Payal Mittal

604 citations
23 papers · 369 indexed · 1 hit paper · h-index 7
Topics
Advanced Neural Network Applications (6 papers)Electromagnetic Fields and Biological Effects (4 papers)Video Surveillance and Tracking Methods (4 papers)
Journals
SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsImage and Vision Computing

In The Last Decade

Payal Mittal

22 papers receiving 355 citations

Hit Papers

Deep learning-based object detection in low-altitude UAV ...2020202620222024202050100150200

Peers

Payal Mittal
Comparison fields: 5 of 89
  • Computer Vision and Pattern Recognition 216
  • Aerospace Engineering 129
  • Artificial Intelligence 41
  • Environmental Engineering 31
  • Media Technology 29
Replace Nima Razavi with:
Nima Razavi Switzerland
Fatih Çağatay Akyön Türkiye
Chunjiang Ge China
Roman Solovyev Russia
Tao Gong China
Ali Hassani United States
Shaharyar Ahmed Khan Tareen Pakistan
Kwang-Seok Moon South Korea
Qiaosong Wang United States
Payal Mittal relative to Nima Razavi Switzerland Nima Razavi's profile →
Citations per field
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Countries citing papers authored by Payal Mittal

Since Specialization
Citations

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

Fields of papers citing papers by Payal Mittal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Payal Mittal

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 5
2 2
3 4
4 42
5 3
6 13
7 2
8 8
9 2
10 1
11 6
12
Deep learning-based object detection in low-altitude UAV datasets: A surveybreakdown →
225
13 6
14 0
15 2
16 4
17
A Survey on OFDM and IEEE WLAN Standard
1
18 2
19 1
20 3

About Payal Mittal

Payal Mittal is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Media Technology, having authored 23 papers that have together received 369 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (6 papers), Electromagnetic Fields and Biological Effects (4 papers) and Video Surveillance and Tracking Methods (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (216 citations), Aerospace Engineering (129 citations) and Media Technology (29 citations). Payal Mittal has collaborated with scholars based in India, United Kingdom and United Arab Emirates. Frequent co-authors include Akashdeep Sharma, Raman Singh, Satnam Singh, K.L. Khanduja, Mukesh Dalal, Arun Kumar Sangaiah, Bhisham Sharma, Mohammad S. Obaidat, Abhishek Singhal and Nitish Kumar. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Image and Vision Computing.

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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