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22nd International Conference on Cyberworlds, CW 2023

作者： Boujnah, Sana Ferjaoui, Radhia Khalifa, Anouar Ben University of Tunis El Manar National Engineering School of Tunis Tunisia NOCCS-Laboratory of Networked Objects Control and Communication Systems Eniso Tunisia Istmt Tunis Tunisia Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia Université de Jendouba Institut National des Technologies et des Sciences du Kef Le Kef7100 Tunisia

ISBN: (纸本)9798350315653

Since the smartphone is adapted to the ambient intelligence and the smart home systems are remotely accessed through the smartphones, there is a need for a secure authentication system based on some biometrics proprieties that can be taken from a smartphone. The identification of persons through ear and voice print is one of the basic biometric matters. The earlier research in ear recognition have shown that human ear is one of the representative human biometrics with uniqueness and stability. Indeed, the human voice is a perfect source of data for person identification in many applications. In this paper, we propose a fusion between the ear and voice biometrics in degraded conditions in a smart home context at 3 levels (feature, score, and decision). The experiments are conducted on the EVDDC database and a chimeric database (TIMIT and USTB-I). The best results are obtained with the feature level fusion (95.8%) with the KNN classifier. © 2023 IEEE.

关键词： Biometrics

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Early Diagnosis of Diabetic Retinopathy using Random Forest Algorithm

Early Diagnosis of Diabetic Retinopathy using Random Forest ...

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International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Nihel ZAABOUB Ali DOUIK Networked Objects Control and Communication Systems (NOCCS) Laboratory ENISo University of Sousse National Engeneering School of Tunis (ENIT) University of Tunis El Manar National Engeneering School of Sousse (ENISo) University of Sousse

ISBN: (数字)9781728175133

ISBN: (纸本)9781728175140

The diabetic retinopathy is one of the most frequent causes of visual damage and vision loss. It can cause blindness in the absence of the diagnosis and the treatment. The automatic detection of the hard exudate in color fundus retinal images is an important task to early diagnosis the diabetic retinopathy. In this paper, a hard exudate detection algorithm is proposed. It is based on the application of a learning method to retinal image with removed optic disk. This paper proposes the use of Random Forest algorithm with a specific parameter from which a binary mask of exudate is obtained after intensity thresholding. It achieves 91.40% for sensitivity and 94.38% for the accuracy.

关键词： Diabetes Retinopathy Retina Sensitivity Optical sensors Optical imaging Vegetation

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FFGAN: An Auto-supervised Approach for Frontal Face Generation Via Disentangled Contrastive Learning

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Procedia Computer Science 2024年 246卷 3644-3653页

作者： Grina Wiem Douik Ali National Engineering School of Monastir University of Monastir Rue Ibn Jazzar 5035 Monastir Tunisia Networked Objects Control and Communication Systems Laboratory Sousse Technology Centre National School of Engineers of Sousse University of Sousse Sahloul Belt Road 4054 Sousse Tunisia

This work proposes a novel generative model, FF-GAN (Frontal Face Generative Adversarial Network), for generating high-quality and diverse frontal faces. FF-GAN utilizes contrastive learning to effectively learn the underlying representation of frontal faces from unlabeled image datasets. This approach allows the model to capture the essential characteristics of frontal faces without the need for explicit pose annotations. We evaluate the performance of FF-GAN using established metrics like FID (Fréchet Inception Distance), IS (Inception Score), and SSIM (Structural Similarity Index Measure). The results demonstrate that FF-GAN achieves superior performance compared to existing methods, generating highly realistic and visually appealing frontal faces with exceptional structural coherence. This research contributes to the field of facial image generation by introducing an effective unsupervised learning approach based on contrastive learning for generating high-quality frontal faces.

