Shigeo Abe

11.3k citations

198 papers · 7.4k indexed · 3 hit papers · h-index 31

Impact in

Computer Vision and Pattern Recognition top 0.5%
- Face and Expression Recognition
- Image Retrieval and Classification Techniques
Artificial Intelligence top 0.2%
- Neural Networks and Applications
- Fuzzy Logic and Control Systems
- Imbalanced Data Classification Techniques
- Anomaly Detection Techniques and Applications

Papers in

Computer Vision and Pattern Recognition 73
- Face and Expression Recognition 63
Artificial Intelligence 106
- Neural Networks and Applications 58
- Fuzzy Logic and Control Systems 38
- Machine Learning and ELM 25
- Metaheuristic Optimization Algorithms Research 10

Co-authors: Ming-Shong Lan Takuya Inoue Ruck Thawonmas Yasuyoshi Kaneko Akihiro Doi Minoru Maruyama Seiichi Ozawa Victor N. Uebele
Journals: Neural Networks (5 papers)Journal of the Meteorological Society of Japan Ser II (5 papers)IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) (5 papers)Pattern Recognition Letters (3 papers)IEEJ Transactions on Industry Applications (3 papers)
Partner nations: Japan United States Germany

In The Last Decade

Shigeo Abe

179 papers receiving 7.0k citations

Hit Papers

align trajectories log scale

Support Vector Machines for Pattern Classification 2010 · 389 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2010 Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B))
2005 Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B))
2001 Pattern Classification

Peers

Countries citing papers authored by Shigeo Abe

Since Specialization

Citations

This map shows the geographic impact of Shigeo Abe's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shigeo Abe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shigeo Abe more than expected).

Fields of papers citing papers by Shigeo Abe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shigeo Abe. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shigeo Abe. The network helps show where Shigeo Abe may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Shigeo Abe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shigeo Abe Line = papers co-authored together Shigeo Abe links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	Training Mahalanobis Kernels by Linear Programming Lecture notes in computer science ·Shigeo Abe	2012	0
2	Subspace-Based L2 Support Vector Machines Takuya Kitamura, Shigeo Abe	2010	0
3	Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space Lecture notes in computer science ·Nadine Davina Krisam, Shigeo Abe	2007	1
4	Fuzzy LP-SVMs for Multiclass Problems. The European Symposium on Artificial Neural Networks ·Shigeo Abe	2004	16
5	Fuzzy Support Vector Machines for Multiclass Problems The European Symposium on Artificial Neural Networks ·Shigeo Abe, Takuya Inoue	2002	92
6	Improvement of Generalization Ability of a Fuzzy Classifier with Ellipsoidal Regions by the Optimum Division of Data Transactions of the Institute of Systems Control and Information Engineers ·M. Kobayashi, Deri Derliana, Shigeo Abe	2000	0
7	On Input Invariance of Fuzzy Classifiers with Learning Capability Transactions of the Institute of Systems Control and Information Engineers ·Bagus Hilmawan, Shigeo Abe	1999	0
8	A Genetic Algorithm Approach to Optimization Problems with Uncertainties Transactions of the Institute of Systems Control and Information Engineers ·Hisashi Tamaki, Toshihiko Arai, Shigeo Abe	1999	1
9	Tuning of a fuzzy classifier derived from data by solving inequalities IEICE Transactions on Information and Systems ·Ruck Thawonmas, Shigeo Abe	1998	0
10	Fuzzy Clustering Networks : Design Criteria for Approximation and Prediction IEICE Transactions on Information and Systems ·John B. O. Mitchell, Shigeo Abe	1996	2
11	Efficient methods for fuzzy rule extraction from numerical data McGraw-Hill, Inc. eBooks ·Shigeo Abe, Ming-Shong Lan	1996	4
12	Global convergence of the hopfield neural network with non-zero diagonal elements IEEE Transactions on Circuits & Systems II Express Briefs ·Shigeo Abe, Andrew H. Gee	1995	2
13	Character recognition using fuzzy rules extracted from data Ming-Shong Lan, Park Bum Ki, Shigeo Abe	1994	6
14	Tuning of a fuzzy classifier derived from data Shigeo Abe, Grete Sofie Hortemo, Ruck Thawonmas	1994	1
15	Dependency of Generalization Capability for a Multi-Layered Neural Network on its Number of Hideen Units. IEEJ Transactions on Industry Applications ·Zen Xiaojun, Shigeo Abe, Hiroshi Takenaga, JAQULINE CHINNA RANI I.	1993	2
16	Determining Optimal Number of Hidden Units for Multi-Layered Neural Networks. IEEJ Transactions on Industry Applications ·Zen Xiaojun, Shigeo Abe, Hiroshi Takenaga, JAQULINE CHINNA RANI I.	1992	2
17	Input layer optimization of neural networks by sensitivity analysis and its application to recognition of numerals. IEEJ Transactions on Industry Applications ·Hiroshi Takenaga, Shigeo Abe, EugÃ¨ne Mbuyi Mukendi, Zen Xiaojun, 裕小川, Eduard Schubert	1991	2
18	How neural networks for pattern recognition can be synthesized Journal of information processing ·Shigeo Abe, Zen Xiaojun, Hiroshi Takenaga	1991	9
19	A Trial to Reduce Truncation Errors of the Pressure Gradient Force in the Sigma Coordinate Systems Journal of the Meteorological Society of Japan Ser II ·潔井出, Shigeo Abe	1982	3
20	The Nishinihon Journal of Dermatology ·津田忠昭, 渡会文果, Shigeo Abe	1975	1

About Shigeo Abe

Shigeo Abe is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Control and Systems Engineering and Energy Engineering and Power Technology, having authored 198 papers that have together received 7.4k indexed citations. Recurring topics across this work include Face and Expression Recognition (63 papers), Neural Networks and Applications (58 papers), Fuzzy Logic and Control Systems (38 papers), Machine Learning and ELM (25 papers), Power System Optimization and Stability (14 papers), Metaheuristic Optimization Algorithms Research (10 papers), Optimal Power Flow Distribution (9 papers) and Advanced Algorithms and Applications (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.1k citations), Artificial Intelligence (3.0k citations), Signal Processing (641 citations), Media Technology (440 citations) and Control and Systems Engineering (1.1k citations). Shigeo Abe has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Ming-Shong Lan, Takuya Inoue, Ruck Thawonmas, Yasuyoshi Kaneko, Akihiro Doi, Minoru Maruyama, Seiichi Ozawa, Victor N. Uebele, Tao Ban and R.R. Shoults. Their work appears in journals such as Neural Networks, Journal of the Meteorological Society of Japan Ser II, IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), Pattern Recognition Letters and IEEJ Transactions on Industry Applications.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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