2 citations · 6 across the 9 of their papers we have counts for
6 papers · 1 filter
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…
Implicit to Explicit Entropy Regularization: Benchmarking ViT Fine-tuning under Noisy Labels
Maria Marrium, Arif Mahmood, Mohammed Bennamoun
Automatic annotation of large-scale datasets can introduce noisy training data labels, which adversely affect the learning process of deep neural networks (DNNs). Consequently, Noi…
DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action Recognition
Qi Wang, Zhou Xu, Yuming Lin +6
Neuromorphic sensors, specifically event cameras, revolutionize visual data acquisition by capturing pixel intensity changes with exceptional dynamic range, minimal latency, and en…
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…
Language Model Guided Interpretable Video Action Reasoning
Ning Wang, Guangming Zhu, HS Li +3
While neural networks have excelled in video action recognition tasks, their black-box nature often obscures the understanding of their decision-making processes. Recent approaches…