Outputs (35)

STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation (2024)
Journal Article
Fang, M., Yu, L., Xie, H., Tan, Q., Tan, Z., Hussain, A., Wang, Z., Li, J., & Tian, Z. (2024). STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation. IEEE Transactions on Computational Social Systems, 11(4), 5354 - 5366. https://doi.org/10.1109/tcss.2024.3356549

The impressive development of facial manipulation techniques has raised severe public concerns. Identity-aware methods, especially suitable for protecting celebrities, are seen as one of promising face forgery detection approaches with additional ref... Read More about STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation.

RI-L1Approx: A novel Resnet-Inception-based Fast L1-approximation method for face recognition (2024)
Journal Article
Bajpai, S., Mishra, G., Jain, R., Jain, D. K., Saini, D., & Hussain, A. (2024). RI-L1Approx: A novel Resnet-Inception-based Fast L1-approximation method for face recognition. Neurocomputing, 613, Article 128708. https://doi.org/10.1016/j.neucom.2024.128708

Performance of deep learning methods for face recognition often relies on abundant data, posing challenges in surveillance and security where data availability is limited and environments are unconstrained. To address this challenge, we propose a nov... Read More about RI-L1Approx: A novel Resnet-Inception-based Fast L1-approximation method for face recognition.

Novel Category Discovery without Forgetting for Automatic Target Recognition (2024)
Journal Article
Huang, H., Gao, F., Sun, J., Wang, J., Hussain, A., & Zhou, H. (2024). Novel Category Discovery without Forgetting for Automatic Target Recognition. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 4408-4420. https://doi.org/10.1109/jstars.2024.3358449

We explore a cutting-edge concept known as C lass Incremental Learning in N ovel Category Discovery for Synthetic Aperture Radar T argets (CNT). This innovative task involves the challenge of identifying categories within unlabeled datasets by utiliz... Read More about Novel Category Discovery without Forgetting for Automatic Target Recognition.

Deep learning methods for early detection of Alzheimer’s disease using structural MR images: A survey (2024)
Journal Article
Hassen, S. B., Neji, M., Hussain, Z., Hussain, A., Alimi, A. M., & Frikha, M. (2024). Deep learning methods for early detection of Alzheimer’s disease using structural MR images: A survey. Neurocomputing, 576, Article 127325. https://doi.org/10.1016/j.neucom.2024.127325

In this paper, we present an extensive review of the most recent works for Alzheimer’s disease (AD) prediction, particularly Moderate Cognitive Impairment (MCI) conversion prediction. We aimed to identify the most useful brain-magnetic resonance imag... Read More about Deep learning methods for early detection of Alzheimer’s disease using structural MR images: A survey.

SAR Target Incremental Recognition Based on Features With Strong Separability (2024)
Journal Article
Gao, F., Kong, L., Lang, R., Sun, J., Wang, J., Hussain, A., & Zhou, H. (2024). SAR Target Incremental Recognition Based on Features With Strong Separability. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-13. https://doi.org/10.1109/tgrs.2024.3351636

With the rapid development of deep learning technology, many synthetic aperture radar (SAR) target recognition algorithms based on convolutional neural networks have achieved exceptional performance on various datasets. However, conventional neural n... Read More about SAR Target Incremental Recognition Based on Features With Strong Separability.