Hamid Behravan

467 total citations
18 papers, 294 citations indexed

About

Hamid Behravan is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hamid Behravan has authored 18 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 7 papers in Signal Processing and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hamid Behravan's work include Speech Recognition and Synthesis (7 papers), AI in cancer detection (6 papers) and Speech and Audio Processing (4 papers). Hamid Behravan is often cited by papers focused on Speech Recognition and Synthesis (7 papers), AI in cancer detection (6 papers) and Speech and Audio Processing (4 papers). Hamid Behravan collaborates with scholars based in Finland, Iran and United States. Hamid Behravan's co-authors include Ville Hautamäki, Tomi Kinnunen, Veli‐Matti Kosma, Jaana M. Hartikainen, Maria Tengström, Saeed Mozaffari, Sabato Marco Siniscalchi, Chin‐Hui Lee, Robert Winqvist and Arto Mannermaa and has published in prestigious journals such as Scientific Reports, IEEE Access and Speech Communication.

In The Last Decade

Hamid Behravan

16 papers receiving 273 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hamid Behravan Finland 9 177 105 59 38 37 18 294
Yipei Wang United States 11 126 0.7× 38 0.4× 153 2.6× 29 0.8× 84 2.3× 17 316
Konstantinos Sechidis United Kingdom 10 109 0.6× 23 0.2× 69 1.2× 65 1.7× 9 0.2× 23 318
Hirokazu Masataki Japan 10 245 1.4× 93 0.9× 29 0.5× 27 0.7× 3 0.1× 44 333
Yang Ai China 11 119 0.7× 79 0.8× 164 2.8× 15 0.4× 24 0.6× 30 526
Ana F. Sequeira Portugal 11 41 0.2× 253 2.4× 222 3.8× 42 1.1× 22 0.6× 34 426
Tiago Gonçalves Portugal 9 65 0.4× 20 0.2× 84 1.4× 12 0.3× 38 1.0× 26 194
Md. Khayrul Bashar Japan 10 41 0.2× 58 0.6× 236 4.0× 17 0.4× 16 0.4× 34 416
Xiaoxue Gao Singapore 10 76 0.4× 74 0.7× 10 0.2× 53 1.4× 3 0.1× 32 191
Hua-Nong Ting Malaysia 10 128 0.7× 98 0.9× 12 0.2× 40 1.1× 14 0.4× 49 351
Ehab A. AlBadawy United States 8 177 1.0× 47 0.4× 69 1.2× 33 0.9× 168 4.5× 9 331

Countries citing papers authored by Hamid Behravan

Since Specialization
Citations

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

Fields of papers citing papers by Hamid Behravan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hamid Behravan

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

All Works

18 of 18 papers shown
1.
2.
Sudah, Mazen, et al.. (2024). A Multi-View Deep Evidential Learning Approach for Mammogram Density Classification. IEEE Access. 12. 67889–67909. 4 indexed citations
3.
Kosma, Veli‐Matti, et al.. (2023). Nuclei instance segmentation from histopathology images using Bayesian dropout based deep learning. BMC Medical Imaging. 23(1). 162–162. 8 indexed citations
4.
5.
Behravan, Hamid, Mazen Sudah, Hidemi Okuma, et al.. (2022). Area-based breast percentage density estimation in mammograms using weight-adaptive multitask learning. Scientific Reports. 12(1). 12060–12060. 7 indexed citations
6.
Behravan, Hamid, Mazen Sudah, Hidemi Okuma, et al.. (2021). Multi-level dilated residual network for biomedical image segmentation. Scientific Reports. 11(1). 14105–14105. 26 indexed citations
7.
Behravan, Hamid, et al.. (2020). Predicting breast cancer risk using interacting genetic and demographic factors and machine learning. Scientific Reports. 10(1). 11044–11044. 43 indexed citations
8.
Behravan, Hamid, Jaana M. Hartikainen, Maria Tengström, et al.. (2018). Machine learning identifies interacting genetic variants contributing to breast cancer risk: A case study in Finnish cases and controls. Scientific Reports. 8(1). 13149–13149. 46 indexed citations
9.
Behravan, Hamid, Tomi Kinnunen, & Ville Hautamäki. (2016). Out-of-Set i-Vector Selection for Open-set Language Identification. 303–310. 5 indexed citations
10.
Behravan, Hamid, Ville Hautamäki, Sabato Marco Siniscalchi, Tomi Kinnunen, & Chin‐Hui Lee. (2015). i-Vector Modeling of Speech Attributes for Automatic Foreign Accent Recognition. IEEE/ACM Transactions on Audio Speech and Language Processing. 24(1). 29–41. 22 indexed citations
11.
Hautamäki, Ville, et al.. (2015). Boosting universal speech attributes classification with deep neural network for foreign accent characterization. Nova Science Publishers (Nova Science Publishers, Inc.). 408–412. 19 indexed citations
12.
Behravan, Hamid, Ville Hautamäki, & Tomi Kinnunen. (2014). Factors affecting i-vector based foreign accent recognition: A case study in spoken Finnish. Speech Communication. 66. 118–129. 33 indexed citations
13.
Behravan, Hamid, et al.. (2014). Introducing attribute features to foreign accent recognition. Nova Science Publishers (Nova Science Publishers, Inc.). 5332–5336. 9 indexed citations
14.
Behravan, Hamid, et al.. (2014). Dialect levelling in Finnish: a universal speech attribute approach. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2165–2169. 6 indexed citations
15.
Behravan, Hamid & Karim Faez. (2013). Introducing a new multimodal database from twins' biometric traits. 1–6. 7 indexed citations
16.
Behravan, Hamid, Ville Hautamäki, & Tomi Kinnunen. (2013). Foreign accent detection from spoken Finnish using i-vectors. 79–83. 26 indexed citations
17.
Mozaffari, Saeed & Hamid Behravan. (2011). Twins facial similarity impact on conventional face recognition systems. Iranian Conference on Electrical Engineering. 1–1. 7 indexed citations
18.

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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