D. Sen

552 citations
24 papers · 411 · h-index 9

Impact in

Papers in

D. Sen

17 papers receiving 368 citations

Peers

D. Sen
Comparison fields: 5 of 42
  • Signal Processing 138
  • Computer Vision and Pattern Recognition 155
  • Materials Chemistry 212
  • Electrical and Electronic Engineering 221
  • Computational Mechanics 60
Replace Bhabesh Deka with:
Bhabesh Deka India
Chunxi Dong China
Ping Tan China
Xinyu Ma China
Pai Wang China
Xiaolong Yuan China
Xiefeng Cheng China
Jafar Ramadhan Mohammed Iraq
Long Ma China
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D. Sen relative to Bhabesh Deka India Bhabesh Deka's profile →
Citations per field
00.5×8.2×
Bhabesh Deka · 1×
Citations per year

Countries citing papers authored by D. Sen

Since Specialization
Citations

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

Fields of papers citing papers by D. Sen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside D. Sen, 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 D. Sen Line = papers co-authored together D. Sen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007184
2 200770
3 201053
4 200820
5 200218
6 199315
7 200811
8 20029
9
Functionality of cochlear micromechanics - As elucidated by upward spread of masking and two tone suppression
20068
10 20048
11 20094
12 19992
13 20092
14
Identification of Partials in Polyphonic Mixtures Based on Temporal Envelope Similarity
20071
15 20051
16 20031
17 20081
18
Efficient Compression and Transportation of Scene-Based Audio for Television Broadcast
20161
19 20031
20 20091

About D. Sen

D. Sen is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Computational Mechanics, Cognitive Neuroscience and Biomedical Engineering, having authored 24 papers that have together received 411 indexed citations. Recurring topics across this work include Speech and Audio Processing (12 papers), Advanced Data Compression Techniques (8 papers), Advanced Adaptive Filtering Techniques (6 papers), Image and Signal Denoising Methods (5 papers), Hearing Loss and Rehabilitation (5 papers), Acoustic Wave Phenomena Research (3 papers), Structural Health Monitoring Techniques (2 papers) and Music and Audio Processing (2 papers). The work is most often cited by research in Signal Processing (138 citations), Computer Vision and Pattern Recognition (155 citations), Materials Chemistry (212 citations), Electrical and Electronic Engineering (221 citations) and Computational Mechanics (60 citations). D. Sen has collaborated with scholars based in Australia, United States and Malaysia. Frequent co-authors include B.T. Phung, T.R. Blackburn, David Gunawan, W.H. Holmes, Y. Shoham, Sisi Wang, W. Bastiaan Kleijn, Jont B. Allen, R. Hagen and David Clark. Their work appears in journals such as IEEE Transactions on Dielectrics and Electrical Insulation, IEEE Transactions on Applied Superconductivity, The Journal of the Acoustical Society of America, Journal of the Audio Engineering Society and IEEE Signal Processing Letters.

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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