Candace Ross
Impact in
-
- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Advanced Neural Network Applications
- Artificial Intelligence top 10%
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
- Natural Language Processing Techniques
- Explainable Artificial Intelligence (XAI)
Papers in
-
- Multimodal Machine Learning Applications 4
- Video Analysis and Summarization 1
- Advanced Image and Video Retrieval Techniques 1
- Face recognition and analysis 1
- Human Pose and Action Recognition 1
-
- Topic Modeling 3
- Domain Adaptation and Few-Shot Learning 2
- Natural Language Processing Techniques 1
- Co-authors
- Adina Williams (3 shared papers)Douwe Kiela (3 shared papers)Amanpreet Singh (1 shared paper)Tristan Thrush (1 shared paper)Max Bartolo (1 shared paper)Eric M. Smith (1 shared paper)Cheng-Yang Fu (1 shared paper)Quentin Duval (1 shared paper)
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- IsraelCanadaUnited States
In The Last Decade
Candace Ross
7 papers receiving 150 citations
Peers
Comparison fields: 5 of 42
- Computer Vision and Pattern Recognition 88
- Artificial Intelligence 107
- Health Informatics 4
- General Social Sciences 3
- Safety Research 6
Countries citing papers authored by Candace Ross
This map shows the geographic impact of Candace Ross'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 Candace Ross with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Candace Ross more than expected).
Fields of papers citing papers by Candace Ross
This network shows the impact of papers produced by Candace Ross. 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 Candace Ross. The network helps show where Candace Ross may publish in the future.
Co-authors
The 16 scholars most cited alongside Candace Ross, 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 | 2022 | 104 | |
| 2 | 2022 | 32 | |
| 3 | 2023 | 13 | |
| 4 | 2018 | 6 | |
| 5 | 2024 | 4 | |
| 6 | 2023 | 2 | |
| 7 | 2024 | 1 |
About Candace Ross
Candace Ross is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Infectious Diseases, Organic Chemistry and Surgery, having authored 7 papers that have together received 162 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (4 papers), Topic Modeling (3 papers), Domain Adaptation and Few-Shot Learning (2 papers), Video Analysis and Summarization (1 paper), Advanced Image and Video Retrieval Techniques (1 paper), Face recognition and analysis (1 paper), Natural Language Processing Techniques (1 paper) and Human Pose and Action Recognition (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (88 citations), Artificial Intelligence (107 citations), Health Informatics (4 citations), General Social Sciences (3 citations) and Safety Research (6 citations). Candace Ross has collaborated with scholars based in Israel, Canada and United States. Frequent co-authors include Adina Williams, Douwe Kiela, Amanpreet Singh, Tristan Thrush, Max Bartolo, Eric M. Smith, Cheng-Yang Fu, Quentin Duval, Nikhila Ravi and Laura Gustafson. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.