Nuno Vasconcelos
Impact in
- Computer Vision and Pattern Recognition top 0.02%
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Image Retrieval and Classification Techniques
- Advanced Neural Network Applications
- Visual Attention and Saliency Detection
- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
- Artificial Intelligence top 0.05%
- Anomaly Detection Techniques and Applications
Papers in
-
- Advanced Image and Video Retrieval Techniques 91
- Image Retrieval and Classification Techniques 64
- Video Surveillance and Tracking Methods 28
- Visual Attention and Saliency Detection 25
- Face and Expression Recognition 24
- Video Analysis and Summarization 24
-
- Domain Adaptation and Few-Shot Learning 36
- Anomaly Detection Techniques and Applications 30
- Co-authors
- Antoni B. Chan (24 shared papers)Vijay Mahadevan (18 shared papers)Zhaowei Cai (9 shared papers)Weixin Li (8 shared papers)Dashan Gao (13 shared papers)Andrew Lippman (28 shared papers)Nikhil Rasiwasia (13 shared papers)Pedro J. Moreno (5 shared papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (18 papers)IEEE Transactions on Image Processing (4 papers)Lecture notes in computer science (22 papers)IEEE Transactions on Multimedia (2 papers)Medical Image Analysis (2 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Nuno Vasconcelos
235 papers receiving 17.3k citations
Nuno Vasconcelos's Hit Papers
Peers
Comparison fields: 5 of 182
- Computer Vision and Pattern Recognition 14.2k
- Artificial Intelligence 7.3k
- Media Technology 1.2k
- Sensory Systems 549
- Signal Processing 1.2k
Countries citing papers authored by Nuno Vasconcelos
This map shows the geographic impact of Nuno Vasconcelos'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 Nuno Vasconcelos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nuno Vasconcelos more than expected).
Fields of papers citing papers by Nuno Vasconcelos
This network shows the impact of papers produced by Nuno Vasconcelos. 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 Nuno Vasconcelos. The network helps show where Nuno Vasconcelos may publish in the future.
Co-authors
The 25 scholars most cited alongside Nuno Vasconcelos, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 249 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Cascade R-CNN: High Quality Object Detection and Instance Segmentation Hit paper breakdown → | 2019 | 1259 |
| 2 | A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection Hit paper breakdown → | 2016 | 1188 |
| 3 | Anomaly detection in crowded scenes Hit paper breakdown → | 2010 | 1175 |
| 4 | A new approach to cross-modal multimedia retrieval Hit paper breakdown → | 2010 | 1056 |
| 5 | Privacy preserving crowd monitoring: Counting people without people models or tracking Hit paper breakdown → | 2008 | 888 |
| 6 | Anomaly Detection and Localization in Crowded Scenes Hit paper breakdown → | 2013 | 788 |
| 7 | Supervised Learning of Semantic Classes for Image Annotation and Retrieval Hit paper breakdown → | 2007 | 682 |
| 8 | Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures Hit paper breakdown → | 2008 | 358 |
| 9 | On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval Hit paper breakdown → | 2013 | 351 |
| 10 | 2009 | 323 | |
| 11 | Deep Learning with Low Precision by Half-Wave Gaussian Quantization Hit paper breakdown → | 2017 | 320 |
| 12 | 2009 | 310 | |
| 13 | 2011 | 309 | |
| 14 | A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications | 2003 | 301 |
| 15 | 2009 | 236 | |
| 16 | 2018 | 236 | |
| 17 | 2008 | 230 | |
| 18 | 2016 | 219 | |
| 19 | 2007 | 205 | |
| 20 | 2009 | 176 |
About Nuno Vasconcelos
Nuno Vasconcelos is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Media Technology and Computational Mechanics, having authored 249 papers that have together received 18.0k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (91 papers), Image Retrieval and Classification Techniques (64 papers), Domain Adaptation and Few-Shot Learning (36 papers), Anomaly Detection Techniques and Applications (30 papers), Video Surveillance and Tracking Methods (28 papers), Visual Attention and Saliency Detection (25 papers), Face and Expression Recognition (24 papers) and Video Analysis and Summarization (24 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (14.2k citations), Artificial Intelligence (7.3k citations), Media Technology (1.2k citations), Sensory Systems (549 citations) and Signal Processing (1.2k citations). Nuno Vasconcelos has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Antoni B. Chan, Vijay Mahadevan, Zhaowei Cai, Weixin Li, Dashan Gao, Andrew Lippman, Nikhil Rasiwasia, Pedro J. Moreno, Rogério Feris and Quanfu Fan. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, Lecture notes in computer science, IEEE Transactions on Multimedia and Medical Image Analysis.
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.