G. Ravindran

51 total papers · 485 total citations
40 papers, 358 citations indexed

About

G. Ravindran is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, G. Ravindran has authored 40 papers receiving a total of 358 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 13 papers in Radiology, Nuclear Medicine and Imaging and 11 papers in Artificial Intelligence. Recurrent topics in G. Ravindran's work include Medical Image Segmentation Techniques (16 papers), AI in cancer detection (11 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). G. Ravindran is often cited by papers focused on Medical Image Segmentation Techniques (16 papers), AI in cancer detection (11 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). G. Ravindran collaborates with scholars based in India. G. Ravindran's co-authors include S. Poonguzhali, R. Sivakumar, S. Lakshminarayanan, P. Pandiyan, Sumathi Poobal, Krishnan Ganapathy, R. Tamilselvi, Gurinder Mohan, Praveen Ravishankaran and T. Parthasarathy and has published in prestigious journals such as SHILAP Revista de lepidopterología, BioMed Research International and Journal of Clinical Neuroscience.

In The Last Decade

G. Ravindran

29 papers receiving 290 citations

Author Peers

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

Author						Papers	Cites
G. Ravindran	139	111	102	39	33	40	358
Maleika Heenaye-Mamode Khan	70 0.5×	130 1.2×	123 1.2×	21 0.5×	14 0.4×	43	341
Patrick Then	96 0.7×	68 0.6×	74 0.7×	15 0.4×	36 1.1×	65	378
Tina Babu	61 0.4×	133 1.2×	77 0.8×	20 0.5×	10 0.3×	79	337
Tapabrata Chakraborti	126 0.9×	103 0.9×	107 1.0×	19 0.5×	18 0.5×	33	341
Hammad Majeed	120 0.9×	160 1.4×	24 0.2×	30 0.8×	21 0.6×	27	347
Serkan Savaş	54 0.4×	104 0.9×	56 0.5×	13 0.3×	19 0.6×	37	358
Aruna Bhat	93 0.7×	115 1.0×	32 0.3×	22 0.6×	9 0.3×	71	337
Kun Lan	52 0.4×	117 1.1×	77 0.8×	14 0.4×	65 2.0×	30	366
Poonam Saini	84 0.6×	51 0.5×	111 1.1×	11 0.3×	17 0.5×	39	357
Giovanna Maria Dimitri	50 0.4×	91 0.8×	33 0.3×	14 0.4×	81 2.5×	42	365

Countries citing papers authored by G. Ravindran

Since Specialization

Citations

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

Fields of papers citing papers by G. Ravindran

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Ravindran

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