Achintya Das

1.1k citations
36 papers · 433 · h-index 12

Impact in

Papers in

Achintya Das

33 papers receiving 408 citations

Peers

Achintya Das
Comparison fields: 5 of 69
  • Computer Vision and Pattern Recognition 219
  • Signal Processing 65
  • Media Technology 48
  • Computer Graphics and Computer-Aided Design 9
  • Artificial Intelligence 61
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Citations per year

Countries citing papers authored by Achintya Das

Since Specialization
Citations

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

Fields of papers citing papers by Achintya Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Achintya Das, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Achintya Das Line = papers co-authored together Achintya Das links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201362
2 201457
3 201239
4 201237
5 201226
6 201221
7 201218
8 201116
9 201214
10 200513
11 201412
12 201212
13 201511
14 201210
15
Analysis of a Nature Inspired Firefly Algorithm based Back-propagation Neural Network Training
201210
16 201210
17 20169
18
SIMULATION ASPECT OF AN ARTIFICIAL PACEMAKER
20108
19 20137
20 20157

About Achintya Das

Achintya Das is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Control and Systems Engineering and Radiology, Nuclear Medicine and Imaging, having authored 36 papers that have together received 433 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (12 papers), Digital Media Forensic Detection (6 papers), Retinal Imaging and Analysis (4 papers), Chaos-based Image/Signal Encryption (4 papers), Neural Networks and Applications (3 papers), Metaheuristic Optimization Algorithms Research (3 papers), Industrial Automation and Control Systems (3 papers) and Wireless Body Area Networks (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (219 citations), Signal Processing (65 citations), Media Technology (48 citations), Computer Graphics and Computer-Aided Design (9 citations) and Artificial Intelligence (61 citations). Achintya Das has collaborated with scholars based in India, Italy and United Kingdom. Frequent co-authors include Nilanjan Dey, Sheli Sinha Chaudhuri, Sourav Samanta, Xin‐She Yang, Poulami Das, Sayan Chakraborty, Jasjit S. Suri, Sudarshan Nandy, Partha Sarkar and Biswarup Rana. Their work appears in journals such as Reproduction in Domestic Animals, ISIJ International, International Journal of Bio-Inspired Computation, Ultrasound in Medicine & Biology and Journal of Medical Systems.

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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