Abstract: Dynamic image degradations, including noise, blur and lighting inconsistencies, pose significant challenges in image restoration, often due to sensor limitations or adverse environmental ...
Abstract: In this study, we propose AlphaGrad, a novel adaptive loss blending strategy for optimizing multi-task learning (MTL) models in motor imagery (MI)-based electroencephalography (EEG) ...
Abstract: Conventional loss functions for gradient descent are designed mainly to assess output quality, with limited attention to gradient behavior. This study identifies the gradient inconsistency ...