• Models for the neurons of various visual levels (不同视觉层次神经元的模型)
• Neural coding and decoding of visual information (视觉信息的神经编码与解码)
• Neural networks for local visual circuits (局部视觉回路的神经网络)
• Visual mechanism inspired deep neural networks (受视觉机制启发的深度神经网络)
• Visual models for image processing (用于图像处理的视觉模型)
• Visual mechanism inspired models for computer vision applications (受视觉机制启发的计算机视觉应用模型)
• Hardware implementations of visual models (视觉模型的硬件实现)
• Artificial vision related software and hardware (与人工智能视觉相关的软硬件)
• Visual models for temporal information processing (用于时间信息处理的视觉模型)
• Receptive field-based models (基于感受野的模型)
• Biologically inspired novel spiking neural networks and optimization methods (受生物启发的新型脉冲神经网络及其优化方法)
• Visual dynamic information processing technology based on event camera (基于事件相机的视觉动态信息处理技术)

The visual system of the brain is a complex and efficient image processing system, and it is an important source of computer vision theory and technological innovation. Brain-inspired and imitated brains are important breakthroughs in the theoretical innovation and technological revolution of the new generation of artificial intelligence. From the perspective of computational simulation, it helps to clarify or predict some information processing mechanisms of the brain's visual system; on the other hand, it also provides a series of new general-purpose computing models and common key technologies for many engineering applications centered on intelligent environment perception. This proposed Biologically Inspired Vision and Image Processing (BIVIP) Special Issue welcomes original, unpublished contributions from authors.