Accueil › Annuaire des chercheurs › Sid Ahmed Fezza
Sid Ahmed Fezza
Affiliation : Ecole Nationale Supérieur des Télécommunications et des Technologies de l’Information et de la Communication, Abdelhafid Boussouf
- 52Publications (affiliation algérienne)
- 61Publications au total
- 879Citations
- 15Indice h
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Créer mon profil gratuit Ajouter mes publicationsDomaines de recherche
- Image and Video Quality Assessment
- Video Coding and Compression Technologies
- Digital Media Forensic Detection
- Adversarial Robustness in Machine Learning
- Advanced Data Compression Techniques
Publications (52)
- Does data augmentation help or hinder the generalization of deepfake video detection?
- Complexity prediction of hardware and software video transcoding in the cloud
- Convex Hull Prediction Methods for Bitrate Ladder Construction: Design, Evaluation, and Comparison
- Energy Backdoor Attack to Deep Neural Networks
- PCG Classification for Diseases Detection: Windowing vs. Heart Cycle Segmentation
- Deepfake Detection Using Spatiotemporal Transformer
- Energy Consumption and Carbon Emissions of Modern Software Video Encoders
- On the effectiveness of handcrafted features for deepfake video detection
- Energy Consumption and Carbon Footprint of Modern Video Decoding Software
- Efficient Per-Shot Transformer-Based Bitrate Ladder Prediction for Adaptive Video Streaming
- Evaluating the Vulnerability of Deep Learning-based Image Quality Assessment Methods to Adversarial Attacks
- Adversarial example detection for DNN models: a review and experimental comparison
- Evaluation of Pre-Trained CNN Models for Geographic Fake Image Detection
- Benchmarking Learning-based Bitrate Ladder Prediction Methods for Adaptive Video Streaming
- Hardware-Friendly Multiple Transform Selection Module for the VVC Standard
- Visual Security Evaluation of Perceptually Encrypted Images based on Multi-Task Learning
- NTIRE 2021 Challenge on Perceptual Image Quality Assessment
- HCiT: Deepfake Video Detection Using a Hybrid Model of CNN features and Vision Transformer
- Light Field Image Coding Using VVC Standard and View Synthesis Based on Dual Discriminator GAN
- Detect and defense against adversarial examples in deep learning using natural scene statistics and adaptive denoising
- EGB: Image Quality Assessment based on Ensemble of Gradient Boosting
- Deep multi-task learning for image/video distortions identification
- Visual Quality and Security Assessment of Perceptually Encrypted Images Based on Multi-Output Deep Neural Network
- Detection of Adversarial Examples in Deep Neural Networks with Natural Scene Statistics
- Light Field Image Coding Using Dual Discriminator Generative Adversarial Network And VVC Temporal Scalability
- Natural Scene Statistics for Detecting Adversarial Examples in Deep Neural Networks
- Effect of Video Transcoding Parameters on Visual Object Tracking for Surveillance Systems
- Light Field Image Coding Using Dual Discriminator Generative Adversarial Network and VVC Temporal Scalability
- DDSA: A Defense Against Adversarial Attacks Using Deep Denoising Sparse Autoencoder
- Perceptual Evaluation of Adversarial Attacks for CNN-based Image Classification
- Subjective Evaluation of Light Field Image Compression Methods based on View Synthesis
- RDO-Based Light Field Image Coding Using Convolutional Neural Networks and Linear Approximation
- Visual Security Assessment of Selective Video Encryption
- Using distortion and asymmetry determination for blind stereoscopic image quality assessment strategy
- Towards light-compensated saliency prediction for omnidirectional images
- Perceptually Driven Nonuniform Asymmetric Coding of Stereoscopic 3D Video
- Universal blind image quality assessment for stereoscopic images
- Adaptive colorization-based compression for stereoscopic images
- Color calibration of multi-view video plus depth for advanced 3D video
- Color Correction for Stereo and Multi-view Coding
- Feature-Based Color Correction of Multiview Video for Coding and Rendering Enhancement
- Stereoscopic image quality metric based on local entropy and binocular just noticeable difference
- Stereoscopic 3D image quality assessment based on cyclopean view and depth map
- Asymmetric coding using Binocular Just Noticeable Difference and depth information for stereoscopic 3D
- Asymmetric coding of stereoscopic 3D based on perceptual significance
- No-reference perceptual blur metric for stereoscopic images
- Stereo image coding: State of the art
- Coding and rendering enhancement of multi-view video by color correction
- Fast stereo matching via graph cuts
- A comparison of prediction structures for multi-view video coding based on the H.264/AVC standard
- New Prediction Structure for Stereoscopic Video Coding Based on the H.264/AVC Standard
- Stereoscopic video coding based on the H.264/AVC standard
Co-auteurs
- Kamel Mohamed Faraoun
- Bachir Kaddar
- Ghalem Belalem
- Samira Ouddane
- Taieb Chachou
- Dounia Hammou
- Mamadou Keïta
- Elhocine Boutellaa
- Yassine Bakhti
- anouar kherchouche
- Aymen Abderraouf Rahmani
- Reda Abdellah Kamraoui
Données bibliographiques issues d’OpenAlex (base ouverte).
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