Abstract
As perception stands for the acquisition of a real world representation by interaction with an environment, learning is the modification of this internal representation. This book highlights the relation between perception and learning and describes the influence of the learning in the interaction with the environment. Besides, this volume contains a series of applications of both machine learning and perception, where the former is often embedded in the latter and vice-versa. Among the topics covered, there are visual perception for autonomous robots, model generation of visual patterns, attentional reasoning, genetic approaches and various categories of neural networks.
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