Tirtharaj Dash

954 citations
35 papers · 481 · h-index 12

Impact in

Papers in

Tirtharaj Dash

33 papers receiving 464 citations

Peers

Tirtharaj Dash
Comparison fields: 5 of 100
  • Computer Networks and Communications 190
  • Artificial Intelligence 210
  • Signal Processing 42
  • Health Informatics 4
  • Computer Vision and Pattern Recognition 57
Replace Noha A. Hikal with:
Noha A. Hikal Egypt
Saiful Azad Malaysia
Bhabani Shankar Prasad Mishra India
Zhaohui Cai China
Mahua Bhattacharya India
Radwa Marzouk Saudi Arabia
Roobaea Alroobaea Saudi Arabia
Basem M. ElHalawany Egypt
Amang Sudarsono Indonesia
Ghodrat Sepidnam Iran
Tirtharaj Dash relative to Noha A. Hikal Egypt Noha A. Hikal's profile →
Citations per field
00.5×8.7×
Noha A. Hikal · 1×
Citations per year

Countries citing papers authored by Tirtharaj Dash

Since Specialization
Citations

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

Fields of papers citing papers by Tirtharaj Dash

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Tirtharaj Dash, 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 Tirtharaj Dash Line = papers co-authored together Tirtharaj Dash links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022107
2 201573
3 201843
4 201929
5 201823
6 201720
7 201820
8 202119
9 202219
10 201513
11 201513
12 202112
13 201410
14 20237
15 20217
16 20166
17 20236
18
Handwritten Signature Verification (Offline) using Neural Network Approaches: A Comparative Study
20126
19 20156
20 20245

About Tirtharaj Dash

Tirtharaj Dash is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing and Molecular Biology, having authored 35 papers that have together received 481 indexed citations. Recurring topics across this work include Energy Efficient Wireless Sensor Networks (7 papers), Neural Networks and Applications (4 papers), Anomaly Detection Techniques and Applications (3 papers), Handwritten Text Recognition Techniques (3 papers), Water Quality Monitoring Technologies (3 papers), Topic Modeling (3 papers), Security in Wireless Sensor Networks (3 papers) and Fuzzy Logic and Control Systems (3 papers). The work is most often cited by research in Computer Networks and Communications (190 citations), Artificial Intelligence (210 citations), Signal Processing (42 citations), Health Informatics (4 citations) and Computer Vision and Pattern Recognition (57 citations). Tirtharaj Dash has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Rakesh Ranjan Swain, Pabitra Mohan Khilar, Ashwin Srinivasan, Lovekesh Vig, Ross D. King, Iván Olier, Oghenejokpeme I. Orhobor, Andy Davis, Larisa Soldatova and Joaquin Vanschoren. Their work appears in journals such as Machine Learning, Wireless Personal Communications, Ad Hoc Networks, Journal of Computational Chemistry and CAAI Transactions on Intelligence Technology.

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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