关键词： Unsupervised Facial Pose Analysis Contrastive Learning Disentanglement Pose Estimation

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Detecting Video Saliency via Local Motion Estimation

Detecting Video Saliency via Local Motion Estimation

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ACS/IEEE International Conference on Computer systems and Applications

作者： Rahma Kalboussi Aymen Azaza Mehrez Abdellaoui Ali Douik ENISO Ecole Nationale d'Ingénieurs de Sousse NOCCS Networked Objects Control and Communication Systems Laboratory Soussel Tunisiay ENIM Ecole Nationale d'Ingénieurs de Monastir NOCCS Laboratory Monastir Tunisia ENISO NOCCS Laboratory Sousse Tunisia

In the last decades, saliency detection was extensively studied. The number of computational models that help to detect salient regions in still images is increasing, whereas, detecting salient regions in videos is in its early stages. In this paper we propose a video saliency detection method using local motion estimation. Starting from a patch, the problem of saliency detection is modeled as a growing region starting from a region which contains the higher motion information to the background. Local saliency is measured by combining local motion estimation and local surrounding contrast which leads to the construction of foreground and background patches. Experiments have proved that The proposed method outperforms state-of-the-art methods over two benchmark datasets.

关键词： Saliency detection Motion measurement Computational modeling Motion estimation Feature extraction Image color analysis Dynamics

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Delay-dependent synchronization criteria for delayed chaotic systems with parameter mismatches

Delay-dependent synchronization criteria for delayed chaotic...

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作者： He, Wangli Qian, Feng Han, Qing-Long Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China Centre for Intelligent and Networked Systems And School of Information and Communication Technology Central Queensland University Rockhampton 4702 Australia

ISBN: (纸本)9789881725592

This paper investigates synchronization between two delayed chaotic systems with parameter mismatches. Based on Lyapunov functional approach and generalized Halanay inequality, some delay-dependent criteria are derived to guarantee the synchronization error converges to a bounded ball, whose radius, referred to as the error level, is also estimated. Moreover, an optimization algorithm is established for error level estimate, and the feedback matrix design is also addressed. Finally, a chaotic neural network is used to illustrate the effectiveness of the proposed method. © 2011 Chinese Assoc of Automati.

关键词： Synchronization

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A Comparative Study of PCA and LDA for Dimensionality Reduction in a 4-Way Classification Framework

Research Square

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Research Square 2024年

作者： Mabrouk, Besma Jazzar, Nessrine Sallemi, Lamia Hamida, Ahmed Ben Advanced Technologies for Medicine and Signals ATMS Department of Electrical and Computer Engineering National Engineers School Sfax University Tunisia Networked Objects Control and Communication Systems National Engineering School Sfax Tunisia

Alzheimer’s disease (AD), recognized as the second-most impactful neurological disorder and currently incurable, stands as the leading cause of dementia. An imperative research focus is efficiently diagnosing the stages of patients, distinguishing early or late Mild Cognitive Impairment and AD from those with normal cognitive function. Advancements in anatomical and diffusion-weighted imaging, coupled with machine learning techniques, have significantly progressed in this predictive domain. However, in real-world trials, datasets often contain numerous features, and the curse of dimensionality can introduce challenges such as increased computational complexity, overfitting, and diminished model interpretability. To address these issues, the present study explores the efficacy of Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) as dimensionality reduction techniques. LDA, a supervised technique emphasizing class separability, surpasses PCA, particularly in selecting features that significantly contribute to discriminating between classes. The 3D-LDA features obtained were subsequently assessed across various machine learning algorithms, leading to the establishment of a 4-way classification framework that utilized the K-Nearest Neighbors model. The outcome of this evaluation yielded an impressive accuracy rate of 87% in predicting the four different classes. © 2024, CC BY.

关键词： Nearest neighbor search

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Leader-follower synchronization for complex dynamical networks via sampled-data control

Leader-follower synchronization for complex dynamical networ...

