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International Conference on Engineering and Emerging Technologies (ICEET)

作者： Maraoui Amna Werda Imen Sayadi Fatma Ezahra Electronics and Microelectronics Laboratory University of Monastir Monastir Tunisia Electronic and Information Technology Laboratory University of Sfax Sfax Tunisia Networked objects control and communication systems Laboratory University of Sousse Sousse Tunisia

ISBN: (纸本)9781665427159

The evolution of the coding unit module from the High Efficiency Video Coding (HEVC) video standards to the Joint Exploration Model (JEM) extensively enhanced compression performance while severely increases coding complexity caused by the brute force search built on Rate Distortion Optimization (RDO). Effectively, compared to the predecessor HEVC standard that makes use of the quad-tree (QT) block partitioning module, the novel quad-tree binary-tree (QTBT) block partitioning process proposed within the JEM encoder uses additional block sizes and shapes which induces additional flexibility. In this paper, we suggest a deep convolutional neural network (CNN) based method to reduce the block partitioning module complexity for both HEVC and JEM encoders at all intra-configurations. The results show that the CNN approach leads to better optimization performance with the HEVC encoder reaching up to 59%. However, the CNN model is more robust with several JEM versions.

关键词： Deep learning Shape Rate-distortion Encoding Complexity theory Convolutional neural networks Optimization

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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

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.

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Performance Analysis of Cooperative Wireless-Powered NOMA System With Energy Buffer

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green communications and Networking 2024年

作者： Xie, Kengyuan Cai, Guofa Ning, Ting He, Jiguang Kaddoum, Georges Guangdong University of Technology School of Information Engineering Guangzhou510006 China Chongqing University of Posts and Telecommunications Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing400065 China Great Bay University School of Computing and Information Technology China University of Oulu Centre for Wireless Communications Oulu90014 Finland University of Quebec Electrical Engineering Department École de Technologie Supérieure MontrealQCH2L 2C4 Canada Lebanese American University Artificial Intelligence and Cyber Systems Research Center Lebanon

This paper proposes an energy buffer aided cooperative wireless-powered non-orthogonal multiple access (NOMA) system, which includes a base station (BS), a near user (NU), and a far user (FU). To consider a more general case and improve the system performance as much as possible, both the NU and FU are equipped with energy buffers. Two different energy management policies are considered at the NU and FU, namely the best-effort policy (BEP) and on-off policy (OOP). In the proposed system, the NU and FU first collect and store radio frequency based energy from the BS. Then, the FU uses the stored energy to transmit its signal to both the BS and NU. The NU decodes the received signal from the FU and uses the stored energy to transmit the superimposed signal that consists of its own signal and the decoded FU signal to the BS. The outage probability and throughput expressions of the proposed system with BEP and OOP are derived over Rayleigh fading channels. Results reveal that the proposed system can significantly improve the performance of FU compared to the energy buffer aided non-cooperative wireless-powered NOMA system, and can outperform the buffer-less cooperative wireless-powered NOMA system. © 2017 IEEE.

关键词： Fading channels

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Colour-weighted rank transform and improved dynamic programming for fast and accurate stereo matching

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The Journal of Photographic Science 2024年第2期72卷

作者： Mohamed Hallek Randa Khemiri Ali Aseere Abdellatif Mtibaa Mohamed Atri a Laboratory of Electronics and Microelectronics University of Monastir Monastir Tunisia b Networked Objects Control and Communication Systems Laboratory ENISO Sousse University Sousse Tunisia c College of Computer Science King Khalid University Abha Saudi Arabia d National Engineering School of Sfax University of Sfax Sfax Tunisia

ABSTRACTReal-time stereo matching with high accuracy is a dynamic research topic; it is attractive in diverse computer vision applications. This paper presents a stereo-matching algorithm that produces high-quality disparity map while maintaining real-time performance. The proposed stereo-matching method is based on three per-pixel difference measurements with adjustment elements. The absolute differences and the gradient matching are combined with a colour-weighted extension of complete rank transform to reduce the effect of radiometric distortion. The disparity calculation is realized using improved dynamic programming that optimizes along and across all scanlines. It solves the inter-scanline inconsistency problem and increases the matching accuracy. The proposed algorithm is implemented on parallel high-performance graphic hardware using the Compute Unified Device Architecture to reach over 240 million disparity evaluations per second. The processing speed of our algorithm reaches 98 frames per second on 240 × 320-pixel images and 32 disparity levels. Our method ranks fourth in terms of accuracy and runtime for quarter-resolution images in the Middlebury stereo benchmark.

关键词： Cost function rank transform guided filter dynamic programming real-time performance stereo matching GPU CUDA gradient matching

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Performance Analysis of Multi-RIS-Aided LoRa systems With Outdated and Imperfect CSI

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IEEE Transactions on communications 2024年

作者： Liang, Zhaokun Cai, Guofa He, Jiguang Kaddoum, Georges Huang, Chongwen Guangdong University of Technology School of Information Engineering China Ministry of Education Key Laboratory of Industrial Internet of Things and Networked Control Chongqing University of Posts and Telecommunications Chongqing400065 China Great Bay University School of Computing and Information Technology China University of Oulu Centre for Wireless Communications Oulu90014 Finland University of Quebec Electrical Engineering Department École de Technologie Supérieure MontrealQCH2L 2C4 Canada Lebanese American University Artificial Intelligence and Cyber Systems Research Center United States Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China

