Gerald M. Knapp

31 papers receiving 582 citations

Peers

Gerald M. Knapp
Comparison fields: 5 of 75
  • Medical Laboratory Technology 83
  • Safety, Risk, Reliability and Quality 218
  • Industrial and Manufacturing Engineering 128
  • Statistics, Probability and Uncertainty 71
  • Software 31
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Zhenglin Liang China
Mageed Ghaleb Saudi Arabia
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Citations per year

Countries citing papers authored by Gerald M. Knapp

Since Specialization
Citations

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

Fields of papers citing papers by Gerald M. Knapp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gerald M. Knapp. 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 Gerald M. Knapp. The network helps show where Gerald M. Knapp may publish in the future.

Co-authors

The 15 scholars most cited alongside Gerald M. Knapp, 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 Gerald M. Knapp Line = papers co-authored together Gerald M. Knapp 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 1997150
2 1995113
3 199860
4 200347
5 199245
6 201036
7 199229
8 199220
9 200219
10 199817
11 200214
12 200014
13 200112
14 201111
15 201210
16 20068
17 19967
18
Affect Intensity Estimation Using Multiple Modalities
20147
19 20116
20 20115

About Gerald M. Knapp

Gerald M. Knapp is a scholar working on Artificial Intelligence, Control and Systems Engineering, Safety, Risk, Reliability and Quality, Industrial and Manufacturing Engineering and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 652 indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (7 papers), Fault Detection and Control Systems (5 papers), Sentiment Analysis and Opinion Mining (4 papers), Advanced Manufacturing and Logistics Optimization (4 papers), Emotion and Mood Recognition (4 papers), Image Retrieval and Classification Techniques (3 papers), Quality and Safety in Healthcare (3 papers) and Machine Fault Diagnosis Techniques (3 papers). The work is most often cited by research in Medical Laboratory Technology (83 citations), Safety, Risk, Reliability and Quality (218 citations), Industrial and Manufacturing Engineering (128 citations), Statistics, Probability and Uncertainty (71 citations) and Software (31 citations). Gerald M. Knapp has collaborated with scholars based in United States. Frequent co-authors include Lawrence Mann, Boris Kovalerchuk, Evangelos Triantaphyllou, Hsu‐Pin Wang, Milind Mahajan, Bin Chen, Daniel J. Fonseca, Haijing Wang, Fereydoun Aghazadeh and Tapabrata Ray. Their work appears in journals such as Journal of Quality in Maintenance Engineering, Computers & Industrial Engineering, International Journal of Production Research, International Journal of Information Security and IEEE Transactions on Multimedia.

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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