Daniel H. Chae
Impact in
- Developmental Biology top 10%
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- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
Papers in
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- Sparse and Compressive Sensing Techniques 6
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- Microwave Imaging and Scattering Analysis 3
- Photoacoustic and Ultrasonic Imaging 1
- Co-authors
- Blair R. Costelloe (1 shared paper)Jacob M. Graving (1 shared paper)Liang Li (1 shared paper)Iain D. Couzin (1 shared paper)Benjamin Koger (1 shared paper)Hemal Naik (1 shared paper)Rodney A. Kennedy (5 shared papers)Seungjin Choi (1 shared paper)
- Journals
- eLife (1 paper)Antimicrobial Agents and Chemotherapy (1 paper)ANU Open Research (Australian National University) (6 papers)
- Partner nations
- AustraliaUnited StatesSouth Korea
In The Last Decade
Daniel H. Chae
9 papers receiving 451 citations
Daniel H. Chae's Hit Papers
Peers
Comparison fields: 5 of 102
- Developmental Biology 19
- Computer Vision and Pattern Recognition 110
- Small Animals 38
- Ecological Modeling 22
- Cell Biology 66
Countries citing papers authored by Daniel H. Chae
This map shows the geographic impact of Daniel H. Chae'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 H. Chae with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel H. Chae more than expected).
Fields of papers citing papers by Daniel H. Chae
This network shows the impact of papers produced by Daniel H. Chae. 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 H. Chae. The network helps show where Daniel H. Chae may publish in the future.
Co-authors
The 17 scholars most cited alongside Daniel H. Chae, 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 | DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning Hit paper breakdown → | 2019 | 332 |
| 2 | 2016 | 49 | |
| 3 | 2010 | 36 | |
| 4 | 2013 | 26 | |
| 5 | 2016 | 6 | |
| 6 | 2013 | 4 | |
| 7 | 2012 | 4 | |
| 8 | 2014 | 2 | |
| 9 | 2012 | 1 |
About Daniel H. Chae
Daniel H. Chae is a scholar working on Computational Mechanics, Biomedical Engineering, Signal Processing, Artificial Intelligence and Geophysics, having authored 9 papers that have together received 460 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (6 papers), Microwave Imaging and Scattering Analysis (3 papers), Time Series Analysis and Forecasting (1 paper), Medical Imaging Techniques and Applications (1 paper), Geophysical and Geoelectrical Methods (1 paper), Photoacoustic and Ultrasonic Imaging (1 paper), Image and Signal Denoising Methods (1 paper) and Robot Manipulation and Learning (1 paper). The work is most often cited by research in Developmental Biology (19 citations), Computer Vision and Pattern Recognition (110 citations), Small Animals (38 citations), Ecological Modeling (22 citations) and Cell Biology (66 citations). Daniel H. Chae has collaborated with scholars based in Australia, United States and South Korea. Frequent co-authors include Blair R. Costelloe, Jacob M. Graving, Liang Li, Iain D. Couzin, Benjamin Koger, Hemal Naik, Rodney A. Kennedy, Seungjin Choi, Parastoo Sadeghi and Salman Durrani. Their work appears in journals such as eLife, Antimicrobial Agents and Chemotherapy and ANU Open Research (Australian National 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.