Human Vision

Human vision research aims to understand how the visual system processes information, from low-level features like color and texture to high-level tasks like object recognition and scene understanding. Current research focuses on bridging the gap between human and artificial vision by developing models that incorporate aspects of human visual processing, such as attention mechanisms, peripheral vision, and the influence of illumination conditions, often leveraging deep learning architectures like Vision Transformers and convolutional neural networks. These efforts are significant because they not only advance our fundamental understanding of the brain but also have practical implications for improving computer vision systems, particularly in areas like image compression, object detection, and assistive technologies for the visually impaired.