Daniel Bolya
Impact in
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
- Media Technology top 10%
Papers in
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- Advanced Neural Network Applications 3
- Advanced Image and Video Retrieval Techniques 2
- Generative Adversarial Networks and Image Synthesis 2
- Image Enhancement Techniques 1
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- Anomaly Detection Techniques and Applications 1
- Natural Language Processing Techniques 1
- Co-authors
- Fanyi Xiao (1 shared paper)Yong Jae Lee (1 shared paper)Chong Zhou (1 shared paper)Judy Hoffman (5 shared papers)Peizhao Zhang (1 shared paper)Cheng-Yang Fu (1 shared paper)Xiaoliang Dai (1 shared paper)James M. Rehg (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Lecture notes in computer science (2 papers)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesSouth Korea
In The Last Decade
Daniel Bolya
6 papers receiving 496 citations
Daniel Bolya's Hit Papers
Peers
Comparison fields: 5 of 90
- Computer Vision and Pattern Recognition 303
- Media Technology 53
- Industrial and Manufacturing Engineering 57
- Geology 16
- Aerospace Engineering 61
Countries citing papers authored by Daniel Bolya
This map shows the geographic impact of Daniel Bolya'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 Daniel Bolya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Bolya more than expected).
Fields of papers citing papers by Daniel Bolya
This network shows the impact of papers produced by Daniel Bolya. 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 Daniel Bolya. The network helps show where Daniel Bolya may publish in the future.
Co-authors
The 11 scholars most cited alongside Daniel Bolya, 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 | YOLACT++ Better Real-Time Instance Segmentation Hit paper breakdown → | 2020 | 401 |
| 2 | 2023 | 51 | |
| 3 | 2023 | 45 | |
| 4 | 2021 | 4 | |
| 5 | 2020 | 4 | |
| 6 | 2025 | 3 |
About Daniel Bolya
Daniel Bolya is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction, Biomedical Engineering and Infectious Diseases, having authored 6 papers that have together received 508 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (3 papers), Advanced Image and Video Retrieval Techniques (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Hand Gesture Recognition Systems (1 paper), Anomaly Detection Techniques and Applications (1 paper), Image Enhancement Techniques (1 paper), Natural Language Processing Techniques (1 paper) and Gait Recognition and Analysis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (303 citations), Media Technology (53 citations), Industrial and Manufacturing Engineering (57 citations), Geology (16 citations) and Aerospace Engineering (61 citations). Daniel Bolya has collaborated with scholars based in United States and South Korea. Frequent co-authors include Fanyi Xiao, Yong Jae Lee, Chong Zhou, Judy Hoffman, Peizhao Zhang, Cheng-Yang Fu, Xiaoliang Dai, James M. Rehg, Fiona Ryan and Lin Fu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Lecture notes in computer science and arXiv (Cornell University).
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.