| Literature DB >> 31394043 |
Abstract
Artificial vision has often been described as one of the key remaining challenges to be solved before machines can act intelligently. Recent developments in a branch of machine learning known as deep learning have catalyzed impressive gains in machine vision-giving a sense that the problem of vision is getting closer to being solved. The goal of this review is to provide a comprehensive overview of recent deep learning developments and to critically assess actual progress toward achieving human-level visual intelligence. I discuss the implications of the successes and limitations of modern machine vision algorithms for biological vision and the prospect for neuroscience to inform the design of future artificial vision systems.Entities:
Keywords: action recognition; artificial intelligence; computational neuroscience; deep learning; face recognition; image segmentation; neural networks; object recognition
Mesh:
Year: 2019 PMID: 31394043 DOI: 10.1146/annurev-vision-091718-014951
Source DB: PubMed Journal: Annu Rev Vis Sci ISSN: 2374-4642 Impact factor: 6.422