Arpita Das

133 total papers · 853 total citations
79 papers, 543 citations indexed

About

Arpita Das is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Arpita Das has authored 79 papers receiving a total of 543 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 15 papers in Media Technology. Recurrent topics in Arpita Das's work include AI in cancer detection (14 papers), Advanced Image Fusion Techniques (12 papers) and Image and Signal Denoising Methods (10 papers). Arpita Das is often cited by papers focused on AI in cancer detection (14 papers), Advanced Image Fusion Techniques (12 papers) and Image and Signal Denoising Methods (10 papers). Arpita Das collaborates with scholars based in India, Bangladesh and United States. Arpita Das's co-authors include Mahua Bhattacharya, Manish Kumar Jain, Madhuri Mandal Goswami, Anirban Bhattacharyya, Ajay Ghosh, Rajesh Kumar Tripathy, Aritra Banerjee, Priyanka Upadhyay, Arghya Adhikary and Ashavani Kumar and has published in prestigious journals such as Polymer, Expert Systems with Applications and Pattern Recognition.

In The Last Decade

Arpita Das

72 papers receiving 506 citations

Author Peers

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

Author						Papers	Cites
Arpita Das	143	102	88	87	74	79	543
Mingxin Yu	65 0.5×	46 0.5×	47 0.5×	60 0.7×	120 1.6×	55	506
Mohammad Salman	86 0.6×	73 0.7×	48 0.5×	17 0.2×	111 1.5×	75	555
Emmanuel Okafor	108 0.8×	99 1.0×	49 0.6×	70 0.8×	73 1.0×	36	519
Yutao Yue	109 0.8×	50 0.5×	88 1.0×	24 0.3×	93 1.3×	53	455
Ali Haider Khan	42 0.3×	150 1.5×	57 0.6×	37 0.4×	35 0.5×	48	544
Jianhang Zhou	113 0.8×	92 0.9×	87 1.0×	11 0.1×	60 0.8×	54	484
Wu Lu	49 0.3×	36 0.4×	66 0.8×	208 2.4×	352 4.8×	61	617
Zhihua Xie	102 0.7×	28 0.3×	316 3.6×	63 0.7×	48 0.6×	60	587
Lei Su	44 0.3×	107 1.0×	96 1.1×	39 0.4×	179 2.4×	77	516
Ming Yuchi	115 0.8×	64 0.6×	232 2.6×	42 0.5×	24 0.3×	89	538

Countries citing papers authored by Arpita Das

Since Specialization

Citations

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

Fields of papers citing papers by Arpita Das

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arpita Das

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

All Works

Loading papers...

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.

Explore authors with similar magnitude of impact