Mihaela Breaban

50 total papers · 571 total citations
27 papers, 312 citations indexed

About

Mihaela Breaban is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Mihaela Breaban has authored 27 papers receiving a total of 312 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Computer Networks and Communications. Recurrent topics in Mihaela Breaban's work include Metaheuristic Optimization Algorithms Research (7 papers), Face and Expression Recognition (5 papers) and Advanced Clustering Algorithms Research (4 papers). Mihaela Breaban is often cited by papers focused on Metaheuristic Optimization Algorithms Research (7 papers), Face and Expression Recognition (5 papers) and Advanced Clustering Algorithms Research (4 papers). Mihaela Breaban collaborates with scholars based in Romania, United States and Italy. Mihaela Breaban's co-authors include Henri Luchian, Constantin Crânganu, Adrian Iftene, Radu Miron, Marco Grangetto, Chih–Chung Hsu, Fadi Dornaika, Talha Anwar, Alessandro Ortis and Sebastiano Battiato and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Pattern Recognition.

In The Last Decade

Mihaela Breaban

19 papers receiving 298 citations

Author Peers

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

Author						Papers	Cites
Mihaela Breaban	181	44	44	43	43	27	312
Rui Zhang	123 0.7×	49 1.1×	21 0.5×	24 0.6×	44 1.0×	28	303
Yevgeniya Kovalchuk	101 0.6×	38 0.9×	42 1.0×	25 0.6×	19 0.4×	26	331
Jianjian Yang	107 0.6×	22 0.5×	18 0.4×	28 0.7×	43 1.0×	26	306
Samaneh Yazdani	151 0.8×	23 0.5×	36 0.8×	19 0.4×	56 1.3×	16	338
Feng Yue	54 0.3×	29 0.7×	25 0.6×	33 0.8×	43 1.0×	18	311
Gabriel Spadon	61 0.3×	27 0.6×	51 1.2×	17 0.4×	21 0.5×	30	272
Naresh Iyer	80 0.4×	12 0.3×	30 0.7×	17 0.4×	36 0.8×	31	283
Gözde Ulutagay	140 0.8×	37 0.8×	10 0.2×	11 0.3×	66 1.5×	26	307
Chao Liu	109 0.6×	88 2.0×	17 0.4×	14 0.3×	15 0.3×	26	362
Ke-Thia Yao	110 0.6×	42 1.0×	89 2.0×	9 0.2×	21 0.5×	31	266

Countries citing papers authored by Mihaela Breaban

Since Specialization

Citations

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

Fields of papers citing papers by Mihaela Breaban

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mihaela Breaban

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