Suphakant Phimoltares

67 total papers · 626 total citations
51 papers, 418 citations indexed

About

Suphakant Phimoltares is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Suphakant Phimoltares has authored 51 papers receiving a total of 418 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 11 papers in Signal Processing. Recurrent topics in Suphakant Phimoltares's work include Biometric Identification and Security (8 papers), Face and Expression Recognition (7 papers) and Data Stream Mining Techniques (6 papers). Suphakant Phimoltares is often cited by papers focused on Biometric Identification and Security (8 papers), Face and Expression Recognition (7 papers) and Data Stream Mining Techniques (6 papers). Suphakant Phimoltares collaborates with scholars based in Thailand and China. Suphakant Phimoltares's co-authors include Chidchanok Lursinsap, Nagul Cooharojananone, Kosin Chamnongthai, Saichon Jaiyen, Aran Hansuebsai, Suthat Fucharoen and Sissades Tongsima and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and IEEE Access.

In The Last Decade

Suphakant Phimoltares

45 papers receiving 384 citations

Author Peers

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

Author						Papers	Cites
Suphakant Phimoltares	145	132	89	64	38	51	418
Ala Saleh Alluhaidan	117 0.8×	84 0.6×	76 0.9×	72 1.1×	25 0.7×	66	487
I. Jeena Jacob	137 0.9×	180 1.4×	75 0.8×	43 0.7×	14 0.4×	38	495
Abdolhossein Sarrafzadeh	144 1.0×	103 0.8×	69 0.8×	67 1.0×	52 1.4×	48	407
Hela Ltifi	147 1.0×	142 1.1×	38 0.4×	37 0.6×	9 0.2×	61	407
Madhushi Verma	100 0.7×	94 0.7×	41 0.5×	39 0.6×	34 0.9×	39	434
Intan Nurma Yulita	101 0.7×	52 0.4×	73 0.8×	29 0.5×	14 0.4×	76	394
Sameh A. Salem	95 0.7×	102 0.8×	99 1.1×	27 0.4×	35 0.9×	53	424
Sanjeev Sharma	119 0.8×	218 1.7×	63 0.7×	49 0.8×	18 0.5×	63	467
Mohammed Hadwan	173 1.2×	54 0.4×	58 0.7×	24 0.4×	39 1.0×	36	486
Rushit Dave	108 0.7×	157 1.2×	119 1.3×	84 1.3×	49 1.3×	30	385

Countries citing papers authored by Suphakant Phimoltares

Since Specialization

Citations

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

Fields of papers citing papers by Suphakant Phimoltares

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suphakant Phimoltares

This figure shows the co-authorship network connecting the top 25 collaborators of Suphakant Phimoltares. A scholar is included among the top collaborators of Suphakant Phimoltares 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 Suphakant Phimoltares. Suphakant Phimoltares 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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