We argue that prediction success maximization is a basic objective of cognition and cortex,
that it is compatible with but distinct from prediction error minimization, that neither objective …

Deep neural networks have been remarkably successful as models of the primate visual
system. One crucial problem is that they fail to account for the strong shape-dependence of …

This article presents a transdisciplinary analysis of the challenges in fusing neuroscience
concepts with artificial intelligence (AI) to create AI systems inspired by biological cognition …

This special issue on “What Can Computer Vision Learn From Visual Neuroscience?”
follows a workshop with the same name organized by the editors at the Computer Vision …

Contemporary neural networks frequently encounter the challenge of catastrophic forgetting,
wherein newly acquired learning can overwrite and erase previously learned information …

In this paper, the design of a new structure of deep neural networks is discussed with the
aim of use in industrial applications to detect defects in metal parts and to separate defective …