This book introduces neural mechanisms of biological vision and how artificial intelligence algorithms learn to interpret images.
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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.
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Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In English. Artikel-Nr. ria9781108483438_new
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Anbieter: moluna, Greven, Deutschland
Gebunden. Zustand: New. Vision applications are pervasive from smartphones that recognize faces to automatic analysis of clinical images. This book bridges neuroscience, cognitive science, computer science, and artificial intelligence to explain neural mechanisms of biological vis. Artikel-Nr. 400013214
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Anbieter: Kennys Bookstore, Olney, MD, USA
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Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Hardcover. Zustand: Brand New. 280 pages. 10.00x7.25x0.75 inches. In Stock. Artikel-Nr. x-1108483437
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - 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. Artikel-Nr. 9781108483438
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