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This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses.
This project has 2 subprojects:
Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api
Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api
A video from the first prototype has been made:
http://www.youtube.com/watch?
Mullpy is a machine-learning library that mainly aim to solve multi-label problems. It is classifier independent, has many ensemble capabilities (diversity methods like bagging, random subspaces, etc.) and automated results presentation (Excel, images as ROC or class-separated info, etc.). It is fully configurable. At the moment supports Neural Networks and classifiers defined in files. It is working on python3.3.
NeMo is a high-performance spiking neuralnetwork simulator which simulates networks of Izhikevich neurons on CUDA-enabled GPUs. NeMo is a C++ class library, with additional interfaces for pure C, Python, and Matlab.
This software uses computer vision algorithms for mining sequence data from telemonitoring data with CBRs. We propose an approach which treats the detection of changes in behavior detected with a sensor/video fusion, which occur at radically different time-scales, through a CBR in two levels: low and high level. The system is always updating the database with the daily data.
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