Marcella Astrid

428 total citations
21 papers, 216 citations indexed

About

Marcella Astrid is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Marcella Astrid has authored 21 papers receiving a total of 216 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 4 papers in Computer Networks and Communications. Recurrent topics in Marcella Astrid's work include Advanced Neural Network Applications (8 papers), Anomaly Detection Techniques and Applications (7 papers) and Video Surveillance and Tracking Methods (4 papers). Marcella Astrid is often cited by papers focused on Advanced Neural Network Applications (8 papers), Anomaly Detection Techniques and Applications (7 papers) and Video Surveillance and Tracking Methods (4 papers). Marcella Astrid collaborates with scholars based in South Korea, Luxembourg and United Arab Emirates. Marcella Astrid's co-authors include Seung‐Ik Lee, Muhammad Zaigham Zaheer, Arif Mahmood, Jin Ha Lee, Djamila Aouada, Enjie Ghorbel, Beom-Su Seo, Muhammad Haris Khan, Inder Pal Singh and Dat Nguyen and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.

In The Last Decade

Marcella Astrid

19 papers receiving 209 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcella Astrid South Korea 8 132 114 54 40 28 21 216
Dmitry Molchanov Russia 4 134 1.0× 120 1.1× 10 0.2× 5 0.1× 4 0.1× 11 196
Kerui Min China 5 177 1.3× 81 0.7× 4 0.1× 6 0.1× 21 0.8× 6 289
Zheng Shou China 4 75 0.6× 198 1.7× 4 0.1× 8 0.2× 82 2.9× 10 253
Xinyang Yi United States 4 33 0.3× 32 0.3× 13 0.2× 4 0.1× 15 0.5× 7 112
Dian Gong United States 5 70 0.5× 139 1.2× 4 0.1× 2 0.1× 39 1.4× 10 187
Romaric Audigier France 8 80 0.6× 155 1.4× 14 0.3× 14 0.5× 22 188
Sadegh Mohammadi Iran 5 129 1.0× 128 1.1× 29 0.5× 20 0.7× 15 174
Haoyue Shi China 8 134 1.0× 63 0.6× 45 0.8× 15 0.5× 15 156
Vikas Verma Finland 9 181 1.4× 119 1.0× 8 0.1× 7 0.3× 13 241

Countries citing papers authored by Marcella Astrid

Since Specialization
Citations

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

Fields of papers citing papers by Marcella Astrid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcella Astrid

This figure shows the co-authorship network connecting the top 25 collaborators of Marcella Astrid. A scholar is included among the top collaborators of Marcella Astrid 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 Marcella Astrid. Marcella Astrid 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.
Astrid, Marcella, Enjie Ghorbel, & Djamila Aouada. (2025). Audio-Visual Deepfake Detection With Local Temporal Inconsistencies. Open Repository and Bibliography (University of Luxembourg). 1–5. 1 indexed citations
2.
Astrid, Marcella, Enjie Ghorbel, & Djamila Aouada. (2024). Statistics-Aware Audio-Visual Deepfake Detector. Open Repository and Bibliography (University of Luxembourg). 2557–2563. 2 indexed citations
3.
Nguyen, Dat, Inder Pal Singh, Marcella Astrid, et al.. (2024). LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection. Open Repository and Bibliography (University of Luxembourg). 17395–17405. 18 indexed citations
4.
Astrid, Marcella, Enjie Ghorbel, & Djamila Aouada. (2024). Targeted Augmented Data for Audio Deepfake Detection. Open Repository and Bibliography (University of Luxembourg). 346–350. 1 indexed citations
5.
Astrid, Marcella, Muhammad Zaigham Zaheer, Djamila Aouada, & Seung‐Ik Lee. (2024). Exploiting autoencoder’s weakness to generate pseudo anomalies. Neural Computing and Applications. 36(23). 14075–14091.
6.
Astrid, Marcella & Seung‐Ik Lee. (2023). Assembling three one‐camera images for three‐camera intersection classification. ETRI Journal. 45(5). 862–873. 1 indexed citations
7.
Astrid, Marcella, Muhammad Zaigham Zaheer, & Seung‐Ik Lee. (2023). PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies. Neurocomputing. 534. 147–160. 15 indexed citations
8.
Zaheer, Muhammad Zaigham, Arif Mahmood, Marcella Astrid, & Seung‐Ik Lee. (2023). Clustering Aided Weakly Supervised Training to Detect Anomalous Events in Surveillance Videos. IEEE Transactions on Neural Networks and Learning Systems. 35(10). 14085–14098. 25 indexed citations
9.
Zaheer, Muhammad Zaigham, Jin Ha Lee, Arif Mahmood, Marcella Astrid, & Seung‐Ik Lee. (2022). Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies. IEEE Transactions on Image Processing. 31. 5963–5975. 12 indexed citations
10.
Astrid, Marcella, Muhammad Zaigham Zaheer, & Seung‐Ik Lee. (2022). Limiting Reconstruction Capability of Autoencoders Using Moving Backward Pseudo Anomalies. 248–251. 4 indexed citations
11.
Zaheer, Muhammad Zaigham, Arif Mahmood, Muhammad Haris Khan, Marcella Astrid, & Seung‐Ik Lee. (2021). An Anomaly Detection System via Moving Surveillance Robots with Human Collaboration. 2595–2601. 16 indexed citations
12.
Astrid, Marcella, Muhammad Zaigham Zaheer, Jae-Yeong Lee, & Seung‐Ik Lee. (2021). Domain-Robust Pedestrian-View Intersection Classification. 2021 International Conference on Information and Communication Technology Convergence (ICTC). 17. 1087–1090. 1 indexed citations
13.
Lee, Jin Ha, Muhammad Zaigham Zaheer, Marcella Astrid, & Seung‐Ik Lee. (2020). SmoothMix: a Simple Yet Effective Data Augmentation to Train Robust Classifiers. 3264–3274. 32 indexed citations
14.
Astrid, Marcella, Muhammad Zaigham Zaheer, Jin Ha Lee, Jae-Yeong Lee, & Seung‐Ik Lee. (2020). What Do Pedestrians See?: Visualizing Pedestrian-View Intersection Classification. 769–773. 1 indexed citations
15.
Astrid, Marcella, Jin Ha Lee, Muhammad Zaigham Zaheer, Jae-Yeong Lee, & Seung‐Ik Lee. (2020). For Safer Navigation: Pedestrian-View Intersection Classification. 7–10. 3 indexed citations
16.
Lee, Jinsu, et al.. (2018). CNN based Sentence Classification with Semantic Features using Word Clustering. 484–488. 5 indexed citations
17.
Astrid, Marcella, Seung‐Ik Lee, & Beom-Su Seo. (2018). Rank selection of CP-decomposed convolutional layers with variational Bayesian matrix factorization. 2018 20th International Conference on Advanced Communication Technology (ICACT). 1–1. 7 indexed citations
18.
Astrid, Marcella & Seung‐Ik Lee. (2018). Deep compression of convolutional neural networks with low-rank approximation. ETRI Journal. 40(4). 421–434. 13 indexed citations
19.
Astrid, Marcella & Seung‐Ik Lee. (2017). CP-decomposition with Tensor Power Method for Convolutional Neural Networks compression. 115–118. 52 indexed citations
20.
Astrid, Marcella, et al.. (1988). Temporal decomposition of speech: compactness measures compared. 1343–1350. 2 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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