Ramesh R. Manza

125 total papers · 861 total citations
64 papers, 493 citations indexed

About

Ramesh R. Manza is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Signal Processing. According to data from OpenAlex, Ramesh R. Manza has authored 64 papers receiving a total of 493 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Computer Vision and Pattern Recognition, 23 papers in Radiology, Nuclear Medicine and Imaging and 12 papers in Signal Processing. Recurrent topics in Ramesh R. Manza's work include Retinal Imaging and Analysis (17 papers), Digital Imaging for Blood Diseases (11 papers) and Artificial Intelligence in Healthcare (8 papers). Ramesh R. Manza is often cited by papers focused on Retinal Imaging and Analysis (17 papers), Digital Imaging for Blood Diseases (11 papers) and Artificial Intelligence in Healthcare (8 papers). Ramesh R. Manza collaborates with scholars based in India, United States and China. Ramesh R. Manza's co-authors include R. J. Ramteke, Pravin Yannawar, Mukti E. Jadhav, K. V. Kale, S. C. Mehrotra, Rajesh K. Dhumal, Amol D. Vibhute, Bharti W. Gawali, Nazneen Akhter and Ratnadeep R. Deshmukh and has published in prestigious journals such as Mathematics, Indian Journal of Science and Technology and International Journal of Speech Technology.

In The Last Decade

Ramesh R. Manza

55 papers receiving 452 citations

Author Peers

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

Author Last Decade Papers Cites
Ramesh R. Manza 158 126 69 69 68 64 493
Handayani Tjandrasa 197 1.2× 232 1.8× 102 1.5× 102 1.5× 17 0.3× 75 524
Muhammad Shehzad Hanif 337 2.1× 97 0.8× 40 0.6× 66 1.0× 15 0.2× 30 493
Xin Xiong 192 1.2× 47 0.4× 17 0.2× 98 1.4× 14 0.2× 46 525
Evandro Ottoni Teatini Salles 217 1.4× 238 1.9× 142 2.1× 121 1.8× 21 0.3× 59 549
Mohamed K. Nour 144 0.9× 97 0.8× 9 0.1× 197 2.9× 29 0.4× 65 550
Younhyun Jung 255 1.6× 116 0.9× 33 0.5× 89 1.3× 10 0.1× 46 504
Ahmed Atwan 177 1.1× 156 1.2× 60 0.9× 105 1.5× 41 0.6× 42 487
Muyi Sun 220 1.4× 185 1.5× 73 1.1× 106 1.5× 9 0.1× 37 540
Ahmad Shaf 190 1.2× 113 0.9× 26 0.4× 120 1.7× 19 0.3× 41 533
Wei Jin 252 1.6× 107 0.8× 53 0.8× 39 0.6× 21 0.3× 64 530

Countries citing papers authored by Ramesh R. Manza

Since Specialization
Citations

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

Fields of papers citing papers by Ramesh R. Manza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ramesh R. Manza. 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 Ramesh R. Manza. The network helps show where Ramesh R. Manza may publish in the future.

Co-authorship network of co-authors of Ramesh R. Manza

This figure shows the co-authorship network connecting the top 25 collaborators of Ramesh R. Manza. A scholar is included among the top collaborators of Ramesh R. Manza 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 Ramesh R. Manza. Ramesh R. Manza 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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