Robert DiBiano
Impact in
- Media Technology top 2%
- Remote-Sensing Image Classification
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- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Image Retrieval and Classification Techniques
Papers in
-
- Human Pose and Action Recognition 2
- Medical Image Segmentation Techniques 1
- Generative Adversarial Networks and Image Synthesis 1
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- Machine Learning and Data Classification 2
- Co-authors
- Supratik Mukhopadhyay (11 shared papers)Ramakrishna Nemani (5 shared papers)Manohar Karki (7 shared papers)Saikat Basu (7 shared papers)Sangram Ganguly (6 shared papers)Yimin Zhu (3 shared papers)Chang Wei Tan (1 shared paper)Rajgopal Kannan (1 shared paper)
- Journals
- Neural Processing Letters (1 paper)Automation in Construction (1 paper)MethodsX (1 paper)AIAA Journal (1 paper)IEEE Transactions on Geoscience and Remote Sensing (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Robert DiBiano
12 papers receiving 432 citations
Peers
Comparison fields: 5 of 84
- Media Technology 155
- Computer Vision and Pattern Recognition 149
- Environmental Engineering 66
- Building and Construction 52
- Atmospheric Science 58
Countries citing papers authored by Robert DiBiano
This map shows the geographic impact of Robert DiBiano'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 Robert DiBiano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert DiBiano more than expected).
Fields of papers citing papers by Robert DiBiano
This network shows the impact of papers produced by Robert DiBiano. 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 Robert DiBiano. The network helps show where Robert DiBiano may publish in the future.
Co-authors
The 20 scholars most cited alongside Robert DiBiano, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 210 | |
| 2 | 2017 | 57 | |
| 3 | 2016 | 47 | |
| 4 | 2015 | 34 | |
| 5 | 2019 | 30 | |
| 6 | 1972 | 20 | |
| 7 | 2019 | 14 | |
| 8 | 2017 | 10 | |
| 9 | 2018 | 8 | |
| 10 | 2015 | 4 | |
| 11 | 2013 | 3 | |
| 12 | 2016 | 2 | |
| 13 | 2015 | 1 |
About Robert DiBiano
Robert DiBiano is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Environmental Engineering, Building and Construction and Civil and Structural Engineering, having authored 13 papers that have together received 440 indexed citations. Recurring topics across this work include Building Energy and Comfort Optimization (3 papers), Human Pose and Action Recognition (2 papers), Machine Learning and Data Classification (2 papers), Medical Image Segmentation Techniques (1 paper), Wind and Air Flow Studies (1 paper), Noise Effects and Management (1 paper), Facilities and Workplace Management (1 paper) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Media Technology (155 citations), Computer Vision and Pattern Recognition (149 citations), Environmental Engineering (66 citations), Building and Construction (52 citations) and Atmospheric Science (58 citations). Robert DiBiano has collaborated with scholars based in United States and China. Frequent co-authors include Supratik Mukhopadhyay, Ramakrishna Nemani, Manohar Karki, Saikat Basu, Sangram Ganguly, Yimin Zhu, Chang Wei Tan, Rajgopal Kannan, Andrew Michaelis and Laura Duncanson. Their work appears in journals such as Neural Processing Letters, Automation in Construction, MethodsX, AIAA Journal and IEEE Transactions on Geoscience and Remote Sensing.
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.