David Eigen
Impact in
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- Advanced Vision and Imaging
- Advanced Neural Network Applications
- Advanced Image Processing Techniques
- Image Enhancement Techniques
- Optical measurement and interference techniques
- Media Technology top 0.5%
- Image Processing Techniques and Applications
Papers in
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- Multimodal Machine Learning Applications 2
- Image and Signal Denoising Methods 2
- Generative Adversarial Networks and Image Synthesis 2
- Advanced Image and Video Retrieval Techniques 2
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- Anomaly Detection Techniques and Applications 2
- Co-authors
- Rob Fergus (4 shared papers)Dilip Krishnan (1 shared paper)Hongyang Li (1 shared paper)Samuel Dodge (1 shared paper)Matthew D. Zeiler (1 shared paper)Xiaogang Wang (1 shared paper)Li Wan (1 shared paper)Yann LeCun (3 shared papers)
- Journals
- BMJ (1 paper)npj Digital Medicine (1 paper)International Conference on Learning Representations (2 papers)The HKU Scholars Hub (University of Hong Kong) (1 paper)
- Partner nations
- United StatesFranceIsrael
In The Last Decade
David Eigen
9 papers receiving 2.3k citations
David Eigen's Hit Papers
Peers
Comparison fields: 5 of 105
- Computer Vision and Pattern Recognition 2.0k
- Media Technology 665
- Computer Graphics and Computer-Aided Design 83
- Geology 79
- Artificial Intelligence 451
Countries citing papers authored by David Eigen
This map shows the geographic impact of David Eigen'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 David Eigen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Eigen more than expected).
Fields of papers citing papers by David Eigen
This network shows the impact of papers produced by David Eigen. 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 David Eigen. The network helps show where David Eigen may publish in the future.
Co-authors
The 25 scholars most cited alongside David Eigen, 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 | Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture Hit paper breakdown → | 2015 | 1657 |
| 2 | Restoring an Image Taken through a Window Covered with Dirt or Rain Hit paper breakdown → | 2013 | 304 |
| 3 | 2019 | 242 | |
| 4 | 2015 | 62 | |
| 5 | 2015 | 49 | |
| 6 | Overfeat: Integrated recognition, localization and detection using convolutional networks. 2nd International Conference on Learning Representations, ICLR 2014 | 2014 | 16 |
| 7 | 2024 | 3 | |
| 8 | 2024 | 3 | |
| 9 | Unsupervised Feature Learning from Temporal Data | 2015 | 2 |
About David Eigen
David Eigen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Otorhinolaryngology, Pulmonary and Respiratory Medicine and Cognitive Neuroscience, having authored 9 papers that have together received 2.3k indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (2 papers), Image and Signal Denoising Methods (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers), COVID-19 diagnosis using AI (1 paper), Hearing Loss and Rehabilitation (1 paper) and Robotics and Sensor-Based Localization (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (2.0k citations), Media Technology (665 citations), Computer Graphics and Computer-Aided Design (83 citations), Geology (79 citations) and Artificial Intelligence (451 citations). David Eigen has collaborated with scholars based in United States, France and Israel. Frequent co-authors include Rob Fergus, Dilip Krishnan, Hongyang Li, Samuel Dodge, Matthew D. Zeiler, Xiaogang Wang, Li Wan, Yann LeCun, Jonathan Tompson and Ross Goroshin. Their work appears in journals such as BMJ, npj Digital Medicine, International Conference on Learning Representations and The HKU Scholars Hub (University of Hong Kong).
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.