Judith Redi

1.9k total citations
59 papers, 1.1k citations indexed

About

Judith Redi is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Media Technology. According to data from OpenAlex, Judith Redi has authored 59 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Computer Vision and Pattern Recognition, 17 papers in Cognitive Neuroscience and 7 papers in Media Technology. Recurrent topics in Judith Redi's work include Image and Video Quality Assessment (40 papers), Visual Attention and Saliency Detection (28 papers) and Aesthetic Perception and Analysis (8 papers). Judith Redi is often cited by papers focused on Image and Video Quality Assessment (40 papers), Visual Attention and Saliency Detection (28 papers) and Aesthetic Perception and Analysis (8 papers). Judith Redi collaborates with scholars based in Netherlands, Italy and Brazil. Judith Redi's co-authors include Ingrid Heynderickx, Jean‐Luc Dugelay, Rodolfo Zunino, Paolo Gastaldo, Yi Zhu, Alan Hanjalić, Ernestasia Siahaan, Hantao Liu, Boris de Ruyter and Sergio Decherchi and has published in prestigious journals such as PLoS ONE, Computers in Human Behavior and Frontiers in Psychology.

In The Last Decade

Judith Redi

57 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Judith Redi Netherlands 18 801 210 134 114 79 59 1.1k
Vidya Setlur United States 20 879 1.1× 43 0.2× 132 1.0× 367 3.2× 122 1.5× 70 1.3k
Isabelle Hupont Spain 13 280 0.3× 65 0.3× 77 0.6× 193 1.7× 28 0.4× 39 603
Azam Bastanfard Iran 17 344 0.4× 47 0.2× 46 0.3× 174 1.5× 56 0.7× 70 686
Ritendra Datta United States 14 2.7k 3.4× 406 1.9× 250 1.9× 394 3.5× 37 0.5× 24 3.1k
Hatim Aboalsamh Saudi Arabia 20 567 0.7× 104 0.5× 272 2.0× 300 2.6× 16 0.2× 97 1.3k
Marko Tkalčič Slovenia 20 450 0.6× 33 0.2× 193 1.4× 334 2.9× 245 3.1× 88 1.5k
Virginio Cantoni Italy 14 363 0.5× 53 0.3× 69 0.5× 86 0.8× 27 0.3× 81 806
Zoya Bylinskii United States 12 693 0.9× 18 0.1× 227 1.7× 215 1.9× 118 1.5× 34 1.0k
Celso A. S. Santos Brazil 14 211 0.3× 29 0.1× 84 0.6× 37 0.3× 173 2.2× 86 601
Yiqing Wang China 10 270 0.3× 69 0.3× 23 0.2× 49 0.4× 18 0.2× 42 575

Countries citing papers authored by Judith Redi

Since Specialization
Citations

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

Fields of papers citing papers by Judith Redi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Judith Redi

This figure shows the co-authorship network connecting the top 25 collaborators of Judith Redi. A scholar is included among the top collaborators of Judith Redi 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 Judith Redi. Judith Redi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Freitas, Pedro Garcia, et al.. (2018). Performance analysis of a video quality ruler methodology for subjective quality assessment. Journal of Electronic Imaging. 27(5). 1–1. 3 indexed citations
2.
Yang, Jie, et al.. (2018). How Do Crowdworker Communities and Microtask Markets Influence Each Other? A Data-Driven Study on Amazon Mechanical Turk. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 6. 193–202. 4 indexed citations
3.
Gu, Jie, Gaofeng Meng, Judith Redi, Shiming Xiang, & Chunhong Pan. (2017). Blind Image Quality Assessment via Vector Regression and Object Oriented Pooling. IEEE Transactions on Multimedia. 20(5). 1140–1153. 35 indexed citations
4.
Chambel, Teresa, René Kaiser, Omar Niamut, Wei Tsang Ooi, & Judith Redi. (2016). AltMM 2016. 1481–1482. 3 indexed citations
5.
Farias, Mylène C. Q., et al.. (2016). Perceptual Annoyance Models for Videos With Combinations of Spatial and Temporal Artifacts. IEEE Transactions on Multimedia. 18(12). 2446–2456. 8 indexed citations
6.
Redi, Judith, et al.. (2016). Inducing Sadness and Anxiousness through Visual Media: Measurement Techniques and Persistence. Frontiers in Psychology. 7. 1141–1141. 22 indexed citations
7.
Zhu, Yi, Ingrid Heynderickx, & Judith Redi. (2015). Understanding the role of social context and user factors in video Quality of Experience. Computers in Human Behavior. 49. 412–426. 79 indexed citations
8.
Redi, Judith, et al.. (2015). Lighting to Make You Feel Better: Improving the Mood of Elderly People with Affective Ambiences. PLoS ONE. 10(7). e0132732–e0132732. 52 indexed citations
9.
Freitas, Pedro Garcia, et al.. (2015). Video quality ruler: A new experimental methodology for assessing video quality. 402. 1–6. 3 indexed citations
10.
Hoßfeld, Tobias & Judith Redi. (2015). Journey through the crowd: Best practices and recommendations for crowdsourced QoE. 1–2. 6 indexed citations
11.
Redi, Judith, et al.. (2014). Crowdsourcing for Rating Image Aesthetic Appeal. 25–30. 27 indexed citations
12.
Siahaan, Ernestasia, Judith Redi, & Alan Hanjalić. (2014). Beauty is in the scale of the beholder: Comparison of methodologies for the subjective assessment of image aesthetic appeal. 245–250. 17 indexed citations
13.
Zhu, Yi, Ingrid Heynderickx, & Judith Redi. (2014). Alone or together: measuring users' viewing experience in different social contexts. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9014. 90140W–90140W. 6 indexed citations
14.
Decherchi, Sergio, Paolo Gastaldo, Rodolfo Zunino, Erik Cambria, & Judith Redi. (2012). Circular-ELM for the reduced-reference assessment of perceived image quality. Neurocomputing. 102. 78–89. 51 indexed citations
15.
Redi, Judith, et al.. (2012). Examining the effect of task on viewing behavior in videos using saliency maps. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8291. 82910X–82910X. 10 indexed citations
16.
Redi, Judith & Ingrid Heynderickx. (2011). Image quality and visual attention interactions: Towards a more reliable analysis in the saliency space. TU/e Research Portal. 7865. 201–206. 10 indexed citations
17.
Liu, Hantao, et al.. (2010). No-reference image quality assessment based on localized gradient statistics: application to JPEG and JPEG2000. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7527. 75271F–75271F. 6 indexed citations
18.
Redi, Judith, Paolo Gastaldo, Ingrid Heynderickx, & Rodolfo Zunino. (2010). Color Distribution Information for the Reduced-Reference Assessment of Perceived Image Quality. IEEE Transactions on Circuits and Systems for Video Technology. 20(12). 1757–1769. 47 indexed citations
19.
Redi, Judith, et al.. (2010). Digital image forensics: a booklet for beginners. Multimedia Tools and Applications. 51(1). 133–162. 255 indexed citations
20.
Redi, Judith, Hantao Liu, Paolo Gastaldo, Rodolfo Zunino, & Ingrid Heynderickx. (2009). How to apply spatial saliency into objective metrics for JPEG compressed images?. TU/e Research Portal. 961–964. 16 indexed citations

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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