Samuel Dodge
Impact in
-
- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
- Face recognition and analysis
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning
- Machine Learning and ELM
Papers in
-
- Video Surveillance and Tracking Methods 1
- Image and Video Quality Assessment 1
-
- Image Processing Techniques and Applications 4
- Co-authors
- Lina J. Karam (7 shared papers)Matthew D. Zeiler (1 shared paper)Xiaogang Wang (1 shared paper)David Eigen (1 shared paper)Hongyang Li (1 shared paper)Björn Stenger (1 shared paper)Jiu Xu (1 shared paper)Martin Braun (1 shared paper)
- Journals
- ACM Transactions on Applied Perception (1 paper)IEEE Transactions on Semiconductor Manufacturing (1 paper)IEEE Transactions on Image Processing (1 paper)IET Biometrics (1 paper)The HKU Scholars Hub (University of Hong Kong) (1 paper)
- Partner nations
- United StatesIndiaLebanon
In The Last Decade
Samuel Dodge
8 papers receiving 610 citations
Peers
Comparison fields: 5 of 95
- Computer Vision and Pattern Recognition 380
- Artificial Intelligence 286
- Geology 40
- Signal Processing 70
- Media Technology 48
Countries citing papers authored by Samuel Dodge
This map shows the geographic impact of Samuel Dodge'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 Samuel Dodge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel Dodge more than expected).
Fields of papers citing papers by Samuel Dodge
This network shows the impact of papers produced by Samuel Dodge. 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 Samuel Dodge. The network helps show where Samuel Dodge may publish in the future.
Co-authors
The 9 scholars most cited alongside Samuel Dodge, 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 | 2019 | 242 | |
| 2 | 2017 | 189 | |
| 3 | 2017 | 73 | |
| 4 | 2018 | 59 | |
| 5 | 2019 | 25 | |
| 6 | 2018 | 22 | |
| 7 | 2020 | 11 | |
| 8 | 2012 | 2 | |
| 9 | 2016 | 0 |
About Samuel Dodge
Samuel Dodge is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Industrial and Manufacturing Engineering, Human-Computer Interaction and Cognitive Neuroscience, having authored 9 papers that have together received 623 indexed citations. Recurring topics across this work include Image Processing Techniques and Applications (4 papers), Industrial Vision Systems and Defect Detection (3 papers), Gaze Tracking and Assistive Technology (2 papers), Speech and Audio Processing (1 paper), Video Surveillance and Tracking Methods (1 paper), Hand Gesture Recognition Systems (1 paper), Image and Video Quality Assessment (1 paper) and Remote Sensing and LiDAR Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (380 citations), Artificial Intelligence (286 citations), Geology (40 citations), Signal Processing (70 citations) and Media Technology (48 citations). Samuel Dodge has collaborated with scholars based in United States, India and Lebanon. Frequent co-authors include Lina J. Karam, Matthew D. Zeiler, Xiaogang Wang, David Eigen, Hongyang Li, Björn Stenger, Jiu Xu, Martin Braun and Nital S. Patel. Their work appears in journals such as ACM Transactions on Applied Perception, IEEE Transactions on Semiconductor Manufacturing, IEEE Transactions on Image Processing, IET Biometrics 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.