Yoichi Kageyama

649 citations
121 papers · 454 indexed · h-index 10
Topics
Speech and Audio Processing (17 papers)Remote-Sensing Image Classification (14 papers)Face recognition and analysis (11 papers)
Partner nations
JapanChinaUnited States

In The Last Decade

Yoichi Kageyama

90 papers receiving 422 citations

Peers

Yoichi Kageyama
Comparison fields: 5 of 97
  • Endocrinology, Diabetes and Metabolism 98
  • Water Science and Technology 98
  • Computer Vision and Pattern Recognition 73
  • Environmental Engineering 65
  • Media Technology 49
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Citations per field
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Citations per year

Countries citing papers authored by Yoichi Kageyama

Since Specialization
Citations

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

Fields of papers citing papers by Yoichi Kageyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoichi Kageyama

This figure shows the co-authorship network connecting the top 25 collaborators of Yoichi Kageyama. A scholar is included among the top collaborators of Yoichi Kageyama based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yoichi Kageyama. Yoichi Kageyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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BASIC STUDY OF LAND COVER CLASSIFICATION USING RAPIDEYE DATA TO ESTIMATE THE AMOUNT OF DISASTER WASTE
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10 5
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Detection and feature analysis of groundwater discharge points in coastal regions around Mt Chokaisan, Japan using ALOS AVNIR-2 data
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13
Analysis of lip motion due to the influence of vocalization
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14
Algorithm for Estimating Ratio of Harmful Vegetation to Manage River Bank
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Features for image retrieval: The impression degree of a human image by overexposure occurring in the facial area
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About Yoichi Kageyama

Yoichi Kageyama is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 121 papers that have together received 454 indexed citations. Recurring topics across this work include Speech and Audio Processing (17 papers), Remote-Sensing Image Classification (14 papers) and Face recognition and analysis (11 papers). The work is most often cited by research in Water Science and Technology (98 citations), Endocrinology, Diabetes and Metabolism (98 citations) and Media Technology (49 citations). Yoichi Kageyama has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Elena Bravo, T Saruta, Hiromichi Suzuki, Hiroyuki Suzuki, Hiroshi Yokoyama, Makoto Nishida, Dejian Wang, Hiroko Hosaka, Masaki Ishii and Tsuyoshi Takahashi. Their work appears in journals such as Hypertension, Sensors and Journal of the Physical Society of Japan.

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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