Biological and Computer Vision

Imagine a world where machines can see and understand the world the way humans do. Rapid progress in artificial intelligence has led to smartphones that recognize faces, cars that detect pedestrians, and algorithms that suggest diagnoses from clinical images, among many other applications. The success of computer vision is founded on a deep understanding of the neural circuits in the brain responsible for visual processing. This book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the psychological understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence. Topics include the neurophysiological investigation of visual cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among others. It is an ideal resource for students and researchers looking to build bridges across different approaches to studying and developing visual systems.

• Combines research from animal and human visual cognition, the brain, and artificial intelligence vision systems
• Introduces state-of-the-art topics in biological vision and algorithmic approaches to modeling visual systems in machines
• Explains experimental design, hypothesis testing, and critical thinking through discussion of biological and computational experiments in vision research
• Shows how machines are trained to see and interpret the visual world around us