M.T. Manry
Impact in
- Artificial Intelligence top 2%
- Neural Networks and Applications
- Machine Learning and ELM
- Signal Processing top 5%
- Blind Source Separation Techniques
Papers in
-
- Neural Networks and Applications 89
- Machine Learning and ELM 20
- Fuzzy Logic and Control Systems 16
-
- Face and Expression Recognition 25
- Image and Signal Denoising Methods 20
- Co-authors
- Kanishka Tyagi (18 shared papers)A.K. Fung (12 shared papers)M.-S. Chen (7 shared papers)Xun Cai (4 shared papers)Changhua Yu (9 shared papers)R. Nelson (1 shared paper)D. S. Kimes (1 shared paper)R.R. Shoults (2 shared papers)
- Journals
- Neurocomputing (8 papers)Neural Networks (4 papers)Neural Processing Letters (4 papers)Remote Sensing Reviews (3 papers)IEEE Transactions on Signal Processing (2 papers)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
M.T. Manry
127 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 134
- Artificial Intelligence 822
- Signal Processing 218
- Energy Engineering and Power Technology 57
- Computer Vision and Pattern Recognition 369
- Environmental Engineering 234
Countries citing papers authored by M.T. Manry
This map shows the geographic impact of M.T. Manry'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 M.T. Manry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.T. Manry more than expected).
Fields of papers citing papers by M.T. Manry
This network shows the impact of papers produced by M.T. Manry. 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 M.T. Manry. The network helps show where M.T. Manry may publish in the future.
Co-authors
The 25 scholars most cited alongside M.T. Manry, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 139 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 250 | |
| 2 | 1998 | 150 | |
| 3 | 1991 | 64 | |
| 4 | 1999 | 59 | |
| 5 | 1994 | 57 | |
| 6 | 2000 | 52 | |
| 7 | 2007 | 47 | |
| 8 | 1993 | 46 | |
| 9 | 1994 | 46 | |
| 10 | 1993 | 43 | |
| 11 | 2006 | 42 | |
| 12 | 2006 | 42 | |
| 13 | 1997 | 37 | |
| 14 | 2011 | 35 | |
| 15 | 2019 | 35 | |
| 16 | 2011 | 33 | |
| 17 | 2011 | 31 | |
| 18 | 2013 | 30 | |
| 19 | 2014 | 30 | |
| 20 | 2014 | 30 |
About M.T. Manry
M.T. Manry is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Control and Systems Engineering and Computational Mechanics, having authored 139 papers that have together received 2.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (89 papers), Blind Source Separation Techniques (39 papers), Face and Expression Recognition (25 papers), Machine Learning and ELM (20 papers), Image and Signal Denoising Methods (20 papers), Fuzzy Logic and Control Systems (16 papers), Control Systems and Identification (7 papers) and Advanced Adaptive Filtering Techniques (7 papers). The work is most often cited by research in Artificial Intelligence (822 citations), Signal Processing (218 citations), Energy Engineering and Power Technology (57 citations), Computer Vision and Pattern Recognition (369 citations) and Environmental Engineering (234 citations). M.T. Manry has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Kanishka Tyagi, A.K. Fung, M.-S. Chen, Xun Cai, Changhua Yu, R. Nelson, D. S. Kimes, R.R. Shoults, Chiman Kwan and K. Liu. Their work appears in journals such as Neurocomputing, Neural Networks, Neural Processing Letters, Remote Sensing Reviews and IEEE Transactions on Signal Processing.
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.