A Blinking Measurement Method for Driver Drowsiness Detection. - Belhassen Akrout; Walid Mahdi (CORES, 2013)

A visual based approach for drowsiness detection. - Belhassen Akrout; Walid Mahdi (Intelligent Vehicles Symposium, 2013)

Vision Based Approach for Driver Drowsiness Detection Based on 3D Head Orientation. - Belhassen Akrout; Walid Mahdi (MUE, 2013)

Drowsiness Detection based on Video Analysis Approach. - Belhassen Akrout; Walid Mahdi; Abdelmajid Ben Hamadou (VISAPP (1), 2013)

A new scheme of signature extraction for iris authentication - Belhassen Akrout; Imen Khanfir Kallel; Chokri Ben Amar (CoRR, 2013)

Hypovigilance Detection Based on Eyelids Behavior Study. - Belhassen Akrout; Walid Mahdi (Int. J. Recent Contributions Eng. Sci. IT, 2013)

Hypovigilance detection by calculating and analyzing a spatio-temporal features of the face components based on 3D head orientation. - Belhassen Akrout; Walid Mahdi (ATSIP, 2014)

A Visual Search of Multimedia Documents in ImageCLEF 2014. - Sana Fakhfakh; Belhassen Akrout; Mohamed Tmar; Walid Mahdi (CLEF (Working Notes), 2014)

Spatio-temporal features for the automatic control of driver drowsiness state and lack of concentration. - Belhassen Akrout; Walid Mahdi (Mach. Vis. Appl., 2015)

Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness. - Belhassen Akrout; Walid Mahdi (IPAS, 2016)

Clever use of Meyer wavelet for iris recognition. - Imene Khanfir Kallel; Sonda Ammar Bouhamed; Belhassen Akrout (ATSIP, 2017)

Automated Drowsiness Detection Through Facial Features Analysis. - Walid Mahdi; Belhassen Akrout; Roobaea Alroobaea; Abdulmajeed Alsufyani (Computación y Sistemas, 2019)

Shoppers Interaction Classification Based on An Improved DenseNet Model Using RGB-D Data. - Almustafa Abed; Belhassen Akrout; Ikram Amous (ICSAI, 2022)

A Novel Deep Convolutional Neural Network Architecture for Customer Counting in the Retail Environment. - Almustafa Abed; Belhassen Akrout; Ikram Amous (ISPR, 2022)

A novel approach for driver fatigue detection based on visual characteristics analysis. - Belhassen Akrout; Walid Mahdi (J. Ambient Intell. Humaniz. Comput., 2023)

Semantic Heads Segmentation and Counting in Crowded Retail Environment with Convolutional Neural Networks Using Top View Depth Images. - Almustafa Abed; Belhassen Akrout; Ikram Amous (SN Comput. Sci., 2023)

Deep learning-based few-shot person re-identification from top-view RGB and depth images. - Almustafa Abed; Belhassen Akrout; Ikram Amous (Neural Comput. Appl., 2024)

Deep facial emotion recognition model using optimal feature extraction and dual-attention residual U-Net classifier. - Belhassen Akrout (Expert Syst. J. Knowl. Eng., 2025)