Explores the synergy between machine learning and neuroscience, showcasing how deep neural networks can predict neural responses and the challenges faced by AI in robotics.
Explores techniques for delineation, including Hough transform, gradient orientation, and shape detection, emphasizing the importance of combining graph-based techniques and machine learning.
Explores neuroprostheses for sensory systems, including auditory, vestibular, vision, and tactile applications, addressing the challenges of artificial vision.
