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Hierarchical Neural Networks for Image Interpretation

โœ Scribed by Sven Behnke (auth.)


Publisher
Springer-Verlag Berlin Heidelberg
Year
2003
Tongue
English
Leaves
244
Series
Lecture Notes in Computer Science 2766
Edition
1
Category
Library

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โœฆ Subjects


Computation by Abstract Devices; Neurosciences; Algorithm Analysis and Problem Complexity; Artificial Intelligence (incl. Robotics); Image Processing and Computer Vision; Pattern Recognition


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Hierarchical Neural Networks for Image I
โœ Sven Behnke (auth.) ๐Ÿ“‚ Library ๐Ÿ“… 2003 ๐Ÿ› Springer-Verlag Berlin Heidelberg ๐ŸŒ English

<p><P>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

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<p>In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are mainly evaluated within the phoneme recognition task under the Hybrid Hidden Markov Model/Artificial Neural Network (HMM/ANN) paradigm. The baseline hierarchical