Miho Ohsaki

785 citations
54 papers · 430 indexed · h-index 9

Miho Ohsaki

47 papers receiving 397 citations

Peers

Miho Ohsaki
Comparison fields: 5 of 93
  • Signal Processing 98
  • Artificial Intelligence 199
  • Computer Vision and Pattern Recognition 114
  • Health Information Management 23
  • Computer Graphics and Computer-Aided Design 15
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Citations per year

Countries citing papers authored by Miho Ohsaki

Since Specialization
Citations

This map shows the geographic impact of Miho Ohsaki'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 Miho Ohsaki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miho Ohsaki more than expected).

Fields of papers citing papers by Miho Ohsaki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miho Ohsaki. 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 Miho Ohsaki. The network helps show where Miho Ohsaki may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Miho Ohsaki, 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 Miho Ohsaki Line = papers co-authored together Miho Ohsaki links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20233
2
Study on Maximum Bayes Boundary-ness Training for Pattern Classification
20200
3 20181
4 2017142
5 20122
6 20111
7
Comparison between Minimum Classification Error Training and Support Vector Machine in Prototype-based Classifier Design
20100
8
Large Geometric Margin Minimum Classification Error Training for Kernel-based High Dimensional Space
20101
9
Minimum Classification Error Training with Automatic Control of Loss Smoothness
20102
10 20108
11
Geometric Margin Control for Minimum Error Classification
20091
12 20081
13 200741
14 20070
15
Part VI-Risk Management Systems with Intelligent Data Analysis-Implementing an Integrated Time-Series Data Mining Environment Based on Temporal Pattern Extraction Methods: A Case Study of an
20061
16
Evaluation of rule interestingness measures with a clinical dataset on hepatitis
20049
17
Development and Evaluation of an Integrated Time - Series KDD Environment -A Case Study of Medical KDD on Hepatitis-
20042
18
A Study on Modeling of Search Space with GA Sampling
20030
19
Investigation of Rule Interestingness in Medical Data Mining
20032
20 200225

About Miho Ohsaki

Miho Ohsaki is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 54 papers that have together received 430 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (14 papers), Face and Expression Recognition (12 papers), Data Mining Algorithms and Applications (11 papers), Neural Networks and Applications (10 papers), Rough Sets and Fuzzy Logic (8 papers), Time Series Analysis and Forecasting (7 papers), Speech and Audio Processing (5 papers) and Gaussian Processes and Bayesian Inference (5 papers). The work is most often cited by research in Signal Processing (98 citations), Artificial Intelligence (199 citations) and Computer Vision and Pattern Recognition (114 citations). Miho Ohsaki has collaborated with scholars based in Japan, Malaysia and Belgium. Frequent co-authors include Hideyuki Takagi, Shigeru Katagiri, Kenji Matsuda, Anca Ralescu, Peng Wang, Takahira Yamaguchi, Hideto Yokoi, Shusaku Tsumoto, Kazuya Okamoto and Hiroshi Ohno. Their work appears in journals such as Scientific Reports, IEEE Transactions on Evolutionary Computation and IEEE Transactions on Knowledge and Data Engineering.

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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