Mohit Dua

2.7k citations
143 papers · 2.0k · h-index 27

Impact in

Papers in

Mohit Dua

132 papers receiving 1.9k citations

Peers

Mohit Dua
Comparison fields: 5 of 103
  • Signal Processing 701
  • Computer Vision and Pattern Recognition 799
  • Artificial Intelligence 1.0k
  • Experimental and Cognitive Psychology 146
  • Mathematical Physics 96
Replace Mourad Zaied with:
Mourad Zaied Tunisia
Stefano Berretti Italy
KokSheik Wong Malaysia
Ridha Ejbali Tunisia
Chokri Ben Amar Tunisia
Muhammad Ehatisham-ul-Haq Pakistan
Cüneyt Güzelіș Türkiye
Qiuqi Ruan China
C. Eswaran Malaysia
Ariadna Quattoni Spain
Mohit Dua relative to Mourad Zaied Tunisia Mourad Zaied's profile →
Citations per field
00.5×2×3×4.2×
Mourad Zaied · 1×
Citations per year

Countries citing papers authored by Mohit Dua

Since Specialization
Citations

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

Fields of papers citing papers by Mohit Dua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 143 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020149
2
Punjabi Automatic Speech Recognition Using HTK
201277
3 202070
4 201849
5 201947
6 201844
7 202143
8 201843
9 201940
10 201937
11 202037
12 201937
13 202336
14 202033
15 202132
16 201732
17 202331
18 202130
19 202130
20 202329

About Mohit Dua

Mohit Dua is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computational Theory and Mathematics and Mathematical Physics, having authored 143 papers that have together received 2.0k indexed citations. Recurring topics across this work include Speech and Audio Processing (52 papers), Speech Recognition and Synthesis (50 papers), Music and Audio Processing (47 papers), Chaos-based Image/Signal Encryption (38 papers), Advanced Steganography and Watermarking Techniques (24 papers), Cellular Automata and Applications (12 papers), Natural Language Processing Techniques (10 papers) and Cryptographic Implementations and Security (10 papers). The work is most often cited by research in Signal Processing (701 citations), Computer Vision and Pattern Recognition (799 citations), Artificial Intelligence (1.0k citations), Experimental and Cognitive Psychology (146 citations) and Mathematical Physics (96 citations). Mohit Dua has collaborated with scholars based in India, United States and Australia. Frequent co-authors include Shelza Dua, Rajesh Kumar Aggarwal, Mantosh Biswas, Virender Kadyan, Ankita Bisht, Sushil Kumar, Rajender Kumar, Ankit Kumar Jain, Vaibhav Garg and Ankit Kumar. Their work appears in journals such as International Journal of Speech Technology, Multimedia Tools and Applications, Journal of Ambient Intelligence and Humanized Computing, Complex & Intelligent Systems and The Imaging Science Journal.

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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