2 citations · 5 across the 6 of their papers we have counts for
6 papers
Classification of 24-hour movement behaviors from wrist-worn accelerometer data: from handcrafted features to deep learning techniques
Alireza Sameh, Mehrdad Rostami, Mourad Oussalah +1
Purpose: We compared the performance of deep learning (DL) and classical machine learning (ML) algorithms for the classification of 24-hour movement behavior into sleep, sedentary,…
Semi-Supervised learning for Face Anti-Spoofing using Apex frame
Usman Muhammad, Mourad Oussalah, Jorma Laaksonen
Conventional feature extraction techniques in the face anti-spoofing domain either analyze the entire video sequence or focus on a specific segment to improve model performance. Ho…
Deep Ensemble Learning with Frame Skipping for Face Anti-Spoofing
Usman Muhammad, Md Ziaul Hoque, Mourad Oussalah +1
Face presentation attacks (PA), also known as spoofing attacks, pose a substantial threat to biometric systems that rely on facial recognition systems, such as access control syste…
Domain Generalization via Ensemble Stacking for Face Presentation Attack Detection
Usman Muhammad, Jorma Laaksonen, Djamila Romaissa Beddiar +1
Face Presentation Attack Detection (PAD) plays a pivotal role in securing face recognition systems against spoofing attacks. Although great progress has been made in designing face…
Face Anti-Spoofing from the Perspective of Data Sampling
Usman Muhammad, Mourad Oussalah
Without deploying face anti-spoofing countermeasures, face recognition systems can be spoofed by presenting a printed photo, a video, or a silicon mask of a genuine user. Thus, fac…
Self-Supervised Face Presentation Attack Detection with Dynamic Grayscale Snippets
Usman Muhammad, Mourad Oussalah
Face presentation attack detection (PAD) plays an important role in defending face recognition systems against presentation attacks. The success of PAD largely relies on supervised…