Deepak Garg

152 papers receiving 1.5k citations

Deepak Garg's Hit Papers

Drone-surveillance for search and rescue in natural disaster 2020 · 265 citations
2650+2+4Years since publication50100150200250

Peers

Deepak Garg
Comparison fields: 5 of 130
  • Computer Vision and Pattern Recognition 403
  • Computer Networks and Communications 379
  • Artificial Intelligence 409
  • Aerospace Engineering 279
  • Information Systems 252
Replace Xiaoqiang Ma with:
Xiaoqiang Ma China
Zhigao Zheng China
Liang Hong China
Muhammad Asim Saudi Arabia
Lijun Qian United States
Chenquan Gan China
Mznah Al‐Rodhaan Saudi Arabia
Jian Wan China
Chang Choi South Korea
Deepak Garg relative to Xiaoqiang Ma China Xiaoqiang Ma's profile →
Citations per field
00.5×7.2×
Xiaoqiang Ma · 1×
Citations per year

Countries citing papers authored by Deepak Garg

Since Specialization
Citations

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

Fields of papers citing papers by Deepak Garg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 171 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Drone-surveillance for search and rescue in natural disaster
Hit paper breakdown →
2020265
2 202092
3 202455
4 202143
5 201942
6 201838
7 201737
8 200933
9 202433
10 202333
11 202129
12 202428
13 202228
14 202426
15 201126
16 202123
17 202321
18 202421
19 201421
20 201120

About Deepak Garg

Deepak Garg is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 171 papers that have together received 1.6k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (11 papers), Data Management and Algorithms (11 papers), Algorithms and Data Compression (10 papers), UAV Applications and Optimization (10 papers), Advanced Wireless Communication Technologies (8 papers), Rough Sets and Fuzzy Logic (8 papers), Image and Signal Denoising Methods (8 papers) and Web Data Mining and Analysis (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (403 citations), Computer Networks and Communications (379 citations), Artificial Intelligence (409 citations), Aerospace Engineering (279 citations) and Information Systems (252 citations). Deepak Garg has collaborated with scholars based in India, Saudi Arabia and United States. Frequent co-authors include Vipul Kumar Mishra, Pratik Narang, Balmukund Mishra, Ishan Budhiraja, Prakhar Consul, Anika Gupta, Neeraj Kumar, Frédéric Andrès, Gaurav Singal and Prabhishek Singh. Their work appears in journals such as Optical and Quantum Electronics, Alexandria Engineering Journal, Computer Communications, IEEE Transactions on Consumer Electronics and IEEE Internet of Things 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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