H. B. Mitchell

2.1k citations
39 papers · 1.6k · h-index 17

Impact in

Papers in

H. B. Mitchell

37 papers receiving 1.5k citations

Peers

H. B. Mitchell
Comparison fields: 5 of 116
  • Management Science and Operations Research 820
  • Statistics and Probability 437
  • Media Technology 172
  • Computational Theory and Mathematics 275
  • Artificial Intelligence 553
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Éloi Bossé Canada
Yafei Song China
Miguel Pagola Spain
Jiulun Fan China
Lei Lei China
Enrique H. Ruspini United States
Anne-Laure Jousselme Canada
Derek T. Anderson United States
Hongxing Li China
Kokichi Tanaka Japan
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Citations per field
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Citations per year

Countries citing papers authored by H. B. Mitchell

Since Specialization
Citations

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

Fields of papers citing papers by H. B. Mitchell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by H. B. Mitchell. 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 H. B. Mitchell. The network helps show where H. B. Mitchell may publish in the future.

Co-authors

The 1 scholars most cited alongside H. B. Mitchell, 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 H. B. Mitchell Line = papers co-authored together H. B. Mitchell links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003339
2 2007217
3 2004131
4 2012102
5 2010100
6 2004100
7 201090
8 199774
9 200656
10 200148
11 199942
12 200032
13 199828
14 199127
15 200026
16 200422
17 200520
18 199215
19 199415
20 199311

About H. B. Mitchell

H. B. Mitchell is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Management Science and Operations Research, Statistics and Probability and Signal Processing, having authored 39 papers that have together received 1.6k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (16 papers), Advanced Data Compression Techniques (12 papers), Multi-Criteria Decision Making (10 papers), Fuzzy Systems and Optimization (9 papers), Neural Networks and Applications (9 papers), Fuzzy Logic and Control Systems (7 papers), Rough Sets and Fuzzy Logic (4 papers) and Video Coding and Compression Technologies (3 papers). The work is most often cited by research in Management Science and Operations Research (820 citations), Statistics and Probability (437 citations), Media Technology (172 citations), Computational Theory and Mathematics (275 citations) and Artificial Intelligence (553 citations). H. B. Mitchell has collaborated with scholars based in Israel and United States. Frequent co-authors include J. Wachtel. Their work appears in journals such as International Journal of Intelligent Systems, Signal Processing Image Communication, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, Electronics Letters and Signal Processing.

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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