Neural Learning Methods for Visual Object Detection
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BeschreibungVisual object detection by artificial cognitive systems is currently a great research challenge, both at the theoretical as well as the technical level. On the one hand, a more fundamental understanding of the mechanisms employed by the human brain for this purpose is desired, and, on the other hand, important technical applications could be realized by successful visual object detection, particularly in the domain of intelligent vehicles. This book describes a number of methods, centered around artificial neural networks, that address important issues in the object detection/identification process. Each method is evaluated in a concrete application context, thus giving insights not only into theoretical aspects of the object detection process but also showing potential applicability in technical systems.
PortraitAlexander Gepperth graduated in theoretical physics at the LMU in Munich. He received his PhD in physics at the Ruhr-Universitat Bochum in 2006 as a member of the Institute for Neural Dynamics. Since 2006, he is doing basic research on brain-like learning methods and applications at the Honda Research Institute Europe GmbH.
Untertitel: Brain-like Principles for Environment Perception in Artificial Cognitive Systems. Paperback. Sprache: Englisch.
Verlag: VDM Verlag
Erscheinungsdatum: Juli 2008
Seitenanzahl: 132 Seiten