Takashi Imai

This study evaluates out-of-distribution detection in DNA barcoding using genetic distance and deep learning metrics, finding that detection is more sensitive to sequence noise and lack of diagnosable characters than identification accuracy.

This paper introduces a deep neural network framework that directly predicts the complex-valued analytic signal of EEG from raw data, outperforming traditional methods and showing robustness to missing electrodes.