Ehsan Nowroozi

660 total citations
25 papers, 296 citations indexed

About

Ehsan Nowroozi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Ehsan Nowroozi has authored 25 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 7 papers in Signal Processing. Recurrent topics in Ehsan Nowroozi's work include Digital Media Forensic Detection (13 papers), Adversarial Robustness in Machine Learning (10 papers) and Advanced Steganography and Watermarking Techniques (7 papers). Ehsan Nowroozi is often cited by papers focused on Digital Media Forensic Detection (13 papers), Adversarial Robustness in Machine Learning (10 papers) and Advanced Steganography and Watermarking Techniques (7 papers). Ehsan Nowroozi collaborates with scholars based in Italy, United Kingdom and Türkiye. Ehsan Nowroozi's co-authors include Mauro Barni, Benedetta Tondi, Mauro Conti, Kim‐Kwang Raymond Choo, Ali Dehghantanha, Reza M. Parizi, A. Costanzo, Abdeslam El Fergougui, Rakesh Shrestha and Kassem Kallas and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers & Security and Multimedia Tools and Applications.

In The Last Decade

Ehsan Nowroozi

22 papers receiving 279 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ehsan Nowroozi Italy 10 159 121 91 90 57 25 296
N. R. Sunitha India 9 140 0.9× 45 0.4× 45 0.5× 76 0.8× 102 1.8× 57 251
Aleksandra Mileva North Macedonia 8 136 0.9× 88 0.7× 67 0.7× 107 1.2× 43 0.8× 32 256
Xueluan Gong China 13 326 2.1× 62 0.5× 92 1.0× 124 1.4× 44 0.8× 30 407
Benjamin Zi Hao Zhao Australia 8 274 1.7× 77 0.6× 103 1.1× 66 0.7× 39 0.7× 16 345
Christopher A. Choquette-Choo United States 6 302 1.9× 84 0.7× 33 0.4× 47 0.5× 67 1.2× 10 406
Andrea Paudice Italy 4 276 1.7× 31 0.3× 89 1.0× 95 1.1× 47 0.8× 5 336
Syh‐Yuan Tan Malaysia 8 152 1.0× 65 0.5× 44 0.5× 86 1.0× 115 2.0× 38 253
Konstantin Böttinger Germany 8 188 1.2× 63 0.5× 221 2.4× 79 0.9× 166 2.9× 23 406
Fanchao Qi China 12 482 3.0× 61 0.5× 136 1.5× 85 0.9× 68 1.2× 24 546
Songpon Teerakanok Japan 7 72 0.5× 100 0.8× 36 0.4× 75 0.8× 108 1.9× 19 252

Countries citing papers authored by Ehsan Nowroozi

Since Specialization
Citations

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

Fields of papers citing papers by Ehsan Nowroozi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ehsan Nowroozi

This figure shows the co-authorship network connecting the top 25 collaborators of Ehsan Nowroozi. A scholar is included among the top collaborators of Ehsan Nowroozi 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 Ehsan Nowroozi. Ehsan Nowroozi 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.
Nowroozi, Ehsan, et al.. (2025). A Random Deep Feature Selection Approach to Mitigate Transferable Adversarial Attacks. IEEE Transactions on Network and Service Management. 22(6). 5301–5310.
2.
Nowroozi, Ehsan, Imran Haider, Rahim Taheri, & Mauro Conti. (2025). Federated Learning Under Attack: Exposing Vulnerabilities Through Data Poisoning Attacks in Computer Networks. IEEE Transactions on Network and Service Management. 22(1). 822–831. 7 indexed citations
3.
Nowroozi, Ehsan, et al.. (2024). Mitigating Label Flipping Attacks in Malicious URL Detectors Using Ensemble Trees. IEEE Transactions on Network and Service Management. 21(6). 6875–6884. 3 indexed citations
4.
Nowroozi, Ehsan, et al.. (2024). Real or virtual: a video conferencing background manipulation-detection system. Multimedia Tools and Applications. 84(24). 28157–28189. 2 indexed citations
5.
Nowroozi, Ehsan, Kassem Kallas, & Alireza Jolfaei. (2024). Adversarial Multimedia Forensics. SPIRE - Sciences Po Institutional REpository. 4 indexed citations
6.
7.
Shrestha, Rakesh, et al.. (2024). Anomaly detection based on LSTM and autoencoders using federated learning in smart electric grid. Journal of Parallel and Distributed Computing. 193. 104951–104951. 38 indexed citations
8.
Nowroozi, Ehsan, et al.. (2024). SPRITZ-PS: validation of synthetic face images using a large dataset of printed documents. Multimedia Tools and Applications. 83(26). 67795–67823. 2 indexed citations
9.
Shrestha, Rakesh, et al.. (2023). Anomaly Detection Based on Lstm and Autoencoders Using Federated Learning in Smart Electric Grid. SSRN Electronic Journal. 3 indexed citations
10.
Balador, Ali, et al.. (2023). Balancing Privacy and Accuracy in Federated Learning for Speech Emotion Recognition. SHILAP Revista de lepidopterología. 35. 191–199. 4 indexed citations
11.
Nowroozi, Ehsan, et al.. (2023). Employing Deep Ensemble Learning for Improving the Security of Computer Networks Against Adversarial Attacks. IEEE Transactions on Network and Service Management. 20(2). 2096–2105. 8 indexed citations
12.
Nowroozi, Ehsan, et al.. (2022). Demystifying the Transferability of Adversarial Attacks in Computer Networks. IEEE Transactions on Network and Service Management. 19(3). 3387–3400. 30 indexed citations
13.
Ferreira, Anselmo, Ehsan Nowroozi, & Mauro Barni. (2021). VIPPrint: Validating Synthetic Image Detection and Source Linking Methods on a Large Scale Dataset of Printed Documents. Journal of Imaging. 7(3). 50–50. 11 indexed citations
14.
Barni, Mauro, Ehsan Nowroozi, & Benedetta Tondi. (2020). Improving the security of image manipulation detection through one-and-a-half-class multiple classification. Use Siena air (University of Siena). 6 indexed citations
15.
Barni, Mauro, et al.. (2020). Effectiveness of Random Deep Feature Selection for Securing Image Manipulation Detectors Against Adversarial Examples. Use Siena air (University of Siena). 2977–2981. 11 indexed citations
16.
Nowroozi, Ehsan, Ali Dehghantanha, Reza M. Parizi, & Kim‐Kwang Raymond Choo. (2020). A survey of machine learning techniques in adversarial image forensics. Computers & Security. 100. 102092–102092. 50 indexed citations
17.
Barni, Mauro, Kassem Kallas, Ehsan Nowroozi, & Benedetta Tondi. (2019). On the Transferability of Adversarial Examples against CNN-based Image Forensics. Use Siena air (University of Siena). 16 indexed citations
18.
Barni, Mauro, Ehsan Nowroozi, & Benedetta Tondi. (2018). Detection of adaptive histogram equalization robust against JPEG compression. Use Siena air (University of Siena). 1–8. 9 indexed citations
19.
Barni, Mauro, Ehsan Nowroozi, & Benedetta Tondi. (2017). Higher-order, adversary-aware, double JPEG-detection via selected training on attacked samples. Use Siena air (University of Siena). 281–285. 16 indexed citations
20.
Nowroozi, Ehsan & Ali Zakerolhosseini. (2015). Double JPEG Compression Detection Using Statistical Analysis. Advances in computer science : an international journal. 4(3). 70–76. 1 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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