Stanley Bileschi
Impact in
-
- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques
- Visual Attention and Saliency Detection
- Video Surveillance and Tracking Methods
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Visual perception and processing mechanisms
- Face Recognition and Perception
Papers in
-
- Advanced Image and Video Retrieval Techniques 6
- Image Retrieval and Classification Techniques 4
- Visual Attention and Saliency Detection 1
-
- Remote-Sensing Image Classification 3
- Journals
- International Journal of Computer Vision (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (1 paper)Proceedings - International Conference on Pattern Recognition (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Stanley Bileschi
11 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Computer Vision and Pattern Recognition 869
- Cognitive Neuroscience 448
- Media Technology 162
- Human-Computer Interaction 44
- Artificial Intelligence 223
Countries citing papers authored by Stanley Bileschi
This map shows the geographic impact of Stanley Bileschi'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 Stanley Bileschi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stanley Bileschi more than expected).
Fields of papers citing papers by Stanley Bileschi
This network shows the impact of papers produced by Stanley Bileschi. 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 Stanley Bileschi. The network helps show where Stanley Bileschi may publish in the future.
Co-authors
The 5 scholars most cited alongside Stanley Bileschi, 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 | Deep Learning with JavaScript: Neural networks in TensorFlow.js | 2021 | 3 |
| 2 | 2009 | 32 | |
| 3 | 2008 | 7 | |
| 4 | A Multi-Scale Generalization of the HoG and HMAX Image Descriptors for Object Detection | 2008 | 2 |
| 5 | Robust Object Recognition with Cortex-Like Mechanisms Hit paper breakdown → | 2007 | 1097 |
| 6 | 2007 | 22 | |
| 7 | 2006 | 20 | |
| 8 | 2006 | 115 | |
| 9 | 2005 | 21 | |
| 10 | 2005 | 19 | |
| 11 | 2004 | 4 |
About Stanley Bileschi
Stanley Bileschi is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Human-Computer Interaction, Geology and Biophysics, having authored 11 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (6 papers), Image Retrieval and Classification Techniques (4 papers), Remote-Sensing Image Classification (3 papers), Neural Networks and Applications (2 papers), Robotics and Sensor-Based Localization (2 papers), 3D Surveying and Cultural Heritage (1 paper), Neural dynamics and brain function (1 paper) and Visual Attention and Saliency Detection (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (869 citations), Cognitive Neuroscience (448 citations), Media Technology (162 citations), Human-Computer Interaction (44 citations) and Artificial Intelligence (223 citations). Stanley Bileschi has collaborated with scholars based in United States and Israel. Frequent co-authors include Lior Wolf, Tomaso Poggio, Maximilian Riesenhuber, T. Serre and Ethan M. Meyers. Their work appears in journals such as International Journal of Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, DSpace@MIT (Massachusetts Institute of Technology) and Proceedings - International Conference on Pattern Recognition.
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.