Shaikh Muhammad Allayear
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Neurology
- Signal Processing
- Computer Networks and Communications
- Co-authors
- Sandeep Kumar MathivananV E SathishkumarVipin KumarPrabhu JayagopalS. VelliangiriMohammad Salah UddinM. PrasannaS Sangeetha
- Topics
- Graph Theory and Algorithms (2 papers)AI in cancer detection (2 papers)Cloud Computing and Resource Management (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaComputational Intelligence and NeuroscienceMathematical Problems in Engineering
- Partner nations
- BangladeshIndiaSouth Korea
In The Last Decade
Shaikh Muhammad Allayear
13 papers receiving 135 citations
Peers
Comparison fields: 5 of 63
- Artificial Intelligence 42
- Computer Vision and Pattern Recognition 36
- Neurology 26
- Signal Processing 23
- Computer Networks and Communications 22
Countries citing papers authored by Shaikh Muhammad Allayear
This map shows the geographic impact of Shaikh Muhammad Allayear'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 Shaikh Muhammad Allayear with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaikh Muhammad Allayear more than expected).
Fields of papers citing papers by Shaikh Muhammad Allayear
This network shows the impact of papers produced by Shaikh Muhammad Allayear. 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 Shaikh Muhammad Allayear. The network helps show where Shaikh Muhammad Allayear may publish in the future.
Co-authorship network of co-authors of Shaikh Muhammad Allayear
This figure shows the co-authorship network connecting the top 25 collaborators of Shaikh Muhammad Allayear. A scholar is included among the top collaborators of Shaikh Muhammad Allayear 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 Shaikh Muhammad Allayear. Shaikh Muhammad Allayear is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 20 | |
| 3 | 35 | |
| 4 | 7 | |
| 5 | 9 | |
| 6 | 11 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | A Fuzzy TOPSIS Approach for Big Data Analytics Platform Selection | 2 |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 3 | |
| 13 | 19 | |
| 14 | 11 | |
| 15 | 16 | |
| 16 | iSCSI protocol adaptation with 2-way TCP Hand Shake mechanism for an embedded multi-agent based health care system | 0 |
| 17 | 0 | |
| 18 | 0 |
About Shaikh Muhammad Allayear
Shaikh Muhammad Allayear is a scholar working on Hardware and Architecture, Conservation and Signal Processing, having authored 18 papers that have together received 140 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (2 papers), AI in cancer detection (2 papers) and Cloud Computing and Resource Management (2 papers). The work is most often cited by research in Neurology (26 citations), Health Informatics (3 citations) and Signal Processing (23 citations). Shaikh Muhammad Allayear has collaborated with scholars based in Bangladesh, India and South Korea. Frequent co-authors include Sandeep Kumar Mathivanan, V E Sathishkumar, Vipin Kumar, Prabhu Jayagopal, S. Velliangiri, Mohammad Salah Uddin, M. Prasanna, S Sangeetha, Parasuraman Karthikeyan and Md Nasir Uddin. Their work appears in journals such as SHILAP Revista de lepidopterología, Computational Intelligence and Neuroscience and Mathematical Problems in Engineering.
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.