G. Madhu

45 total papers · 615 total citations
27 papers, 356 citations indexed

About

G. Madhu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, G. Madhu has authored 27 papers receiving a total of 356 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 6 papers in Information Systems. Recurrent topics in G. Madhu's work include Digital Imaging for Blood Diseases (8 papers), Smart Agriculture and AI (4 papers) and COVID-19 diagnosis using AI (4 papers). G. Madhu is often cited by papers focused on Digital Imaging for Blood Diseases (8 papers), Smart Agriculture and AI (4 papers) and COVID-19 diagnosis using AI (4 papers). G. Madhu collaborates with scholars based in India, Saudi Arabia and Egypt. G. Madhu's co-authors include A. Govardhan, V. Lakshmana Gomathi Nayagam, V. R. Renjith, Sandeep Kautish, T. V. Rajinikanth, Ali Wagdy Mohamed, Manoj Kumar, Irfan Ali, B. Srinivas and Mohd Asif Shah and has published in prestigious journals such as Journal of Hazardous Materials, Scientific Reports and Sensors.

In The Last Decade

G. Madhu

24 papers receiving 329 citations

Author Peers

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

Author						Papers	Cites
G. Madhu	153	82	63	60	36	27	356
Talayeh Razzaghi	142 0.9×	18 0.2×	74 1.2×	41 0.7×	3 0.1×	24	357
Danielle Azar	105 0.7×	120 1.5×	10 0.2×	27 0.5×	10 0.3×	32	383
Supriya Raheja	79 0.5×	55 0.7×	9 0.1×	25 0.4×	4 0.1×	40	325
Andrés R. Masegosa	271 1.8×	70 0.9×	28 0.4×	16 0.3×	5 0.1×	24	381
Ramin Ramezani	118 0.8×	52 0.6×	9 0.1×	112 1.9×	7 0.2×	33	388
Lianmeng Jiao	255 1.7×	75 0.9×	21 0.3×	69 1.1×	4 0.1×	39	375
Hossein Karshenas	245 1.6×	29 0.4×	22 0.3×	52 0.9×	2 0.1×	25	392
Anwar Hussain	73 0.5×	47 0.6×	14 0.2×	74 1.2×	3 0.1×	30	397
Nicandro Cruz-Ramírez	215 1.4×	31 0.4×	7 0.1×	39 0.7×	3 0.1×	38	371
Raed Al Kontar	146 1.0×	11 0.1×	50 0.8×	12 0.2×	7 0.2×	41	362

Countries citing papers authored by G. Madhu

Since Specialization

Citations

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

Fields of papers citing papers by G. Madhu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

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