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31st Chinese control Conference, CCC 2012

作者： Wangli, He Feng, Qian Han, Qing-Long Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China Centre for Intelligent and Networked Systems Central Queensland University Rockhampton QLD 4702 Australia School of Information and Communication Technology Central Queensland University Rockhampton QLD 4702 Australia

ISBN: (纸本)9789881563811

This paper is concerned with leader-follower synchronization of complex dynamical networks with sampled-data control. By sampling the signal from the leader at some discrete time instants and using a zero-order hold function, synchronization is achieved between the network and a desired orbit, known as the leader. By applying Lyapunov functional approach and the property of the network topology matrix, a delay-dependent criterion is derived. It is shown that synchronization of N coupled dynamical systems with a leader can be recast into the stability of N decoupled systems, in which eigenvalues of the network topology matrix are involved. Finally, a chaotic neural network is used to illustrate the effectiveness of the proposed method. © 2012 Chinese Assoc of Automati.

关键词： Synchronization

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Lag Quasi-Synchronization of Coupled Delayed systems With Parameter Mismatch

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IEEE Transactions on Circuits and systems I: Regular Papers 2011年第6期58卷 1345-1357页

作者： Wangli He Feng Qian Qing-Long Han Jinde Cao Key Laboratory of Advanced Control and Optimization of Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China Centre of Intelligent and Networked Systems and the School of Information and Communication Technology Central Queensland University Rockhampton QLD Australia Department of Mathematics South-East University Nanjing China

This paper is concerned with lag synchronization of two coupled delayed systems with parameter mismatch. Due to parameter mismatch, complete lag synchronization can not be achieved. Therefore, a new lag quasi-synchronization scheme is proposed to ensure that coupled systems are in a state of lag synchronization with an error level. Several simple criteria are derived and the error level is estimated by applying a generalized Halanary inequality and matrix measure. Three examples are given to illustrate the effectiveness of the proposed lag quasi-synchronization scheme. It is shown that as the coupling strength increases, the estimated error level is close to the simulated one, which well supports theoretical results.

关键词： Synchronization Measurement uncertainty Delay Linear matrix inequalities Trajectory Delay effects Couplings

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Hybrid approach for speaker recognition based on formant and pitch extraction

Hybrid approach for speaker recognition based on formant and...

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International Conference on Cyberworlds

作者： Sana Boujnah Radhia Ferjaoui Anouar Ben Khalifa National Engineering School of Tunis University of Tunis El Manar Tunisia NOCCS-Laboratory of Networked Objects Control and Communication Systems Eniso Tunisia Research Laboratory of biophysics and Medical technologies(LRBTM) ISTMT University of Tunis El Manar Tunis Tunisia Ecole Nationale d’Ingénieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Sousse Tunisie Institut National des Technologies et des Sciences du Kef Université de Jendouba Le Kef Tunisie

Human voice is an ideal data source for identifying people in many applications. Because of the increasing need for security in different public places, voice biometrics may be a good solution, as we can easily take voice records. This paper provides a brief overview of the approaches utilized in recognizing speakers, and then presents a novel approach for recognizing speakers in degraded smart-home conditions. The suggested approach includes a pre-processing phase, a feature extraction phase, and a classification phase, where the feature extraction phase consists of formant extraction to get the spectrum energy maxima of speech audio, dynamic time warping (DTW)to find an optimal alignment between two provided temporal sequences under definite restrictions, and refinement process to improve the results of the DTW system output. The experiments are carried out on a database containing 1,248 samples in order to validate the suggested approach. The latter has good results as regards the state of the art with 94.5% accuracy.

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Person Identification with Voice and Ear-print in Degraded Conditions for Smart Home Access

Person Identification with Voice and Ear-print in Degraded C...

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International Conference on Cyberworlds

作者： Sana Boujnah Radhia Ferjaoui Anouar Ben Khalifa National Engineering School of Tunis University of Tunis El Manar Tunisia NOCCS-Laboratory of Networked Objects Control and Communication Systems Eniso Tunisia University of Tunis El Manar Research Laboratory of biophysics and Medical technologies(LRBTM) ISTMT Tunis Tunisia Université de Sousse Ecole Nationale d’Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse Tunisie Université de Jendouba Institut National des Technologies et des Sciences du Kef Le Kef Tunisie

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