John W. V. Miller

87 total papers · 690 total citations
42 papers, 497 citations indexed

About

John W. V. Miller is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, John W. V. Miller has authored 42 papers receiving a total of 497 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 10 papers in Media Technology and 9 papers in Artificial Intelligence. Recurrent topics in John W. V. Miller's work include Medical Image Segmentation Techniques (9 papers), Industrial Vision Systems and Defect Detection (7 papers) and CCD and CMOS Imaging Sensors (6 papers). John W. V. Miller is often cited by papers focused on Medical Image Segmentation Techniques (9 papers), Industrial Vision Systems and Defect Detection (7 papers) and CCD and CMOS Imaging Sensors (6 papers). John W. V. Miller collaborates with scholars based in United States, United Kingdom and Japan. John W. V. Miller's co-authors include Padhraic Smyth, R.M. Goodman, Frederick M. Waltz, Charles M. Higgins, M. Shridhar, James B. Farison, Joe P. Windham, Kai Wang, F. Alleva and Kevin G. Harding and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Transactions on Image Processing and Soil Science Society of America Journal.

In The Last Decade

John W. V. Miller

37 papers receiving 453 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
John W. V. Miller	125	113	112	67	46	42	497
Caiyu Liu	94 0.8×	64 0.6×	116 1.0×	288 4.3×	24 0.5×	21	605
T. Anitha	48 0.4×	36 0.3×	239 2.1×	20 0.3×	49 1.1×	29	500
Qing Guo	193 1.5×	66 0.6×	37 0.3×	59 0.9×	11 0.2×	34	520
Aaron Don M. Africa	33 0.3×	48 0.4×	76 0.7×	18 0.3×	33 0.7×	76	550
Rajesh Mahadeva	85 0.7×	101 0.9×	157 1.4×	16 0.2×	44 1.0×	59	520
Mengjun Li	131 1.0×	38 0.3×	37 0.3×	42 0.6×	10 0.2×	21	586
Xiaolin Liu	60 0.5×	24 0.2×	36 0.3×	17 0.3×	49 1.1×	52	473
Wen‐Shyong Hsieh	237 1.9×	53 0.5×	54 0.5×	40 0.6×	24 0.5×	57	484
Md. Mahmodul Hasan	104 0.8×	103 0.9×	20 0.2×	29 0.4×	74 1.6×	17	565
Tamás Varga	104 0.8×	59 0.5×	14 0.1×	23 0.3×	124 2.7×	69	518

Countries citing papers authored by John W. V. Miller

Since Specialization

Citations

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

Fields of papers citing papers by John W. V. Miller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John W. V. Miller. 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 John W. V. Miller. The network helps show where John W. V. Miller may publish in the future.

Co-authorship network of co-authors of John W. V. Miller

This figure shows the co-authorship network connecting the top 25 collaborators of John W. V. Miller. A scholar is included among the top collaborators of John W. V. Miller 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 John W. V. Miller. John W. V. Miller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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