be pleased to receive suggestions and criticism.
GNNS - GNNS Neural Network Simulator, is both a set of libraries and an interface for creating and learning neural networks. It is aimed to support as many network typs and learning algorithms as possible. GNNS is meant to support different platforms.
HORUS is a system for knowledge acquisition, hypothesis generation, inference and learning. It is an interactive, internet environment accessible to a diverse community of users (public-access or membership basis) - see also UMKAILASH project for more.
AiM is a system for intelligent computer-aided learning and assessment in mathematics and related disciplines, based on a symbolic mathematics program.
SimAlgPro - it is a tool to simulate the main algorithms for processor planning. to contribute to the learning process. It allows visualize of interactive form the algorithm application and results.
iMate is a win32 / Linux desktop mate programme. It offers more features than the already existing desktop mate (AI, learning capacity, growth and limited lifeTime, third party tools to add new behaviour, ...).
Signal Processing and Classification Environment in Python using YAML
pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...
ScenConnect shows scenarios as networks of situation and event tag sets, for fast comparisons. It links scenarios to tags, scores, and other metadata, creating situationals suitable for search, mining, machine learning, and planning.