Daniel H. Chae

780 citations
9 papers · 460 · 1 hit paper · h-index 5

Impact in

Papers in

Daniel H. Chae

9 papers receiving 451 citations

Daniel H. Chae's Hit Papers

DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning 2019 · 332 citations
3320+2+4Years since publication100200300

Peers

Daniel H. Chae
Comparison fields: 5 of 102
  • Developmental Biology 19
  • Computer Vision and Pattern Recognition 110
  • Small Animals 38
  • Ecological Modeling 22
  • Cell Biology 66
Replace Steffen Schneider with:
Steffen Schneider Germany
Lindsay Willmore United States
Hemal Naik Germany
Benjamin Koger Germany
Diego Aldarondo United States
Mu Zhou China
Jessy Lauer Portugal
Jacob M. Graving Germany
Shaokai Ye United States
Daniel H. Chae relative to Steffen Schneider Germany Steffen Schneider's profile →
Citations per field
00.5×4.4×
Steffen Schneider · 1×
Citations per year

Countries citing papers authored by Daniel H. Chae

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Daniel H. Chae Line = papers co-authored together Daniel H. Chae links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning
Hit paper breakdown →
2019332
2 201649
3 201036
4 201326
5 20166
6 20134
7 20124
8 20142
9 20121

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.

Explore authors with similar magnitude of impact