Mridula Vijendran

Durham University
PhD (Co-supervised with )
, 2021 - Present

Durham University
, UK
  • Research interests: Generative Networks, Semantic Analysis

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Grants Involved


Publications with the Team

BOOST: Out-of-Distribution-Informed Adaptive Sampling for Bias Mitigation in Stylistic Convolutional Neural Networks
BOOST: Out-of-Distribution-Informed Adaptive Sampling for Bias Mitigation in Stylistic Convolutional Neural Networks Impact Factor: 7.5Top 25% Journal in Computer Science, Artificial Intelligence
Expert Systems with Applications (ESWA), 2025
Mridula Vijendran, Shuang Chen, Jingjing Deng and Hubert P. H. Shum
Webpage Cite This Plain Text
Mridula Vijendran, Shuang Chen, Jingjing Deng and Hubert P. H. Shum, "BOOST: Out-of-Distribution-Informed Adaptive Sampling for Bias Mitigation in Stylistic Convolutional Neural Networks," Expert Systems with Applications, vol. 296, pp. 128905, Elsevier, 2025.
Bibtex
@article{vijendran25boost,
 author={Vijendran, Mridula and Chen, Shuang and Deng, Jingjing and Shum, Hubert P. H.},
 journal={Expert Systems with Applications},
 title={BOOST: Out-of-Distribution-Informed Adaptive Sampling for Bias Mitigation in Stylistic Convolutional Neural Networks},
 year={2025},
 volume={296},
 pages={128905},
 numpages={12},
 doi={10.1016/j.eswa.2025.128905},
 issn={0957-4174},
 publisher={Elsevier},
}
RIS
TY  - JOUR
AU  - Vijendran, Mridula
AU  - Chen, Shuang
AU  - Deng, Jingjing
AU  - Shum, Hubert P. H.
T2  - Expert Systems with Applications
TI  - BOOST: Out-of-Distribution-Informed Adaptive Sampling for Bias Mitigation in Stylistic Convolutional Neural Networks
PY  - 2025
VL  - 296
SP  - 128905
EP  - 128905
DO  - 10.1016/j.eswa.2025.128905
SN  - 0957-4174
PB  - Elsevier
ER  - 
Paper GitHub
Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey
Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey Impact Factor: 13.9Top 10% Journal in Computer Science, Artificial IntelligenceCitation: 10#
Artificial Intelligence Review (AIRE), 2024
Mridula Vijendran, Jingjing Deng, Shuang Chen, Edmond S. L. Ho and Hubert P. H. Shum
Webpage Cite This Plain Text
Mridula Vijendran, Jingjing Deng, Shuang Chen, Edmond S. L. Ho and Hubert P. H. Shum, "Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey," Artificial Intelligence Review, vol. 58, no. 2, pp. 64, Springer, 2024.
Bibtex
@article{vijendran25artificial,
 author={Vijendran, Mridula and Deng, Jingjing and Chen, Shuang and Ho, Edmond S. L. and Shum, Hubert P. H.},
 journal={Artificial Intelligence Review},
 title={Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey},
 year={2024},
 volume={58},
 number={2},
 pages={64},
 numpages={47},
 doi={10.1007/s10462-024-11051-3},
 issn={1573-7462},
 publisher={Springer},
}
RIS
TY  - JOUR
AU  - Vijendran, Mridula
AU  - Deng, Jingjing
AU  - Chen, Shuang
AU  - Ho, Edmond S. L.
AU  - Shum, Hubert P. H.
T2  - Artificial Intelligence Review
TI  - Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey
PY  - 2024
VL  - 58
IS  - 2
SP  - 64
EP  - 64
DO  - 10.1007/s10462-024-11051-3
SN  - 1573-7462
PB  - Springer
ER  - 
Paper
ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification
ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification
Book Chapter: Communications in Computer and Information Science (CCIS), 2024
Mridula Vijendran, Frederick W. B. Li, Jingjing Deng and Hubert P. H. Shum
Webpage Cite This Plain Text
Mridula Vijendran, Frederick W. B. Li, Jingjing Deng and Hubert P. H. Shum, "ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification," in CCIS '24: Communications in Computer and Information Science, pp. 181-205, Springer, 2024.
Bibtex
@incollection{vijendran24stsaclf,
 author={Vijendran, Mridula and Li, Frederick W. B. and Deng, Jingjing and Shum, Hubert P. H.},
 booktitle={Communications in Computer and Information Science},
 series={CCIS '24},
 title={ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification},
 year={2024},
 pages={181--205},
 numpages={25},
 doi={10.1007/978-3-031-66743-5_9},
 isbn={978-3-031-66743-5},
 publisher={Springer},
}
RIS
TY  - CHAP
AU  - Vijendran, Mridula
AU  - Li, Frederick W. B.
AU  - Deng, Jingjing
AU  - Shum, Hubert P. H.
T2  - Communications in Computer and Information Science
TI  - ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification
PY  - 2024
SP  - 181
EP  - 205
DO  - 10.1007/978-3-031-66743-5_9
SN  - 978-3-031-66743-5
PB  - Springer
ER  - 
Paper
Tackling Data Bias in Painting Classification with Style Transfer
Tackling Data Bias in Painting Classification with Style Transfer
Proceedings of the 2023 International Conference on Computer Vision Theory and Applications (VISAPP), 2023
Mridula Vijendran, Frederick W. B. Li and Hubert P. H. Shum
Webpage Cite This Plain Text
Mridula Vijendran, Frederick W. B. Li and Hubert P. H. Shum, "Tackling Data Bias in Painting Classification with Style Transfer," in VISAPP '23: Proceedings of the 2023 International Conference on Computer Vision Theory and Applications, pp. 250-261, Lisbon, Portugal, SciTePress, Feb 2023.
Bibtex
@inproceedings{vijendran23tackling,
 author={Vijendran, Mridula and Li, Frederick W. B. and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2023 International Conference on Computer Vision Theory and Applications},
 series={VISAPP '23},
 title={Tackling Data Bias in Painting Classification with Style Transfer},
 year={2023},
 month={2},
 pages={250--261},
 numpages={12},
 doi={10.5220/0011776600003417},
 issn={2184-4321},
 isbn={978-989-758-634-7},
 publisher={SciTePress},
 location={Lisbon, Portugal},
}
RIS
TY  - CONF
AU  - Vijendran, Mridula
AU  - Li, Frederick W. B.
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2023 International Conference on Computer Vision Theory and Applications
TI  - Tackling Data Bias in Painting Classification with Style Transfer
PY  - 2023
Y1  - 2 2023
SP  - 250
EP  - 261
DO  - 10.5220/0011776600003417
SN  - 2184-4321
PB  - SciTePress
ER  - 
Paper GitHub

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