Mary M. Moya
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Media Technology top 10%
- Control and Systems Engineering
- Co-authors
- L.D. HostetlerMark W. KochDon HushH. SerajiJohn G. TaylorMajeed M. HayatJonathan TranDavid N. Perkins
- Topics
- Neural Networks and Applications (8 papers)Advanced SAR Imaging Techniques (6 papers)Remote-Sensing Image Classification (5 papers)
- Journals
- Neural NetworksOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)NASA STI/Recon Technical Report N
- Partner nations
- United States
In The Last Decade
Mary M. Moya
16 papers receiving 359 citations
Peers
Comparison fields: 5 of 75
- Artificial Intelligence 244
- Computer Vision and Pattern Recognition 78
- Computer Networks and Communications 45
- Media Technology 42
- Control and Systems Engineering 41
Countries citing papers authored by Mary M. Moya
This map shows the geographic impact of Mary M. Moya'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 Mary M. Moya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mary M. Moya more than expected).
Fields of papers citing papers by Mary M. Moya
This network shows the impact of papers produced by Mary M. Moya. 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 Mary M. Moya. The network helps show where Mary M. Moya may publish in the future.
Co-authorship network of co-authors of Mary M. Moya
This figure shows the co-authorship network connecting the top 25 collaborators of Mary M. Moya. A scholar is included among the top collaborators of Mary M. Moya 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 Mary M. Moya. Mary M. Moya 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 | 3 | |
| 3 | 3 | |
| 4 | Superpixel Segmentations of Synthetic Aperture Radar Imagery derived from Combinations of Multiple Data Products. | 1 |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 2 | |
| 10 | 122 | |
| 11 | 57 | |
| 12 | One-class classifier networks for target recognition applications | 147 |
| 13 | 3 | |
| 14 | Feature discovery via neural networks for object recognition in SAR imagery | 2 |
| 15 | 1 | |
| 16 | One-class generalization in second-order backpropagation networks for image classification | 9 |
| 17 | 1 | |
| 18 | 12 |
About Mary M. Moya
Mary M. Moya is a scholar working on Media Technology, Aerospace Engineering and Artificial Intelligence, having authored 18 papers that have together received 376 indexed citations. Recurring topics across this work include Neural Networks and Applications (8 papers), Advanced SAR Imaging Techniques (6 papers) and Remote-Sensing Image Classification (5 papers). The work is most often cited by research in Artificial Intelligence (244 citations), Media Technology (42 citations) and Computer Vision and Pattern Recognition (78 citations). Mary M. Moya has collaborated with scholars based in United States. Frequent co-authors include L.D. Hostetler, Mark W. Koch, Don Hush, H. Seraji, John G. Taylor, Majeed M. Hayat, Jonathan Tran, David N. Perkins and D. Hush. Their work appears in journals such as Neural Networks, OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) and NASA STI/Recon Technical Report N.
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.