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Crossmodal Supervised Learning Toolkit using High-Performance Extreme Learning Machines over the audio-visual-textual data

Project Description

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.

Release History

Release History

This version
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0.1.81

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0.1.80

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0.1.70

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0.1.48

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0.1.47

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0.1.46

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0.1.29

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0.1.25

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0.1.22

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0.1.21

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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

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