Cambridge University Press 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. Book Description This book introduces neural mechanisms of biological vision and how artificial intelligence algorithms learn to interpret images. About the Author Gabriel Kreiman is a professor at the Center for Brains, Minds, and Machines and the Children's Hospital at Harvard Medical School. Awards received by Prof. Kreiman include: the National Institute of Health (NIH) New Innovator Award, National Science Foundation (NSF) Career Award, Pisart Award for Vision Resarch, and McKnight Foundation Research Award.