K. Pradeep

927 citations
44 papers · 555 · h-index 12

Impact in

Papers in

K. Pradeep

38 papers receiving 529 citations

Peers

K. Pradeep
Comparison fields: 5 of 56
  • Computer Networks and Communications 404
  • Information Systems 376
  • Artificial Intelligence 128
  • Signal Processing 37
  • Neurology 20
Replace Wenbin Yao with:
Wenbin Yao China
Abhishek Raghuvanshi India
Amir El-Ghamry Egypt
Dinesh Kumar Anguraj India
R.C. Suganthe India
Leyi Shi China
Ahmed Abdulhakim Al-Absi South Korea
Ganesh Reddy Karri India
Amit Kumar Bairwa India
Muhammad Shahid Saeed China
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Citations per field
00.5×3.3×
Wenbin Yao · 1×
Citations per year

Countries citing papers authored by K. Pradeep

Since Specialization
Citations

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

Fields of papers citing papers by K. Pradeep

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside K. Pradeep, 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 K. Pradeep Line = papers co-authored together K. Pradeep links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201987
2 202272
3 201853
4 202352
5 202040
6 202140
7 201735
8 202327
9 202425
10 201819
11 202417
12 202114
13 20238
14 20228
15 20168
16 20226
17 20226
18 20225
19 20224
20 20214

About K. Pradeep

K. Pradeep is a scholar working on Information Systems, Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition and Plant Science, having authored 44 papers that have together received 555 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (25 papers), IoT and Edge/Fog Computing (24 papers), Distributed and Parallel Computing Systems (10 papers), Internet of Things and AI (4 papers), Metaheuristic Optimization Algorithms Research (4 papers), Advanced Neural Network Applications (3 papers), Smart Agriculture and AI (3 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Computer Networks and Communications (404 citations), Information Systems (376 citations), Artificial Intelligence (128 citations), Signal Processing (37 citations) and Neurology (20 citations). K. Pradeep has collaborated with scholars based in India, United States and Australia. Frequent co-authors include T. Prem Jacob, N. Manikandan, A. Balasundaram, Chandrasekharan Raman, Manas Ranjan Prusty, Palani Thanaraj Krishnan, T. Sunil Kumar, K. P. Vijayakumar, K.P. Vijayakumar and R Surendran. Their work appears in journals such as Computers, materials & continua/Computers, materials & continua (Print), Wireless Personal Communications, Computer Communications, Agronomy Journal and Applied Sciences.

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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