用于深度学习的视觉感知计算模型：最新技术、挑战和前景
Visual Sensation and Perception Computational Models for Deep Learning: State of the art, Challenges and Prospects
摘要：
视觉感知是指在环境意识和理解中感知、组织、识别和解释视觉信息的过程。受视觉感知启发的计算模型具有复杂性和多样性的特点，因为它们来自认知科学、信息科学和人工智能等多个学科。本文从生物视觉机制和计算视觉理论出发，系统地研究了面向深度学习的视觉感知计算模型。最后对视觉感知计算模型的发展前景提出了一些看法。最后，本文还总结了视觉感知目前面临的挑战，并预测了其未来的发展趋势。通过本次调查，将为该方向的研究提供全面的参考。
英文摘要：
Visual sensation and perception refers to the process of sensing, organizing, identifying, and interpreting visual information in environmental awareness and understanding. Computational models inspired by visual perception have the characteristics of complexity and diversity, as they come from many subjects such as cognition science, information science, and artificial intelligence. In this paper, visual perception computational models oriented deep learning are investigated from the biological visual mechanism and computational vision theory systematically. Then, some points of view about the prospects of the visual perception computational models are presented. Finally, this paper also summarizes the current challenges of visual perception and predicts its future development trends. Through this survey, it will provide a comprehensive reference for research in this direction.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
