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Abe, Shigeo 1947-

Overview
Works: 16 works in 74 publications in 3 languages and 1,751 library holdings
Classifications: QA76.9.T48, 005.52
Publication Timeline
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Publications about Shigeo Abe
Publications by Shigeo Abe
Most widely held works by Shigeo Abe
Support vector machines for pattern classification by Shigeo Abe( file )
38 editions published between 2005 and 2010 in English and held by 1,200 libraries worldwide
Support vector machines (SVMs), were originally formulated for two-class classification problems, and have been accepted as a powerful tool for developing pattern classification and function approximations systems. This book provides a unique perspective of the state of the art in SVMs by taking the only approach that focuses on classification rather than covering the theoretical aspects. The book clarifies the characteristics of two-class SVMs through their extensive analysis, presents various useful architectures for multiclass classification and function approximation problems, and discusses kernel methods for improving generalization ability of conventional neural networks and fuzzy systems. Ample illustrations, examples and computer experiments are included to help readers understand the new ideas and their usefulness. This book supplies a comprehensive resource for the use of SVMs in pattern classification and will be invaluable reading for researchers, developers & students in academia and industry
Pattern classification : neuro-fuzzy methods and their comparison by Shigeo Abe( Book )
6 editions published between 2001 and 2013 in English and held by 279 libraries worldwide
Neural networks have a learning capability but analysis of a trained network is difficult. On the other hand, extraction of fuzzy rules is difficult but once they have been extracted, it is relatively easy to analyze the fuzzy system. This book solves the above problems by developing new learning paradigms and architectures for neural networks and fuzzy systems. The book consists of two parts: Pattern Classification and Function Approximation. In the first part, based on the synthesis principle of the neural-network classifier: A new learning paradigm is discussed and classification performance and training time of the new paradigm for several real-world data sets are compared with those of the widely-used back-propagation algorithm; Fuzzy classifiers of different architectures based on fuzzy rules can be defined with hyperbox, polyhedral, or ellipsoidal regions. The book discusses the unified approach for training these fuzzy classifiers; The performance of the newly-developed fuzzy classifiers and the conventional classifiers such as nearest-neighbor classifiers and support vector machines are evaluated using several real-world data sets and their advantages and disadvantages are clarified. In the second part: Function approximation is discussed extending the discussions in the first part; Performance of the function approximators is compared. This book is aimed primarily at researchers and practitioners in the field of artificial intelligence and neural networks
Neural networks and fuzzy systems : theory and applications by Shigeo Abe( Book )
9 editions published in 1997 in English and held by 171 libraries worldwide
<Em>Neural Networks and Fuzzy Systems: Theory and Applications</em> discusses theories that have proven useful in applying neural networks and fuzzy systems to real world problems. The book includes performance comparison of neural networks and fuzzy systems using data gathered from real systems. Topics covered include the Hopfield network for combinatorial optimization problems, multilayered neural networks for pattern classification and function approximation, fuzzy systems that have the same functions as multilayered networks, and composite systems that have been successfully applied to real world problems. The author also includes representative neural network models such as the Kohonen network and radial basis function network. New fuzzy systems with learning capabilities are also covered. <br/> The advantages and disadvantages of neural networks and fuzzy systems are examined. The performance of these two systems in license plate recognition, a water purification plant, blood cell classification, and other real world problems is compared
The penicillia by Shigeo Abe( Book )
4 editions published in 1957 in English and Japanese and held by 70 libraries worldwide
Atlas of microorganisms by Kin-ichiro Sakaguchi( Book )
in Multiple languages and held by 6 libraries worldwide
Studies on the Classification of the Penicillia by Shigeo Abe( Book )
3 editions published in 1956 in English and held by 5 libraries worldwide
Patān ninshiki no tameno sapōto bekutoru mashin nyūmon by Shigeo Abe( Book )
2 editions published in 2011 in Japanese and held by 5 libraries worldwide
Nyūraru netto to fajii shisutemu ( Book )
2 editions published in 1995 in Japanese and held by 4 libraries worldwide
Atlas of Microorganisms : The Penicillia by Shigeo Abe( Book )
2 editions published in 1957 in Multiple languages and English and held by 3 libraries worldwide
Atlas of microorganisms : The penicillia : Ed. by Kin-Ichi ro Sakaguchi ( Book )
1 edition published in 1957 in English and held by 2 libraries worldwide
Online Incremental Face Recognition System Using Eigenface Feature and Neural Classifier by Seiichi Ozawa( Book )
1 edition published in 2009 in English and held by 1 library worldwide
This chapter described a new approach to constructing adaptive face recognition systems in which a low-dimensional feature space and a classifier are simultaneously learned in an online way. To learn a useful feature space incrementally, we adopted Chunk Incremental Principal Component Analysis in which a chunk of given training samples are learned at a time to update an eigenspace model. On the other hand, Resource Allocating Network with Long-Term Memory (RAN-LTM) is adopted as a classifier model not only because incremental learning of incoming samples is stably carried out, but also because the network can be easily reconstructed to adapt to dynamically changed eigenspace models. To evaluate the incremental learning performance of the face recognition system, a selfcompiled face image database was used. In the experiments, we verify that the incremental learning of the feature extraction part and classifier works well without serious forgetting, and that the test performance is improved as the incremental learning stages proceed. Furthermore, we also show that Chunk IPCA is very efficient compared with IPCA in term of learning time; in fact, the learning speed of Chunk IPCA was at least 8 times faster than IPCA
Machi ni kosei aran by Philip K Dick( Book )
1 edition published in 2013 in Japanese and held by 1 library worldwide
Arazaran : 1 by Shigeo Abe( Book )
1 edition published in 2006 in Japanese and held by 1 library worldwide
Arazaran : 2 by Shigeo Abe( Book )
1 edition published in 2009 in Japanese and held by 1 library worldwide
Iraku kenkoku : Fukanōna kokka no genten ( Book )
1 edition published in 2004 in Japanese and held by 1 library worldwide
The penicillia : Atlas of microorganismus by Kin-ichiro Sakaguchi( Book )
1 edition published in 1957 in English and held by 1 library worldwide
 
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Abe, Shigeo 1947-
Shigeo Abe.
アベ, シゲオ 1947-
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