Mohammad Saberian

30 total papers · 1.3k total citations
19 papers, 240 citations indexed

About

Mohammad Saberian is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Mohammad Saberian has authored 19 papers receiving a total of 240 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 2 papers in Computational Mechanics. Recurrent topics in Mohammad Saberian's work include Face and Expression Recognition (7 papers), Machine Learning and Data Classification (6 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Mohammad Saberian is often cited by papers focused on Face and Expression Recognition (7 papers), Machine Learning and Data Classification (6 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Mohammad Saberian collaborates with scholars based in United States, Iran and United Kingdom. Mohammad Saberian's co-authors include Nuno Vasconcelos, Mohammad Ali Akhaee, Farokh Marvasti, Zhaowei Cai, Soheil Feizi, Hamed Masnadi-Shirazi, Oscar Beijbom, David Kriegman, Justin Basilico and Maarten van Someren and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Machine Learning Research and IEEE Transactions on Multimedia.

In The Last Decade

Mohammad Saberian

18 papers receiving 227 citations

Author Peers

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

Author						Papers	Cites
Mohammad Saberian	169	113	21	14	9	19	240
Zhilong Ji	174 1.0×	71 0.6×	16 0.8×	14 1.0×	8 0.9×	20	251
Jhony H. Giraldo	145 0.9×	83 0.7×	9 0.4×	14 1.0×	9 1.0×	27	237
Hanshu Yan	138 0.8×	104 0.9×	17 0.8×	14 1.0×	11 1.2×	11	226
Qian Zhang	237 1.4×	102 0.9×	20 1.0×	7 0.5×	12 1.3×	26	312
Yan Lü	86 0.5×	50 0.4×	39 1.9×	16 1.1×	19 2.1×	20	171
Kunlin Liu	208 1.2×	110 1.0×	25 1.2×	28 2.0×	3 0.3×	17	287
Luke Metz	139 0.8×	104 0.9×	17 0.8×	5 0.4×	4 0.4×	12	223
Ürün Doǧan	67 0.4×	118 1.0×	17 0.8×	14 1.0×	4 0.4×	14	188
Paul Hongsuck Seo	230 1.4×	115 1.0×	20 1.0×	3 0.2×	8 0.9×	15	307
Jiacheng Chen	199 1.2×	140 1.2×	11 0.5×	3 0.2×	5 0.6×	16	268

Countries citing papers authored by Mohammad Saberian

Since Specialization

Citations

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

Fields of papers citing papers by Mohammad Saberian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Saberian

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Saberian. A scholar is included among the top collaborators of Mohammad Saberian 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 Mohammad Saberian. Mohammad Saberian 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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