Home
I am a doctorate student at École de technologie supérieure (ÉTS) under the supervision of Prof.Eric Granger. My research interest focused on multi-source, gradual, and source-free domain adaptation. My main research focus is investigating human behavioral changes in weakly-labeled videos using unsupervised domain adaptation. Also, to develop new benchmark datasets for ambivalence recognition by collaborating with the behavioral sciences teams at Concordia university and Montreal Behaviour Medicine Center (MBMC).
Research interests:
- Machine learning
- Computer vision
- Weakly supervised/Unsupervised learning
- Domain adaptation
- Facial expression recognition
- Ambivalence detection
- Multi-instance learning
Research areas:
Project title:
- Personalized Automated Emotion Recognition and Ambivalence using Domain Adaptation
Name of advisor:
- Professor Eric Granger
Code and Publications
GitHub:
List of publications:
-
- Praveen, R. G., de Melo, W. C., Ullah, N., Aslam, H., Zeeshan, O., Denorme, T., … & Granger, E. (2022). A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2486-2495).
- Zeeshan, M. O., Siddiqi, I., & Moetesum, M. (2021, September). Two-Step Fine-Tuned Convolutional Neural Networks for Multi-label Classification of Children’s Drawings. In International Conference on Document Analysis and Recognition (pp. 321-334). Springer, Cham.
- Mirza, A., Zeshan, O., Atif, M., & Siddiqi, I. (2020). Detection and recognition of cursive text from video frames. EURASIP Journal on Image and Video Processing, 2020(1), 1-19.
Research & Innovation
Contact Us
Pavillon Principal (A)
1100, rue Notre-Dame Ouest
Montréal, QC, H3C 1K3
Room A-3600
Tel.: +1 (514) 396-8650
E-Mail: eric.granger@etsmtl.ca