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  • 1
    Online Resource
    Online Resource
    Cambridge :Cambridge University Press,
    UID:
    almafu_9960118872302883
    Format: 1 online resource (xxii, 251 pages) : , digital, PDF file(s).
    ISBN: 1-108-75926-2 , 1-316-99924-6 , 1-108-64999-8
    Content: 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.
    Note: Title from publisher's bibliographic system (viewed on 08 Feb 2021).
    Additional Edition: ISBN 1-108-48343-7
    Language: English
    Subjects: Biology
    RVK:
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Book
    Book
    Cambridge, United Kingdom : Cambridge University Press
    UID:
    gbv_1737254530
    Format: xxii, 251 Seiten , Illustrationen, Diagramme
    ISBN: 9781108483438 , 9781108705004
    Additional Edition: ISBN 9781108649995
    Additional Edition: Erscheint auch als Online-Ausgabe Kreiman, Gabriel, 1971 - Biological and computer vision Cambridge, United Kingdom : Cambridge University Press, 2021 ISBN 9781108649995
    Language: English
    Subjects: Computer Science , Biology
    RVK:
    RVK:
    Keywords: Maschinelles Sehen ; Maschinelles Sehen ; Bioinformatik ; Visuelles System ; Mustererkennung
    Library Location Call Number Volume/Issue/Year Availability
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