Clément Farabet

9.6k citations
16 papers · 4.8k indexed · 3 hit papers · h-index 12

Impact in

Papers in

Clément Farabet

16 papers receiving 4.6k citations

Hit Papers

Learning Hierarchical Features for Scene Labeling 2012 · 1.8k citations
1.8k201020262015202050010001.5k

Peers

Clément Farabet
Comparison fields: 5 of 173
  • Computer Vision and Pattern Recognition 2.7k
  • Media Technology 427
  • Artificial Intelligence 1.5k
  • Hardware and Architecture 219
  • Signal Processing 238
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Adam Paszke United States
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Edward Z. Yang United States
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Sergey Karayev United States
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Citations per field
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Citations per year

Countries citing papers authored by Clément Farabet

Since Specialization
Citations

This map shows the geographic impact of Clément Farabet'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 Clément Farabet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Clément Farabet more than expected).

Fields of papers citing papers by Clément Farabet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Clément Farabet. 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 Clément Farabet. The network helps show where Clément Farabet may publish in the future.

Co-authors

The 22 scholars most cited alongside Clément Farabet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Clément Farabet Line = papers co-authored together Clément Farabet links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
Less is More: An Exploration of Data Redundancy with Active Dataset Subsampling.
20192
2
Toward real-time indoor semantic segmentation using depth information
201411
3
Clustering learning for robotic vision
20131
4
Indoor semantic segmentation using depth information: 1st International Conference on Learning Representations, ICLR 2013
20131
5 201322
6
Learning Hierarchical Features for Scene Labeling
Hit paper breakdown →
20121796
7 201255
8 201265
9
Torch7: A Matlab-like Environment for Machine Learning
Hit paper breakdown →
2011713
10 2011273
11 20114
12 2010158
13
Convolutional networks and applications in vision
Hit paper breakdown →
20101379
14 200926
15 200939
16 2009254

About Clément Farabet

Clément Farabet is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Geology, Biophysics and Hardware and Architecture, having authored 16 papers that have together received 4.8k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), CCD and CMOS Imaging Sensors (4 papers), Advanced Vision and Imaging (4 papers), Advanced Neural Network Applications (4 papers), Robotics and Sensor-Based Localization (3 papers), Advanced Memory and Neural Computing (2 papers), Image Retrieval and Classification Techniques (2 papers) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (2.7k citations), Media Technology (427 citations), Artificial Intelligence (1.5k citations), Hardware and Architecture (219 citations) and Signal Processing (238 citations). Clément Farabet has collaborated with scholars based in United States, France and Australia. Frequent co-authors include Yann LeCun, Koray Kavukcuoglu, Laurent Najman, Camille Couprie, Ronan Collobert, Eugenio Culurciello, Berin Martini, Cyril Poulet, Jefferson Y. Han and J. A. Pérez‐Carrasco. Their work appears in journals such as Frontiers in Neuroscience, IEEE Transactions on Pattern Analysis and Machine Intelligence, Naval Engineers Journal, SPIRE - Sciences Po Institutional REpository and arXiv (Cornell University).

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.

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2026