Tajuddin Manhar Mohammed
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Signal Processing
- Computer Networks and Communications
- Information Systems
- Co-authors
- Lakshmanan NatarajB.S. ManjunathShivkumar ChandrasekaranArjuna FlennerAmit K. Roy–ChowdhuryJawadul H. BappyMichael GoebelB. S. Manjunath
- Topics
- Digital Media Forensic Detection (4 papers)Generative Adversarial Networks and Image Synthesis (2 papers)Anomaly Detection Techniques and Applications (2 papers)
- Journals
- Proceedings of the ... Annual Hawaii International Conference on System SciencesElectronic Imaging
- Partner nations
- United States
In The Last Decade
Tajuddin Manhar Mohammed
6 papers receiving 214 citations
Peers
Comparison fields: 5 of 32
- Computer Vision and Pattern Recognition 183
- Artificial Intelligence 63
- Signal Processing 43
- Computer Networks and Communications 24
- Information Systems 18
Countries citing papers authored by Tajuddin Manhar Mohammed
This map shows the geographic impact of Tajuddin Manhar Mohammed'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 Tajuddin Manhar Mohammed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tajuddin Manhar Mohammed more than expected).
Fields of papers citing papers by Tajuddin Manhar Mohammed
This network shows the impact of papers produced by Tajuddin Manhar Mohammed. 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 Tajuddin Manhar Mohammed. The network helps show where Tajuddin Manhar Mohammed may publish in the future.
Co-authorship network of co-authors of Tajuddin Manhar Mohammed
This figure shows the co-authorship network connecting the top 25 collaborators of Tajuddin Manhar Mohammed. A scholar is included among the top collaborators of Tajuddin Manhar Mohammed 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 Tajuddin Manhar Mohammed. Tajuddin Manhar Mohammed is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 21 | |
| 3 | 16 | |
| 4 | 2 | |
| 5 | 170 | |
| 6 | 13 |
About Tajuddin Manhar Mohammed
Tajuddin Manhar Mohammed is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Biophysics, having authored 6 papers that have together received 229 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (4 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (183 citations), Signal Processing (43 citations) and Artificial Intelligence (63 citations). Tajuddin Manhar Mohammed has collaborated with scholars based in United States. Frequent co-authors include Lakshmanan Nataraj, B.S. Manjunath, Shivkumar Chandrasekaran, Arjuna Flenner, Amit K. Roy–Chowdhury, Jawadul H. Bappy, Michael Goebel and B. S. Manjunath. Their work appears in journals such as Proceedings of the ... Annual Hawaii International Conference on System Sciences and Electronic Imaging.
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.