Fine-Grained fMRI Classification of Visual Stimuli Using CLIP Embedding Alignment

Decoding neural signals from the human brain remains a major challenge. The classification of visual stimuli into categories based on the ImageNet taxonomy and organized according to semantic significance is a promising avenue. In this study, we propose a linear alignment framework that maps fMRI re...

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Detalles Bibliográficos

Principais autores:	Silvia Suchalova, Salvatore Calcagno, Robert Hudec, Concetto Spampinato
Formato:	Artigo
Idioma:	Inglês
Publicado:	IEEE 2026-01-01
Series:	IEEE Access
Assuntos:	fMRI classification fMRI decoding brain–computer interfaces multimodal alignment contrastive training CLIP-based representations
Acceso en liña:	https://ieeexplore.ieee.org/document/11361047/
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