Parvin Razzaghi

885 total citations
24 papers, 581 citations indexed

About

Parvin Razzaghi is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Parvin Razzaghi has authored 24 papers receiving a total of 581 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 8 papers in Molecular Biology and 8 papers in Artificial Intelligence. Recurrent topics in Parvin Razzaghi's work include Advanced Image and Video Retrieval Techniques (11 papers), Computational Drug Discovery Methods (8 papers) and Image Retrieval and Classification Techniques (7 papers). Parvin Razzaghi is often cited by papers focused on Advanced Image and Video Retrieval Techniques (11 papers), Computational Drug Discovery Methods (8 papers) and Image Retrieval and Classification Techniques (7 papers). Parvin Razzaghi collaborates with scholars based in Iran, Canada and Finland. Parvin Razzaghi's co-authors include Karim Abbasi, Ali Masoudi‐Nejad, Antti Poso, Jahan B. Ghasemi, Massoud Amanlou, Sajjad Gharaghani, Shadrokh Samavi, Shima Rashidi, Fatemeh Rafiei and Hojjat Zeraati and has published in prestigious journals such as Bioinformatics, Scientific Reports and Pharmacological Reviews.

In The Last Decade

Parvin Razzaghi

21 papers receiving 571 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Parvin Razzaghi Iran 11 339 328 133 92 91 24 581
Karim Abbasi Iran 15 455 1.3× 446 1.4× 180 1.4× 51 0.6× 108 1.2× 21 722
Qiujie Lv China 14 266 0.8× 275 0.8× 148 1.1× 48 0.5× 99 1.1× 23 543
Ziduo Yang China 15 460 1.4× 485 1.5× 239 1.8× 65 0.7× 121 1.3× 26 809
Ruihan Yang China 9 335 1.0× 344 1.0× 126 0.9× 70 0.8× 49 0.5× 31 610
Alireza Mehridehnavi Iran 13 134 0.4× 171 0.5× 81 0.6× 166 1.8× 74 0.8× 32 733
Joseph Luttrell United States 9 157 0.5× 138 0.4× 37 0.3× 109 1.2× 212 2.3× 17 523
Christian Feldmann Germany 14 114 0.3× 155 0.5× 81 0.6× 122 1.3× 40 0.4× 38 427
Qurrat Ul Ain New Zealand 10 305 0.9× 308 0.9× 113 0.8× 28 0.3× 76 0.8× 28 584
Limeng Pu United States 12 215 0.6× 211 0.6× 65 0.5× 17 0.2× 38 0.4× 27 419
Marcos Gestal Spain 13 131 0.4× 91 0.3× 25 0.2× 32 0.3× 59 0.6× 40 402

Countries citing papers authored by Parvin Razzaghi

Since Specialization
Citations

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

Fields of papers citing papers by Parvin Razzaghi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Parvin Razzaghi

This figure shows the co-authorship network connecting the top 25 collaborators of Parvin Razzaghi. A scholar is included among the top collaborators of Parvin Razzaghi 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 Parvin Razzaghi. Parvin Razzaghi 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
1.
Abbasi, Karim, et al.. (2025). DFT_ANPD: A dual-feature two-sided attention network for anticancer natural products detection. Computers in Biology and Medicine. 194. 110442–110442. 3 indexed citations
2.
3.
Razzaghi, Parvin, et al.. (2025). Integrating convolutional layers and biformer network with forward-forward and backpropagation training. Scientific Reports. 15(1). 7230–7230.
4.
Abbasi, Karim, et al.. (2024). CCL-DTI: contributing the contrastive loss in drug–target interaction prediction. BMC Bioinformatics. 25(1). 48–48. 43 indexed citations
5.
Rafiei, Fatemeh, Hojjat Zeraati, Karim Abbasi, et al.. (2024). CFSSynergy: Combining Feature-Based and Similarity-Based Methods for Drug Synergy Prediction. Journal of Chemical Information and Modeling. 64(7). 2577–2585. 29 indexed citations
6.
Razzaghi, Parvin, et al.. (2023). TripletMultiDTI: Multimodal representation learning in drug-target interaction prediction with triplet loss function. Expert Systems with Applications. 232. 120754–120754. 58 indexed citations
7.
Abbasi, Karim, et al.. (2023). DeepCompoundNet: enhancing compound–protein interaction prediction with multimodal convolutional neural networks. Journal of Biomolecular Structure and Dynamics. 43(3). 1414–1423. 23 indexed citations
8.
Razzaghi, Parvin, et al.. (2022). Multimodal brain tumor detection using multimodal deep transfer learning. Applied Soft Computing. 129. 109631–109631. 43 indexed citations
9.
Abbasi, Karim, et al.. (2020). Deep Learning in Drug Target Interaction Prediction: Current and Future Perspectives. Current Medicinal Chemistry. 28(11). 2100–2113. 71 indexed citations
10.
Abbasi, Karim & Parvin Razzaghi. (2020). Incorporating part-whole hierarchies into fully convolutional network for scene parsing. Expert Systems with Applications. 160. 113662–113662. 7 indexed citations
11.
Razzaghi, Parvin, et al.. (2018). Transfer subspace learning via low-rank and discriminative reconstruction matrix. Knowledge-Based Systems. 163. 174–185. 32 indexed citations
12.
Razzaghi, Parvin. (2018). Self-taught support vector machines. Knowledge and Information Systems. 59(3). 685–709. 9 indexed citations
13.
Razzaghi, Parvin, et al.. (2018). Parametric and nonparametric context models: A unified approach to scene parsing. Pattern Recognition. 84. 165–181. 8 indexed citations
14.
Razzaghi, Parvin, et al.. (2018). Weakly Supervised Semantic Segmentation Using Hierarchical Multi-Image Model. 1634–1640. 2 indexed citations
15.
Razzaghi, Parvin, et al.. (2017). Incorporation of High Level Information in Images Retrieval. 297–302.
16.
Razzaghi, Parvin, et al.. (2017). Similarity based context for nonparametric scene parsing. 1509–1514. 1 indexed citations
17.
Razzaghi, Parvin & Shadrokh Samavi. (2014). Image retargeting using nonparametric semantic segmentation. Multimedia Tools and Applications. 74(24). 11517–11536. 8 indexed citations
18.
Nejati, Mansour, et al.. (2013). Bag of visual words approach for image retrieval using color information. 1–6. 14 indexed citations
19.
Razzaghi, Parvin, et al.. (2013). Texture classification using dominant gradient descriptor. 31. 100–104. 3 indexed citations
20.
Razzaghi, Parvin, Maziar Palhang, & Niloofar Gheissari. (2012). A new invariant descriptor for action recognition based on spherical harmonics. Pattern Analysis and Applications. 16(4). 507–518. 7 indexed citations

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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