AliAmini93/TactileNet
Developed TactileNet, the first deep-learning model designed for surface roughness recognition using EEG data. This project leverages CNNs to classify surface textures encountered through a robotic device in tactile trials.
This project helps researchers and engineers working with robotics and human-robot interaction to automatically identify how rough a surface feels to a robot. It takes brainwave (EEG) data recorded during a robotic tactile interaction and classifies the surface texture. This tool is ideal for neuroscientists, robotics engineers, and materials scientists studying haptic perception and robotic sensing.
No commits in the last 6 months.
Use this if you need to classify surface roughness based on EEG signals collected when a robotic device touches various textures.
Not ideal if you are looking to classify textures using visual data or direct physical measurements of roughness rather than brainwave activity.
Stars
32
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1
Language
Python
License
MIT
Category
Last pushed
Jul 27, 2022
Commits (30d)
0
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