Hierarchical Neural Networks for Image Interpretation

Hierarchical Neural Networks for Image Interpretation

Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in lim...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας:	Behnke, Sven (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή:	SpringerLink (Online service)
Μορφή:	Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:	English
Έκδοση:	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2003.
Έκδοση:	1st ed. 2003.
Σειρά:	Lecture Notes in Computer Science, 2766
Θέματα:	Computers. Neurosciences. Algorithms. Artificial intelligence. Optical data processing. Pattern recognition. Computation by Abstract Devices. Algorithm Analysis and Problem Complexity. Artificial Intelligence. Image Processing and Computer Vision. Pattern Recognition.
Διαθέσιμο Online:	Full Text via HEAL-Link

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