Mukesh Prasad

8.2k citations
201 papers · 5.2k indexed · 3 hit papers · h-index 31

Impact in

Papers in

Mukesh Prasad

187 papers receiving 5.0k citations

Hit Papers

Edge of Things: The Big Picture on the Integration of Edge, IoT and the Cloud in a Distributed Computing Environment 2017 · 279 citations
2792016202620192022250500750

Peers

Mukesh Prasad
Comparison fields: 5 of 189
  • Computer Vision and Pattern Recognition 1.1k
  • Computer Networks and Communications 1.1k
  • Artificial Intelligence 1.3k
  • Health Informatics 47
  • Media Technology 298
Replace Nebojša Bačanin with:
Nebojša Bačanin Serbia
Zhikui Chen China
Md. Jalil Piran South Korea
Wadii Boulila Saudi Arabia
Marcin Woźniak Poland
Saurabh Singh South Korea
Anand Nayyar Vietnam
Mehedi Masud Saudi Arabia
Lê Hoàng Sơn Vietnam
Chinmay Chakraborty India
Mukesh Prasad relative to Nebojša Bačanin Serbia Nebojša Bačanin's profile →
Citations per field
00.5×1.5×2.1×
Nebojša Bačanin · 1×
Citations per year

Countries citing papers authored by Mukesh Prasad

Since Specialization
Citations

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

Fields of papers citing papers by Mukesh Prasad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20250
4 20246
5 20245
6 202410
7 20232
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10 202344
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14 202340
15 20230
16 20217
17 2021143
18 201928
19
Tensor decomposition for EEG signals retrieval
20191
20 201763

About Mukesh Prasad

Mukesh Prasad is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mathematics, Signal Processing and Information Systems, having authored 201 papers that have together received 5.2k indexed citations. Recurring topics across this work include Face and Expression Recognition (24 papers), IoT and Edge/Fog Computing (14 papers), Neural Networks and Applications (14 papers), EEG and Brain-Computer Interfaces (14 papers), Video Surveillance and Tracking Methods (13 papers), Advanced Image and Video Retrieval Techniques (13 papers), Fuzzy Logic and Control Systems (11 papers) and Advanced Neural Network Applications (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Computer Networks and Communications (1.1k citations), Artificial Intelligence (1.3k citations), Health Informatics (47 citations) and Media Technology (298 citations). Mukesh Prasad has collaborated with scholars based in Australia, India and Taiwan. Frequent co-authors include Chin‐Teng Lin, Akshansh Gupta, Weiping Ding, Om Prakash Patel, Deepak Puthal, Aruna Tiwari, Omprakash Kaiwartya, Meng Joo Er, Amit Saxena and Neha Bharill. Their work appears in journals such as IEEE Access, Electronics, Sustainability, Neurocomputing and Neural Computing and Applications.

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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