P. W. C. Prasad
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- Augmented Reality Applications 27
- Chaos-based Image/Signal Encryption 10
- Neurology top 5%
- Human-Computer Interaction top 2%
- Artificial Intelligence top 2%
- AI in cancer detection 14
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- Formal Methods in Verification 19
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- Surgical Simulation and Training 17
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- VLSI and Analog Circuit Testing 14
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- Radiomics and Machine Learning in Medical Imaging 12
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- IoT and Edge/Fog Computing 9
- Co-authors
- Abeer AlsadoonAmr ElchouemiAshutosh Kumar SinghAngelika MaagOmar Hisham AlsadoonDedong YangSiong Hoe LauAzam Beg
- Journals
- SHILAP Revista de lepidopterología (2 papers)Expert Systems with Applications (1 paper)Computers & Education (1 paper)
- Partner nations
- AustraliaUnited StatesIraq
In The Last Decade
P. W. C. Prasad
180 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 153
- Computer Science Applications 173
- Computer Vision and Pattern Recognition 590
- Neurology 217
- Human-Computer Interaction 142
- Artificial Intelligence 625
Countries citing papers authored by P. W. C. Prasad
This map shows the geographic impact of P. W. C. 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 P. W. C. Prasad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P. W. C. Prasad more than expected).
Fields of papers citing papers by P. W. C. Prasad
This network shows the impact of papers produced by P. W. C. 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 P. W. C. Prasad. The network helps show where P. W. C. Prasad may publish in the future.
Co-authorship network
The 25 scholars most cited alongside P. W. C. Prasad, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 2 | |
| 2 | 2021 | 0 | |
| 3 | 2021 | 4 | |
| 4 | 2021 | 2 | |
| 5 | 2020 | 1 | |
| 6 | 2020 | 2 | |
| 7 | 2020 | 3 | |
| 8 | Point-of-interest (POI) recommender systems for social groups in location based social networks (LBSNs): Proposition of an improved model | 2020 | 2 |
| 9 | 2020 | 1 | |
| 10 | 2019 | 195 | |
| 11 | 2019 | 2 | |
| 12 | 2019 | 8 | |
| 13 | 2019 | 6 | |
| 14 | 2018 | 45 | |
| 15 | 2018 | 42 | |
| 16 | 2018 | 97 | |
| 17 | 2017 | 3 | |
| 18 | Complexity of XOR/XNOR Boolean Functions: A Model using Binary Decision Diagrams and Back Propagation Neural Networks | 2007 | 1 |
| 19 | Binary decision diagrams: a mathematical model for the path-related objective functions | 2006 | 0 |
| 20 | Effect of Boolean Min-terms on the Complexity of ROBDDs. | 2004 | 1 |
About P. W. C. Prasad
P. W. C. Prasad is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Software, having authored 196 papers that have together received 2.3k indexed citations. Recurring topics across this work include Augmented Reality Applications (27 papers), Formal Methods in Verification (19 papers), Surgical Simulation and Training (17 papers), VLSI and Analog Circuit Testing (14 papers), AI in cancer detection (14 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), Chaos-based Image/Signal Encryption (10 papers) and IoT and Edge/Fog Computing (9 papers). The work is most often cited by research in Computer Science Applications (173 citations), Computer Vision and Pattern Recognition (590 citations) and Neurology (217 citations). P. W. C. Prasad has collaborated with scholars based in Australia, United States and Iraq. Frequent co-authors include Abeer Alsadoon, Amr Elchouemi, Ashutosh Kumar Singh, Angelika Maag, Omar Hisham Alsadoon, Dedong Yang, Siong Hoe Lau, Azam Beg, Manoranjan Paul and Tarik A. Rashid. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Computers & Education.
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.