Éric Granger

6.8k citations
208 papers · 3.9k · 2 hit papers · h-index 31

Impact in

Papers in

    • Face and Expression Recognition 47
    • Face recognition and analysis 46
    • Video Surveillance and Tracking Methods 33
    • Advanced Neural Network Applications 24
    • Domain Adaptation and Few-Shot Learning 21
    • Neural Networks and Applications 20
    • Anomaly Detection Techniques and Applications 19

Éric Granger

195 papers receiving 3.7k citations

Éric Granger's Hit Papers

Boundary loss for highly unbalanced segmentation 2020 · 274 citations
2740+3+6Years since publication100200300400

Peers

Éric Granger
Comparison fields: 5 of 172
  • Computer Vision and Pattern Recognition 1.8k
  • Signal Processing 510
  • Artificial Intelligence 1.5k
  • Experimental and Cognitive Psychology 483
  • Media Technology 206
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Countries citing papers authored by Éric Granger

Since Specialization
Citations

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

Fields of papers citing papers by Éric Granger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Éric Granger, 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 Éric Granger Line = papers co-authored together Éric Granger links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 208 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Multiple instance learning: A survey of problem characteristics and applications
Hit paper breakdown →
2017435
2
Boundary loss for highly unbalanced segmentation
Hit paper breakdown →
2020274
3 2019155
4 1997129
5 201086
6 202184
7 201277
8 201974
9 201974
10 202270
11 202070
12 201168
13 201866
14 201363
15 201161
16 200158
17 201958
18 201058
19 202355
20 202050

About Éric Granger

Éric Granger is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Experimental and Cognitive Psychology and Biomedical Engineering, having authored 208 papers that have together received 3.9k indexed citations. Recurring topics across this work include Face and Expression Recognition (47 papers), Face recognition and analysis (46 papers), Video Surveillance and Tracking Methods (33 papers), Biometric Identification and Security (26 papers), Advanced Neural Network Applications (24 papers), Domain Adaptation and Few-Shot Learning (21 papers), Neural Networks and Applications (20 papers) and Anomaly Detection Techniques and Applications (19 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.8k citations), Signal Processing (510 citations), Artificial Intelligence (1.5k citations), Experimental and Cognitive Psychology (483 citations) and Media Technology (206 citations). Éric Granger has collaborated with scholars based in Canada, France and United States. Frequent co-authors include Robert Sabourin, Wheidima Carneiro de Melo, Marc‐André Carbonneau, Ghyslain Gagnon, Veronika Cheplygina, Ismail Ben Ayed, José Dolz, Abdenour Hadid, Hoel Kervadec and Wael Khreich. Their work appears in journals such as Pattern Recognition, Applied Soft Computing, Information Sciences, Image and Vision Computing and Expert Systems with Applications.

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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