Àgata Lapedriza
- Computer Vision and Pattern Recognition top 0.05%
- Artificial Intelligence top 0.1%
- Radiology, Nuclear Medicine and Imaging top 1%
- Media Technology top 0.5%
- Aerospace Engineering top 2%
- Co-authors
- Antonio TorralbaBolei ZhouAude OlivaAditya KhoslaJianxiong XiaoAdrià RecasensRonak KostiJosé M. Alvarez
- Topics
- Face recognition and analysis (12 papers)Face and Expression Recognition (12 papers)Emotion and Mood Recognition (7 papers)
- Journals
- Proceedings of the National Academy of SciencesPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- SpainUnited StatesAustralia
In The Last Decade
Àgata Lapedriza
40 papers receiving 11.6k citations
Hit Papers
Peers
Comparison fields: 5 of 202
- Computer Vision and Pattern Recognition 7.1k
- Artificial Intelligence 4.8k
- Radiology, Nuclear Medicine and Imaging 1.3k
- Media Technology 804
- Aerospace Engineering 607
Countries citing papers authored by Àgata Lapedriza
This map shows the geographic impact of Àgata Lapedriza'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 Àgata Lapedriza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Àgata Lapedriza more than expected).
Fields of papers citing papers by Àgata Lapedriza
This network shows the impact of papers produced by Àgata Lapedriza. 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 Àgata Lapedriza. The network helps show where Àgata Lapedriza may publish in the future.
Co-authorship network of co-authors of Àgata Lapedriza
This figure shows the co-authorship network connecting the top 25 collaborators of Àgata Lapedriza. A scholar is included among the top collaborators of Àgata Lapedriza 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 Àgata Lapedriza. Àgata Lapedriza is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 46 | |
| 5 | 22 | |
| 6 | 3 | |
| 7 | 6 | |
| 8 | 48 | |
| 9 | Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems | 10 |
| 10 | Can we do better explanations? A proposal of user-centered explainable AI | 64 |
| 11 | 4 | |
| 12 | Learning Deep Features for Discriminative Localizationbreakdown → | 6518 |
| 13 | Object Detectors Emerge in Deep Scene CNNs | 275 |
| 14 | Learning Deep Features for Scene Recognition using Places Databasebreakdown → | 1556 |
| 15 | 126 | |
| 16 | Enabling Automatic Just-in-time Evaluation of In-class Discussions in On-line Collaborative Learning Practices | 6 |
| 17 | 16 | |
| 18 | 21 | |
| 19 | 1 | |
| 20 | 1 |
About Àgata Lapedriza
Àgata Lapedriza is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Applied Psychology, having authored 43 papers that have together received 12.0k indexed citations. Recurring topics across this work include Face recognition and analysis (12 papers), Face and Expression Recognition (12 papers) and Emotion and Mood Recognition (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (7.1k citations), Health Informatics (236 citations) and Artificial Intelligence (4.8k citations). Àgata Lapedriza has collaborated with scholars based in Spain, United States and Australia. Frequent co-authors include Antonio Torralba, Bolei Zhou, Aude Oliva, Aditya Khosla, Jianxiong Xiao, Adrià Recasens, Ronak Kosti, José M. Alvarez, Laura Igual and Hendrik Strobelt. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine 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.