Crossmodal Supervised Learning Toolkit using High-Performance Extreme Learning Machines over the audio-visual-textual data
Cerebrum’s purpose is getting continuous data inputs from different types of perceptions as memory sequences that triggered according to predefined threshold values and creating a complex time based relations between those memories by Crossmodal logic and training multiple Long Short-Term Memory Networks with this extracted data. Lastly creating outputs triggered by a stimuli, using pre-trained Artificial Neural Networks.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|File Name & Checksum SHA256 Checksum Help||Version||File Type||Upload Date|
|cerebrum-0.1.81-py2.py3-none-any.whl (45.3 kB) Copy SHA256 Checksum SHA256||2.7||Wheel||Apr 20, 2016|
|cerebrum-0.1.81.tar.gz (23.0 kB) Copy SHA256 Checksum SHA256||–||Source||Apr 20, 2016|