Claire-Hélène Demarty

908 citations
31 papers · 262 indexed · h-index 8

Claire-Hélène Demarty

28 papers receiving 232 citations

Peers

Claire-Hélène Demarty
Comparison fields: 5 of 40
  • Computer Vision and Pattern Recognition 221
  • Signal Processing 41
  • Artificial Intelligence 120
  • Experimental and Cognitive Psychology 8
  • Computer Graphics and Computer-Aided Design 2
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Countries citing papers authored by Claire-Hélène Demarty

Since Specialization
Citations

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

Fields of papers citing papers by Claire-Hélène Demarty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Claire-Hélène Demarty. 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 Claire-Hélène Demarty. The network helps show where Claire-Hélène Demarty may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
2 20233
3 20233
4 20236
5 20231
6 20232
7 20234
8 20214
9 20217
10 202017
11
The Predicting Media Memorability Task at MediaEval 2019.
20197
12
Transfer Learning for Video Memorability Prediction.
20182
13
Technicolor@MediaEval 2016 Predicting Media Interestingness Task.
20166
14 201522
15
The MediaEval 2014 Affect Task: Violent Scenes Detection
20147
16 201453
17 20144
18 201427
19
De la détection d'évènements sonores violents par SVM dans les films
20110
20
The MediaEval 2011 Affect Task: Violent Scenes Detection in Hollywood Movies
201123

About Claire-Hélène Demarty

Claire-Hélène Demarty is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Literature and Literary Theory, having authored 31 papers that have together received 262 indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (9 papers), Video Analysis and Summarization (8 papers), Image and Video Quality Assessment (7 papers), Music and Audio Processing (6 papers), Human Pose and Action Recognition (5 papers), Anomaly Detection Techniques and Applications (5 papers), Image Enhancement Techniques (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (221 citations), Signal Processing (41 citations) and Artificial Intelligence (120 citations). Claire-Hélène Demarty has collaborated with scholars based in France, Romania and Germany. Frequent co-authors include Cédric Penet, Mohammad Soleymani, Guillaume Gravier, Bogdan Ionescu, Yu–Gang Jiang, Mats Sjöberg, Markus Schedl, Laurent Blondé, Olivier Le Meur and Ngoc Q. K. Duong. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and International Journal of Computer Vision.

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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