Sarah Adel Bargal
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Experimental and Cognitive Psychology top 10%
- Radiology, Nuclear Medicine and Imaging
- Cognitive Neuroscience
- Co-authors
- Stan SclaroffJianming ZhangJonathan BrandtXiaohui ShenZhe LinFatih ÇakirKun HeCristian Canton Ferrer
- Topics
- Adversarial Robustness in Machine Learning (7 papers)Multimodal Machine Learning Applications (5 papers)Human Pose and Action Recognition (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePattern RecognitionInternational Journal of Computer Vision
- Partner nations
- United StatesItalyEgypt
In The Last Decade
Sarah Adel Bargal
22 papers receiving 813 citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Computer Vision and Pattern Recognition 557
- Artificial Intelligence 396
- Experimental and Cognitive Psychology 95
- Radiology, Nuclear Medicine and Imaging 49
- Cognitive Neuroscience 37
Countries citing papers authored by Sarah Adel Bargal
This map shows the geographic impact of Sarah Adel Bargal'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 Sarah Adel Bargal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sarah Adel Bargal more than expected).
Fields of papers citing papers by Sarah Adel Bargal
This network shows the impact of papers produced by Sarah Adel Bargal. 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 Sarah Adel Bargal. The network helps show where Sarah Adel Bargal may publish in the future.
Co-authorship network of co-authors of Sarah Adel Bargal
This figure shows the co-authorship network connecting the top 25 collaborators of Sarah Adel Bargal. A scholar is included among the top collaborators of Sarah Adel Bargal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sarah Adel Bargal. Sarah Adel Bargal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 8 | |
| 6 | 37 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 22 | |
| 10 | NBDT: Neural-Backed Decision Tree | 4 |
| 11 | 15 | |
| 12 | Are CNN Predictions based on Reasonable Evidence | 1 |
| 13 | 51 | |
| 14 | Multi-way Encoding for Robustness to Adversarial Attacks | 1 |
| 15 | 54 | |
| 16 | Top-Down Neural Attention by Excitation Backpropbreakdown → | 372 |
| 17 | 42 | |
| 18 | 109 | |
| 19 | 12 | |
| 20 | Classification of Mouth Action Units: Using Local Binary Patterns | 2 |
About Sarah Adel Bargal
Sarah Adel Bargal is a scholar working on Computer Vision and Pattern Recognition, Computer Science Applications and Artificial Intelligence, having authored 24 papers that have together received 841 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (7 papers), Multimodal Machine Learning Applications (5 papers) and Human Pose and Action Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (557 citations), Health Informatics (18 citations) and Artificial Intelligence (396 citations). Sarah Adel Bargal has collaborated with scholars based in United States, Italy and Egypt. Frequent co-authors include Stan Sclaroff, Jianming Zhang, Jonathan Brandt, Xiaohui Shen, Zhe Lin, Fatih Çakir, Kun He, Cristian Canton Ferrer, Emad Barsoum and Cha Zhang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and International Journal of Computer Vision.
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.