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 vision and how artificial intelligence computer vision systems work.
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 vision and how artificial intelligence computer vision systems work.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
Inhaltsangabe
1. Introduction to the world of vision 2. The travels of a photon - natural image statistics and the retina 3. The phenomenology of seeing 4. Creating and altering visual percepts through lesions and electrical stimulation 5. Adventures in terra incognita: probing the neural circuits along the ventral visual stream 6. From the highest echelons of visual processing to cognition 7. Neurobiologically plausible computational models 8. Teaching computers how to see 9. Towards a world with intelligent machines that can interpret the visual world 10. Visual consciousness.
1. Introduction to the world of vision 2. The travels of a photon - natural image statistics and the retina 3. The phenomenology of seeing 4. Creating and altering visual percepts through lesions and electrical stimulation 5. Adventures in terra incognita: probing the neural circuits along the ventral visual stream 6. From the highest echelons of visual processing to cognition 7. Neurobiologically plausible computational models 8. Teaching computers how to see 9. Towards a world with intelligent machines that can interpret the visual world 10. Visual consciousness.
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