P.R. Innocent

1.3k citations
32 papers · 922 · h-index 14

Impact in

Papers in

P.R. Innocent

31 papers receiving 848 citations

Peers

P.R. Innocent
Comparison fields: 5 of 105
  • Computer Vision and Pattern Recognition 406
  • Artificial Intelligence 321
  • Media Technology 85
  • Statistics and Probability 78
  • Management Science and Operations Research 114
Replace Petr Somol with:
Petr Somol Czechia
Wojciech Siedlecki United States
Simon Tong United States
Dinabandhu Bhandari India
K. Mehrotra United States
Mingyu Lu China
Nandakishore Kambhatla United States
Mingrui Wu China
Tamalika Chaira India
Jiun-Hung Chen United States
P.R. Innocent relative to Petr Somol Czechia Petr Somol's profile →
Citations per field
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Petr Somol · 1×
Citations per year

Countries citing papers authored by P.R. Innocent

Since Specialization
Citations

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

Fields of papers citing papers by P.R. Innocent

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P.R. Innocent. 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 P.R. Innocent. The network helps show where P.R. Innocent may publish in the future.

Co-authors

The 17 scholars most cited alongside P.R. Innocent, 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 P.R. Innocent Line = papers co-authored together P.R. Innocent links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002314
2 200589
3 200488
4 200073
5 200464
6 198237
7 200233
8 199721
9 200421
10 200220
11 199619
12 200218
13 200315
14 200214
15 200213
16 200413
17 198512
18 198710
19 20039
20 20016

About P.R. Innocent

P.R. Innocent is a scholar working on Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Human-Computer Interaction and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 922 indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (10 papers), Protein Structure and Dynamics (8 papers), Rough Sets and Fuzzy Logic (7 papers), Neural Networks and Applications (6 papers), Usability and User Interface Design (4 papers), Brain Tumor Detection and Classification (3 papers), Multi-Criteria Decision Making (3 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (406 citations), Artificial Intelligence (321 citations), Media Technology (85 citations), Statistics and Probability (78 citations) and Management Science and Operations Research (114 citations). P.R. Innocent has collaborated with scholars based in United Kingdom, Norway and Poland. Frequent co-authors include Robert John, Jonathan M. Garibaldi, Heiko Hirschmüller, M.R. Barnes, Parvez I. Haris, Andrzej Buller, David B. Finlay, G. H. du Boulay, D. Teather and D. Plummer. Their work appears in journals such as Artificial Intelligence in Medicine, PROTEOMICS, Behaviour and Information Technology, Information Sciences and Neuroradiology.

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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