2 citations · 5 across the 11 of their papers we have counts for
11 papers
A Dual-Domain Convolutional Network for Hyperspectral Single-Image Super-Resolution
Murat Karayaka, Usman Muhammad, Jorma Laaksonen +2
This study presents a lightweight dual-domain super-resolution network (DDSRNet) that combines Spatial-Net with the discrete wavelet transform (DWT). Specifically, our proposed mod…
Hybrid Deep Learning for Hyperspectral Single Image Super-Resolution
Usman Muhammad, Jorma Laaksonen
Hyperspectral single image super-resolution (SISR) is a challenging task due to the difficulty of restoring fine spatial details while preserving spectral fidelity across a wide ra…
DACN: Dual-Attention Convolutional Network for Hyperspectral Image Super-Resolution
Usman Muhammad, Jorma Laaksonen
2D convolutional neural networks (CNNs) have attracted significant attention for hyperspectral image super-resolution tasks. However, a key limitation is their reliance on local ne…
A Fusion-Guided Inception Network for Hyperspectral Image Super-Resolution
Usman Muhammad, Jorma Laaksonen
The fusion of low-spatial-resolution hyperspectral images (HSIs) with high-spatial-resolution conventional images (e.g., panchromatic or RGB) has played a significant role in recen…
Towards Lightweight Hyperspectral Image Super-Resolution with Depthwise Separable Dilated Convolutional Network
Usman Muhammad, Jorma Laaksonen, Lyudmila Mihaylova
Deep neural networks have demonstrated highly competitive performance in super-resolution (SR) for natural images by learning mappings from low-resolution (LR) to high-resolution (…
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…
Saliency-based Video Summarization for Face Anti-spoofing
Usman Muhammad, Mourad Oussalah, Jorma Laaksonen
With the growing availability of databases for face presentation attack detection, researchers are increasingly focusing on video-based face anti-spoofing methods that involve hund…
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…