Daniel Moyer

1.0k citations
48 papers · 327 · h-index 12

Impact in

Papers in

Daniel Moyer

37 papers receiving 324 citations

Peers

Daniel Moyer
Comparison fields: 5 of 87
  • Computational Mathematics 4
  • Radiology, Nuclear Medicine and Imaging 120
  • Cognitive Neuroscience 81
  • Health Informatics 4
  • Pediatrics, Perinatology and Child Health 48
Replace Tabinda Sarwar with:
Tabinda Sarwar Australia
Biao Cai United States
Gina Belmonte Italy
Pedro F. da Costa United Kingdom
Simon Koppers Germany
Lili He United States
Salman Ul Hassan Dar Türkiye
Byungkon Kang South Korea
Jelena Božek Croatia
Ning Situ United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Moyer

Since Specialization
Citations

This map shows the geographic impact of Daniel Moyer'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 Moyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Moyer more than expected).

Fields of papers citing papers by Daniel Moyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Moyer. 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 Moyer. The network helps show where Daniel Moyer may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Moyer, 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 Moyer Line = papers co-authored together Daniel Moyer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202353
2 202225
3
Invariant Representations without Adversarial Training
201822
4 201322
5 202021
6 202121
7 201918
8 201616
9 202316
10 201716
11 201512
12 201811
13 20178
14 20247
15 20166
16 20215
17 20235
18 20215
19 20165
20 20214

About Daniel Moyer

Daniel Moyer is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Artificial Intelligence, Computer Vision and Pattern Recognition and Surgery, having authored 48 papers that have together received 327 indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (23 papers), Advanced MRI Techniques and Applications (17 papers), Functional Brain Connectivity Studies (13 papers), MRI in cancer diagnosis (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Adversarial Robustness in Machine Learning (3 papers), Fetal and Pediatric Neurological Disorders (3 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Computational Mathematics (4 citations), Radiology, Nuclear Medicine and Imaging (120 citations), Cognitive Neuroscience (81 citations), Health Informatics (4 citations) and Pediatrics, Perinatology and Child Health (48 citations). Daniel Moyer has collaborated with scholars based in United States, United Kingdom and Russia. Frequent co-authors include Polina Golland, Paul M. Thompson, Elfar Adalsteinsson, Junshen Xu, Juan Eugenio Iglesias, Neda Jahanshad, Boris A. Gutman, Borjan Gagoski, P. Ellen Grant and Joshua Faskowitz. Their work appears in journals such as IEEE Transactions on Medical Imaging, The Journal of Arthroplasty, Magnetic Resonance Imaging, IEEE Robotics and Automation Letters and Frontiers in Human Neuroscience.

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.

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