Pierre Sermanet
About
In The Last Decade
Pierre Sermanet
33 papers receiving 32.1k citations
Hit Papers
Peers
Comparison fields: 5 of 215
- Computer Vision and Pattern Recognition 18.9k
- Artificial Intelligence 10.6k
- Radiology, Nuclear Medicine and Imaging 3.7k
- Media Technology 3.3k
- Electrical and Electronic Engineering 2.3k
Countries citing papers authored by Pierre Sermanet
This map shows the geographic impact of Pierre Sermanet'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 Pierre Sermanet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierre Sermanet more than expected).
Fields of papers citing papers by Pierre Sermanet
This network shows the impact of papers produced by Pierre Sermanet. 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 Pierre Sermanet. The network helps show where Pierre Sermanet may publish in the future.
Co-authorship network of co-authors of Pierre Sermanet
This figure shows the co-authorship network connecting the top 25 collaborators of Pierre Sermanet. A scholar is included among the top collaborators of Pierre Sermanet 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 Pierre Sermanet. Pierre Sermanet is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 25 | |
| 2 | 22 | |
| 3 | 9 | |
| 4 | 1 | |
| 5 | 67 | |
| 6 | 27 | |
| 7 | 7 | |
| 8 | Temporal Reasoning in Videos Using Convolutional Gated Recurrent Units | 12 |
| 9 | Time-Contrastive Networks: Self-Supervised Learning from Video breakdown → | 305 |
| 10 | 63 | |
| 11 | Attention for fine-grained categorization | 15 |
| 12 | Going deeper with convolutions breakdown → | 30609 |
| 13 | Overfeat: Integrated recognition, localization and detection using convolutional networks. 2nd International Conference on Learning Representations, ICLR 2014 | 16 |
| 14 | Traffic sign recognition with multi-scale Convolutional Networks breakdown → | 526 |
| 15 | Learning Convolutional Feature Hierarchies for Visual Recognition breakdown → | 328 |
| 16 | Learning maneuver dictionaries for ground robot planning | 4 |
| 17 | 54 | |
| 18 | A multi-range vision strategy for autonomous offroad navigation | 12 |
| 19 | 7 | |
| 20 | 25 |
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.