Michele A. Saad

20 papers receiving 2.2k citations

Hit Papers

Blind Image Quality Assessment: A Natural Scene Statistic...2012202620162021201220144008001.2k

Peers

Michele A. Saad
Comparison fields: 5 of 78
  • Computer Vision and Pattern Recognition 2.2k
  • Media Technology 1.1k
  • Atomic and Molecular Physics, and Optics 167
  • Signal Processing 148
  • Cognitive Neuroscience 51
Replace Christophe Charrier with:
Christophe Charrier France
Muhammad Farooq Sabir United States
Manish Narwaria France
Anish Mittal United States
Jari Korhonen Denmark
Lina Jin United States
Hojatollah Yeganeh Canada
Ee Ping Ong Singapore
Deepti Ghadiyaram United States
Tsung-Jung Liu Taiwan
Michele A. Saad relative to Christophe Charrier France Christophe Charrier's profile →
Citations per field
00.5×1.5×
Christophe Charrier · 1×
Citations per year

Countries citing papers authored by Michele A. Saad

Since Specialization
Citations

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

Fields of papers citing papers by Michele A. Saad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michele A. Saad. 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 Michele A. Saad. The network helps show where Michele A. Saad may publish in the future.

Co-authorship network of co-authors of Michele A. Saad

This figure shows the co-authorship network connecting the top 25 collaborators of Michele A. Saad. A scholar is included among the top collaborators of Michele A. Saad 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 Michele A. Saad. Michele A. Saad 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
#WorkIndexed citations
1 5
2 7
3 18
4 3
5 3
6 1
7 15
8 246
9 12
10 5
11 2
12
Blind Prediction of Natural Video Qualitybreakdown →
332
13 1
14 31
15
Blind Image Quality Assessment: A Natural Scene Statistics Approach in the DCT Domainbreakdown →
1258
16 1
17 16
18 292
19 6
20 4

About Michele A. Saad

Michele A. Saad is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Cognitive Neuroscience, having authored 20 papers that have together received 2.3k indexed citations. Recurring topics across this work include Image and Video Quality Assessment (15 papers), Advanced Image Processing Techniques (7 papers) and Advanced Image Fusion Techniques (6 papers). The work is most often cited by research in Media Technology (1.1k citations), Computer Vision and Pattern Recognition (2.2k citations) and Signal Processing (148 citations). Michele A. Saad has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Alan C. Bovik, Christophe Charrier, Anish Mittal, Philip Corriveau, Glenn Van Wallendael, Stamos Katsigiannis, Lucjan Janowski, Naeem Ramzan, Jennifer Healey and Sridhar Mahadevan. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Signal Processing Letters and Journal of 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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