Marguerite Moore
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Signal Processing
- Industrial and Manufacturing Engineering
- Artificial Intelligence
- Co-authors
- B.S. ManjunathYining DengCharles KenneyHyejin ShinSamit ChakrabortyJayanta MukherjeeSushmita MitraRichard E. Weyers
- Topics
- Image and Signal Denoising Methods (2 papers)Advanced Image Fusion Techniques (2 papers)Industrial Vision Systems and Defect Detection (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Graphics and Computer-Aided Design
- Journals
- IEEE Transactions on Image ProcessingSustainabilityInternational Journal of Fashion Design Technology and Education
- Partner nations
- United StatesIndiaSouth Korea
In The Last Decade
Marguerite Moore
6 papers receiving 332 citations
Peers
Comparison fields: 5 of 66
- Computer Vision and Pattern Recognition 297
- Media Technology 85
- Signal Processing 27
- Industrial and Manufacturing Engineering 21
- Artificial Intelligence 19
Countries citing papers authored by Marguerite Moore
This map shows the geographic impact of Marguerite Moore'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 Marguerite Moore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marguerite Moore more than expected).
Fields of papers citing papers by Marguerite Moore
This network shows the impact of papers produced by Marguerite Moore. 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 Marguerite Moore. The network helps show where Marguerite Moore may publish in the future.
Co-authorship network of co-authors of Marguerite Moore
This figure shows the co-authorship network connecting the top 25 collaborators of Marguerite Moore. A scholar is included among the top collaborators of Marguerite Moore 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 Marguerite Moore. Marguerite Moore is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 17 | |
| 4 | 138 | |
| 5 | 5 | |
| 6 | 201 | |
| 7 | EVALUATING THE PERES GROUND PENETRATING RADAR SYSTEM FOR BRIDGE DECK INSPECTION USING IMAGE PROCESSING AND PATTERN RECOGNITION DATA ANALYSIS | 1 |
About Marguerite Moore
Marguerite Moore is a scholar working on Media Technology, Industrial and Manufacturing Engineering and Computer Vision and Pattern Recognition, having authored 7 papers that have together received 367 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (2 papers), Advanced Image Fusion Techniques (2 papers) and Industrial Vision Systems and Defect Detection (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (297 citations), Media Technology (85 citations) and Computer Graphics and Computer-Aided Design (9 citations). Marguerite Moore has collaborated with scholars based in United States, India and South Korea. Frequent co-authors include B.S. Manjunath, Yining Deng, Charles Kenney, Hyejin Shin, Samit Chakraborty, Jayanta Mukherjee, Sushmita Mitra, Richard E. Weyers, Jennifer Duke and Daniel Saloni. Their work appears in journals such as IEEE Transactions on Image Processing, Sustainability and International Journal of Fashion Design Technology and 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.