Error-perception-classification-in-BCI-using-CNN

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software/error-perception-classification-in-bci-using-cnn

This work aims to classify the occurrence of a feedback error, i.e., the perception of an error by a user interacting with a Brain-Computer Interface (BCI). To achieve that, Convolutional Neural…

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Error-perception-classification-in-BCI-using-CNN project image — GitHub preview card for LeafarCoder/Error-perception-classification-in-BCI-using-CNN. Served by its origin, not stored here, and not covered by this registry’s licence.

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Category: Software & Systems
Subcategory: unknown
License: MIT(osi)
Status: dormant
Maturity: deployed
Organization: unknown
Country: unknown
Homepage: unknown
Repository: github.com/LeafarCoder/Error-perception-classification-in-BCI-using-CNN
Documentation: unknown
Tags: brain-computer-interface · comet-ml · deep-learning · error-perception · machine-learning · master-thesis · python · pytorch
Regulatory: unknown

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api.github.com/repos/LeafarCoder/Error-perception-classification-in-BCI-using-CNN
retrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2021-10-09, 5 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

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