Ari Seff
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Automotive Engineering top 1%
- Autonomous Vehicle Technology and Safety
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 4
- Radiation Dose and Imaging 1
-
- Autonomous Vehicle Technology and Safety 3
- Co-authors
- Chenyi Chen (1 shared paper)Alain L. Kornhauser (1 shared paper)Jianxiong Xiao (1 shared paper)Le Lu (8 shared papers)Ronald M. Summers (8 shared papers)Jianhua Yao (6 shared papers)Lauren Kim (5 shared papers)Holger R. Roth (6 shared papers)
- Journals
- Advances in computer vision and pattern recognition (2 papers)Journal of Imaging Informatics in Medicine (1 paper)Brain Imaging and Behavior (1 paper)IEEE Transactions on Medical Imaging (1 paper)Lecture notes in computer science (3 papers)
- Partner nations
- United States
In The Last Decade
Ari Seff
13 papers receiving 2.2k citations
Ari Seff's Hit Papers
Peers
Comparison fields: 5 of 100
- Health Informatics 120
- Automotive Engineering 471
- Computer Vision and Pattern Recognition 749
- Artificial Intelligence 763
- Software 70
Countries citing papers authored by Ari Seff
This map shows the geographic impact of Ari Seff'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 Ari Seff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ari Seff more than expected).
Fields of papers citing papers by Ari Seff
This network shows the impact of papers produced by Ari Seff. 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 Ari Seff. The network helps show where Ari Seff may publish in the future.
Co-authors
The 25 scholars most cited alongside Ari Seff, 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 | DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving Hit paper breakdown → | 2015 | 1372 |
| 2 | Improving Computer-Aided Detection UsingConvolutional Neural Networks and Random View Aggregation Hit paper breakdown → | 2015 | 491 |
| 3 | 2015 | 142 | |
| 4 | 2015 | 77 | |
| 5 | 2023 | 61 | |
| 6 | 2014 | 47 | |
| 7 | 2015 | 26 | |
| 8 | 2016 | 19 | |
| 9 | 2014 | 16 | |
| 10 | 2017 | 7 | |
| 11 | 2017 | 3 | |
| 12 | 2024 | 3 | |
| 13 | 2015 | 2 |
About Ari Seff
Ari Seff is a scholar working on Radiology, Nuclear Medicine and Imaging, Automotive Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Health Informatics, having authored 13 papers that have together received 2.3k indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Autonomous Vehicle Technology and Safety (3 papers), Multimodal Machine Learning Applications (2 papers), Image Retrieval and Classification Techniques (2 papers), Medical Image Segmentation Techniques (2 papers), Radiation Dose and Imaging (1 paper) and Artificial Intelligence in Healthcare and Education (1 paper). The work is most often cited by research in Health Informatics (120 citations), Automotive Engineering (471 citations), Computer Vision and Pattern Recognition (749 citations), Artificial Intelligence (763 citations) and Software (70 citations). Ari Seff has collaborated with scholars based in United States. Frequent co-authors include Chenyi Chen, Alain L. Kornhauser, Jianxiong Xiao, Le Lu, Ronald M. Summers, Jianhua Yao, Lauren Kim, Holger R. Roth, Kevin M. Cherry and Jiamin Liu. Their work appears in journals such as Advances in computer vision and pattern recognition, Journal of Imaging Informatics in Medicine, Brain Imaging and Behavior, IEEE Transactions on Medical Imaging and Lecture notes in computer science.
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.