Although LoRa has emerged as the leading technology among the rapidly developing low-power wide-area networks, the performance of the LoRa system severely deteriorates over fading channels. To address this problem, in this paper, we introduce multiple reconfigurable intelligent surfaces (multi-RISs) into the LoRa system to improve its performance. Our specific focus is on the impact of outdated channel state information (CSI), the imperfection of estimated CSI, and the design of RIS discrete phase shifts on the performance. To this end, we first use the moment-matching method to obtain the end-to-end (E2E) channel coefficient of the joint outdated channels and erroneous channels over Nakagami-m fading. Moreover, the closed-form bit error rates (BERs) of the proposed system with non-coherent and coherent detections are derived. The results reveal that, in the high signal-to-noise ratio (SNR) regime, coherent detection encounters the error floor and performs worse than non-coherent detection. Furthermore, we also analyze delay outage rate, throughput, and achievable diversity order of the proposed system. The results show that, despite the presence of outdated CSI and channel estimation errors, the proposed system is still superior to RIS-aided LoRa systems adopting blind transmission and RIS-free ones. Finally, we also thoroughly investigate the effects of various important factors such as the correlation factor, channel estimation errors, the number of RIS reflecting elements, and the number of quantization bits for RIS discrete phase shifts on the performance. © 1972-2012 IEEE.

关键词： Fading channels

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Local saliency estimation and global homogeneity refinement for video saliency detection 11th

Local saliency estimation and global homogeneity refinement ...

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11th International KES Conference on Intelligent Interactive Multimedia: systems and Services, KES-IIMSS 2018

作者： Kalboussi, Rahma Abdellaoui, Mehrez Douik, Ali Networked Objects Control and Communication Systems Laboratory Pôle technologique de Sousse Route de Ceinture Sahloul Sousse4054 Tunisia University of Sousse Sousse Tunisia Higher Institute of Computer Sciences and Communications Technology Hammam SousseSousse Tunisia

ISBN: (纸本)9783319922300

Saliency detection aims to segment the object of interest from the rest of the scene. While there has been a big number of saliency detection methods in still images, video saliency is in its early stages. In this paper, we propose a two stages video saliency detection method using local saliency estimation and global homogeneity refinement. Starting from a patch, the problem of saliency detection is modeled as a growing region which starts from a patch with high saliency information to the background. Local saliency is measured by combining spatial priors presented by local surrounding contrast with temporal information issued from the motion estimation feature. Temporal and spatial information are fused and then used to label each patch as foreground and background patches and produce the final saliency maps. Finally, Global homogeneity refinement is used to refine the saliency results by evaluating the foreground and background probabilities ratio propagated from the patches. Experiments have proved that the proposed method outperforms state-of-the-art methods over two benchmark datasets. © Springer International Publishing AG, part of Springer Nature 2019.

关键词： Motion estimation

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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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Video saliency using supervoxels 10th

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10th KES International Conference on Intelligent Interactive Multimedia systems and Services, IIMSS 2017

作者： Kalboussi, Rahma Abdellaoui, Mehrez Douik, Ali Networked Objects Control and Communication Systems Laboratory National Engineering School of Sousse Pôle technologique de Sousse Route de Ceinture Sahloul Sousse4054 Tunisia

ISBN: (纸本)9783319594798

Physiology and neural systems researchers revealed that the visual system is attracted by some parts of an image more than others. Different computational models were developed to simulate the visual system. In this paper we propose a video saliency model that helps to predict and detect the regions of interest in each video frame. We use a supervoxel segmentation as an indicator of dynamic objects. Based on the observation that dynamic objects attract attention when an observer watches a video sequence, supervoxel segmentation provides a first estimation for what belongs to foreground and background. Then, a saliency score is attributed to each supervoxel according to its motion distinctiveness. Experiments over two benchmark datasets, using several evaluation metrics have shown that our proposed method outperforms five saliency detection methods. © Springer International Publishing AG 2018.

关键词： Computers

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Parallel video processing on FPGA architecture

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International Journal of High Performance systems Architecture 2018年第3期8卷 169-178页

作者： Touil, Lamjed Abdelali, Abdessalem Ben Kechiche, Lilia Chaieb, Chiheb Ouni, Bouraoui Mtibaa, Abdellatif Networked Objects Control and Communications Systems Laboratory ENISo Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Tunisia Laboratory of Electronics and Microelectronics University of Monastir Tunisia Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Tunisia Networked Objects Control and Communications Systems Laboratory ENISo University of Sousse Tunisia

Real-time video applications are becoming widely used in many domains with more demand for high performance. Video processing is intensive and habitually has accompanying real-time or super-real-time requirements. Such us, multiple cameras are used in monitoring and surveillance systems in automatically real-time analyse video to detect unusual events. Due to the strong computational imposed by video algorithms, real-time video treatment is notably amenable to concurrent processing. Classical implementation solutions whether based on general purpose processors or dedicated ones like DSP cannot fulfil wanted performance. In this article, we focus on the applicability of computing reconfigurable architectures to parallel video processing applications. The experiment results show that the proposed hardware-oriented multi-treatment architecture can provide an average frame rate of 45 frames/s at high definition resolution. Statistics show a consumption about 18% of logic resources and 27% of on chip memory which gives the possibility to integrate additional treatments. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Reconfigurable architectures

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