cross-subject-generalization

This paper examines how evaluation protocols affect reported accuracy in EEG emotion recognition, using a DGCNN on SEED and SEED-IV datasets. It demonstrates that subject-dependent, subject-disjoint, and cross-session evaluations answer different questions, and that checkpoint selection and test-set reuse can inflate accuracy.