57 citations · 118 across the 19 of their papers we have counts for
21 papers
Automatic diagnosis of knee osteoarthritis severity using Swin transformer
Aymen Sekhri, Marouane Tliba, Mohamed Amine Kerkouri +4
Knee osteoarthritis (KOA) is a widespread condition that can cause chronic pain and stiffness in the knee joint. Early detection and diagnosis are crucial for successful clinical i…
Transformer with Selective Shuffled Position Embedding and Key-Patch Exchange Strategy for Early Detection of Knee Osteoarthritis
Zhe Wang, Aladine Chetouani, Mohamed Jarraya +2
Knee OsteoArthritis (KOA) is a widespread musculoskeletal disorder that can severely impact the mobility of older individuals. Insufficient medical data presents a significant obst…
Quality evaluation of point clouds: a novel no-reference approach using transformer-based architecture
Marouane Tliba, Aladine Chetouani, Giuseppe Valenzise +1
With the increased interest in immersive experiences, point cloud came to birth and was widely adopted as the first choice to represent 3D media. Besides several distortions that c…
Confidence-Driven Deep Learning Framework for Early Detection of Knee Osteoarthritis
Zhe Wang, Aladine Chetouani, Yung Hsin Chen +7
Knee Osteoarthritis (KOA) is a prevalent musculoskeletal disorder that severely impacts mobility and quality of life, particularly among older adults. Its diagnosis often relies on…
Kernel function impact on convolutional neural networks
M. Amine Mahmoudi, Aladine Chetouani, Fatma Boufera +1
This paper investigates the usage of kernel functions at the different layers in a convolutional neural network. We carry out extensive studies of their impact on convolutional, po…
BASICS: Broad quality Assessment of Static point clouds In Compression Scenarios
Ali Ak, Emin Zerman, Maurice Quach +4
Point clouds have become increasingly prevalent in representing 3D scenes within virtual environments, alongside 3D meshes. Their ease of capture has facilitated a wide array of ap…
Objective quality assessment of medical images and videos: Review and challenges
Rafael Rodrigues, Lucie Lévêque, Jesús Gutiérrez +7
Quality assessment is a key element for the evaluation of hardware and software involved in image and video acquisition, processing, and visualization. In the medical field, user-b…
PCQA-GRAPHPOINT: Efficients Deep-Based Graph Metric For Point Cloud Quality Assessment
Marouane Tliba, Aladine Chetouani, Giuseppe Valenzise +1
Following the advent of immersive technologies and the increasing interest in representing interactive geometrical format, 3D Point Clouds (PC) have emerged as a promising solution…
End-to-end deep multi-score model for No-reference stereoscopic image quality assessment
Oussama Messai, Aladine Chetouani
Deep learning-based quality metrics have recently given significant improvement in Image Quality Assessment (IQA). In the field of stereoscopic vision, information is evenly distri…
An Inter-observer consistent deep adversarial training for visual scanpath prediction
Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani +1
The visual scanpath is a sequence of points through which the human gaze moves while exploring a scene. It represents the fundamental concepts upon which visual attention research…
Deep-based quality assessment of medical images through domain adaptation
Marouane Tliba, Aymen Sekhri, Mohamed Amine Kerkouri +1
Predicting the quality of multimedia content is often needed in different fields. In some applications, quality metrics are crucial with a high impact, and can affect decision maki…
A domain adaptive deep learning solution for scanpath prediction of paintings
Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani +1
Cultural heritage understanding and preservation is an important issue for society as it represents a fundamental aspect of its identity. Paintings represent a significant part of…
SalyPath360: Saliency and Scanpath Prediction Framework for Omnidirectional Images
Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani +1
This paper introduces a new framework to predict visual attention of omnidirectional images. The key setup of our architecture is the simultaneous prediction of the saliency map an…
A Simple and efficient deep Scanpath Prediction
Mohamed Amine Kerkouri, Aladine Chetouani
Visual scanpath is the sequence of fixation points that the human gaze travels while observing an image, and its prediction helps in modeling the visual attention of an image. To t…
Learnable Triangulation for Deep Learning-based 3D Reconstruction of Objects of Arbitrary Topology from Single RGB Images
Tarek Ben Charrada, Hedi Tabia, Aladine Chetouani +1
We propose a novel deep reinforcement learning-based approach for 3D object reconstruction from monocular images. Prior works that use mesh representations are template based. Thus…
SALYPATH: A Deep-Based Architecture for visual attention prediction
Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani +1
Human vision is naturally more attracted by some regions within their field of view than others. This intrinsic selectivity mechanism, so-called visual attention, is influenced by…
A Multi-task convolutional neural network for blind stereoscopic image quality assessment using naturalness analysis
Salima Bourbia, Ayoub Karine, Aladine Chetouani +1
This paper addresses the problem of blind stereoscopic image quality assessment (NR-SIQA) using a new multi-task deep learning based-method. In the field of stereoscopic vision, th…
A deep perceptual metric for 3D point clouds
Maurice Quach, Aladine Chetouani, Giuseppe Valenzise +1
Point clouds are essential for storage and transmission of 3D content. As they can entail significant volumes of data, point cloud compression is crucial for practical usage. Recen…
Kernelized dense layers for facial expression recognition
M. Amine Mahmoudi, Aladine Chetouani, Fatma Boufera +1
Fully connected layer is an essential component of Convolutional Neural Networks (CNNs), which demonstrates its efficiency in computer vision tasks. The CNN process usually starts…
Blind Robust 3-D Mesh Watermarking based on Mesh Saliency and QIM quantization for Copyright Protection
Mohamed Hamidi, Aladine Chetouani, Mohamed El Haziti +2
Due to the recent demand of 3-D models in several applications like medical imaging, video games, among others, the necessity of implementing 3-D mesh watermarking schemes aiming t…
A Robust Blind 3-D Mesh Watermarking technique based on SCS quantization and mesh Saliency for Copyright Protection
Mohamed Hamidi, Aladine Chetouani, Mohamed El Haziti1 +2
Due to the recent demand of 3-D meshes in a wide range of applications such as video games, medical imaging, film special effect making, computer-aided design (CAD), among others,…