Maha Sallam

13 total papers · 2.8k total citations
9 papers, 90 citations indexed

About

Maha Sallam is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Maha Sallam has authored 9 papers receiving a total of 90 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Computer Networks and Communications. Recurrent topics in Maha Sallam's work include AI in cancer detection (3 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Image Retrieval and Classification Techniques (2 papers). Maha Sallam is often cited by papers focused on AI in cancer detection (3 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Image Retrieval and Classification Techniques (2 papers). Maha Sallam collaborates with scholars based in United States. Maha Sallam's co-authors include Kevin W. Bowyer, Dmitry B. Goldgof, Daniel Eggert, K. Woods, D. Goldgof and Sanjay Kumar and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Pattern Recognition Letters.

In The Last Decade

Maha Sallam

8 papers receiving 83 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Maha Sallam 63 39 20 18 8 9 90
Mehdi Cherti 133 2.1× 99 2.5× 12 0.6× 7 0.4× 5 0.6× 6 221
Noel E. O’Connor 204 3.2× 37 0.9× 28 1.4× 10 0.6× 7 0.9× 11 258
Ruifei He 180 2.9× 70 1.8× 16 0.8× 17 0.9× 2 0.3× 6 224
Tianhe Wu 181 2.9× 15 0.4× 18 0.9× 16 0.9× 7 0.9× 7 265
Jiahao Wang 151 2.4× 14 0.4× 12 0.6× 15 0.8× 4 0.5× 11 216
JoonHo Lee 36 0.6× 40 1.0× 24 1.2× 6 0.3× 6 0.8× 12 121
Jonas Wulff 212 3.4× 21 0.5× 24 1.2× 25 1.4× 6 0.8× 6 251
Saba Dadsetan 182 2.9× 34 0.9× 29 1.4× 7 0.4× 18 2.3× 6 247
Kangfu Mei 201 3.2× 26 0.7× 11 0.6× 14 0.8× 12 242
Tanvir Fatima Naik Bukht 98 1.6× 81 2.1× 66 3.3× 10 0.6× 3 0.4× 15 216

Countries citing papers authored by Maha Sallam

Since Specialization
Citations

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

Fields of papers citing papers by Maha Sallam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maha Sallam

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

All Works

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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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