policy

Multiclass_Classification_HarmfulBrainActivity

aryanmaingi · PyTorch

or hover any field below to flag it

Overview

Name
Multiclass_Classification_HarmfulBrainActivity
Author
aryanmaingi
Framework
PyTorch
License
unknown
Skill type
manipulation
Evidence level
untested
Task description
ResNet50-based deep learning model for multiclass classification of harmful brain activity using raw EEG (Parquet, 200 Hz) and regional spectrogram power (LL, RL, LP, RP). Trained with Stratified Group K-Fold for patient-wise generalization. Uses zero-imputation for stable tensor input. Optimized fo

Spaces

Action space
other · 0-dim · 0Hz
Observation space
  • type: other

Links

HuggingFace repo
null
Paper (arXiv)
null

Compatible robots

20

Compatible environments

0

No environments list Multiclass_Classification_HarmfulBrainActivity yet.

Datasets that reference this policy

0

No datasets reference Multiclass_Classification_HarmfulBrainActivity yet.