62 citations · 204 across the 55 of their papers we have counts for
7 papers · 1 filter
Reconstructing Deep Neural Networks: Unleashing the Optimization Potential of Natural Gradient Descent
Weihua Liu, Said Boumaraf, Jianwu Li +4
Natural gradient descent (NGD) is a powerful optimization technique for machine learning, but the computational complexity of the inverse Fisher information matrix limits its appli…
BENet: A Cross-domain Robust Network for Detecting Face Forgeries via Bias Expansion and Latent-space Attention
Weihua Liu, Jianhua Qiu, Said Boumaraf +5
In response to the growing threat of deepfake technology, we introduce BENet, a Cross-Domain Robust Bias Expansion Network. BENet enhances the detection of fake faces by addressing…
Advancing Histopathology with Deep Learning Under Data Scarcity: A Decade in Review
Ahmad Obeid, Said Boumaraf, Anabia Sohail +5
Recent years witnessed remarkable progress in computational histopathology, largely fueled by deep learning. This brought the clinical adoption of deep learning-based tools within…
Video Anomaly Detection in 10 Years: A Survey and Outlook
Moshira Abdalla, Sajid Javed, Muaz Al Radi +2
Video anomaly detection (VAD) holds immense importance across diverse domains such as surveillance, healthcare, and environmental monitoring. While numerous surveys focus on conven…
CPLIP: Zero-Shot Learning for Histopathology with Comprehensive Vision-Language Alignment
Sajid Javed, Arif Mahmood, Iyyakutti Iyappan Ganapathi +3
This paper proposes Comprehensive Pathology Language Image Pre-training (CPLIP), a new unsupervised technique designed to enhance the alignment of images and text in histopathology…
RobMOT: Robust 3D Multi-Object Tracking by Observational Noise and State Estimation Drift Mitigation on LiDAR PointCloud
Mohamed Nagy, Naoufel Werghi, Bilal Hassan +2
This paper addresses limitations in 3D tracking-by-detection methods, particularly in identifying legitimate trajectories and reducing state estimation drift in Kalman filters. Exi…
A Robust Adversary Detection-Deactivation Method for Metaverse-oriented Collaborative Deep Learning
Pengfei Li, Zhibo Zhang, Ameena S. Al-Sumaiti +2
Metaverse is trending to create a digital circumstance that can transfer the real world to an online platform supported by large quantities of real-time interactions. Pre-trained A…