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17th IEEE/ACIS International Conference on Computer and information Science, ICIS 2018

作者： Louhichi, Soumaya Gzara, Mariem Abdallah, Hanene Ben MIRACL: Multimedia InforRmation Systems and Advanced Computing Laboratory Sfax Tunisia High School of Computer Science and Mathematics at the University of Monastir Monastir Tunisia King Abdulaziz University Jeddah Saudi Arabia

ISBN: (纸本)9781538658925

Skin lesion segmentation is a key step in a diagnosis system based on dermoscopic images. This paper proposes a method to detect the skin lesion accurately. The images are first cleansed to remove noise. Then, pertinent features are extracted from RGB, HSV and XYZ color spaces. Cluster analysis is used for segmentation. We take advantage of the multiple density clustering algorithm MDCUT [1] to solve the problem of image segmentation using region growing. We demonstrate how MDCUT algorithm is used to automatically determine the needed parameters for region growing image segmentation. Experiments on medical skin lesion image and comparison with the ground truth segmentation results demonstrate the validity of our method. © 2018 IEEE.

关键词： Clustering algorithms

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20th International Conference on Enterprise information systems, ICEIS 2018

作者： Sebei, Hiba Taieb, Mohamed Ali Hadj Aouicha, Mohamed Ben Computer Science Department Faculty of Economics and Mangement Sfax Tunisia Multimedia InfoRmation Systems and Advanced Computing Laboratory Sfax Tunisia Computer Science Department Faculty of Sciences Sfax Tunisia

ISBN: (纸本)9789897582981

With the spread of online social media websites, a huge amount of online content is continuously provided. However, some contents gain an important attention from users while other contents are completely ignored. This highlights the analysis of popularity relative to different social content. The popularity is expressed through measures and features that act as factors expressing and influencing the popularity. Those features vary from an online social media website to another as it depends on the type of social entity. This paper tries to create a normalized view of the popularity metrics independent of the online social media and in relation with specific social entities that are user and media content (i.e. text, image, and video). We propose a Service Provider Interface (SPI) as a contract between users. The SPI offers a variety of interfaces for implementing services related to the quantification of social entities popularity independently of the online social media they belong to. Copyright © 2018 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Social networking (online)

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Hand gesture recognition method based on HOG-LBP features for mobile devices

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Procedia Computer Science 2018年 126卷 254-263页

作者： Houssem Lahiani Mahmoud Neji National School of Electronics and Telecommunications (Enet’Com) University of Sfax Tunisia Faculty of Economics and Management (FSEGS) University of Sfax Tunisia Multimedia Information Systems and Advanced Computing Laboratory (Miracl) Sfax Tunisia

Hand Gesture recognition becomes a challenging task in computer vision field especially after the appearance of mobile devices. Although gesture recognition algorithms have been widely applied to the human-mobile interaction systems, it is difficult to meet the real time requirements and the robustness in different lightening conditions and backgrounds. This paper provides a description of a practical investigation into ways of improving hand gesture recognition algorithms for computationally limited handheld Android devices. We thoroughly researched possible approaches and find out how they affect the mobile device in terms of execution time and energy consumption. We have identified a combined HOG-LBP methodology whose performance improved upon the detection rate of other systems. In this paper, we present a static hand gesture recognition system for mobile devices by combining the histogram of oriented gradients (HOG) and local binary pattern (LBP) features, which can accurately detect hand poses. With the help of combining HOG and LBP features, we achieved a detection rate of approximately 92% on the enhanced NUS dataset I. This combination performs a better result than the results obtained when using only LBP or HOG features in term of recognition rate. However, in term of execution and detection time, LBP and HOG perform better than the combined HOG-LBP.

关键词： Hand posture recognition android LBP AdaBoost HOG Human-machine interaction

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Association Rules Transformation for Knowledge Integration and Warehousing 17th

Association Rules Transformation for Knowledge Integration a...

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17th International Conference on Intelligent systems Design and Applications, ISDA 2017

作者： Ayadi, Rim Hachaichi, Yasser Feki, Jamel Multimedia Information Systems and Advanced Computing Laboratory University of Sfax Sfax Tunisia Department of Computer Science and Quantitative Methods Higher Institute of Business Administration of Sfax Sfax Tunisia Faculty of Computing and IT University of Jeddah Jeddah Saudi Arabia

ISBN: (纸本)9783319763477

Knowledge management process is a set of procedures and tools applied to facilitate capturing, sharing and effectively using knowledge. However, knowledge collected from organizations is generally expressed in various formalisms, therefore it is heterogeneous. Thus, a Knowledge Warehouse (KW), which is a solution for implementing all phases of the knowledge management process, should solve this structural heterogeneity before loading and storing knowledge. In this paper, we are interested in knowledge normalization. More accurately, we firstly introduce our proposed architecture for a KW, and then we present the MOT (Modeling with Object Types) language for knowledge representation. Since our objective is to transform heterogeneous knowledge into MOT, as a pivot model, we suggest a meta-model for the MOT and another for the explicit knowledge extracted through the association rules technique. Thereafter, we define eight transformation rules and an algorithm to transform an association rules model into the MOT model. © 2018, Springer International Publishing AG, part of Springer Nature.

关键词： Data mining

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Hand Gesture Recognition System Based on Local Binary Pattern Approach for Mobile Devices 1

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17th International Conference on Intelligent systems Design and Applications, ISDA 2017

作者： Lahiani, Houssem Kherallah, Monji Neji, Mahmoud National School of Electronics and Telecommunications University of Sfax Sfax Tunisia Faculty of Sciences University of Sfax Sfax Tunisia Faculty of Economics and Management University of Sfax Sfax Tunisia Multimedia Information Systems and Advanced Computing Laboratory Sfax Tunisia

ISBN: (数字)9783319763484

ISBN: (纸本)9783319763477

Since the appearance of mobile devices, gesture recognition is being a challenging task in the field of computer vision. In this paper, a simple and fast algorithm for static hand gesture recognition for mobile device is described. The hand pose is recognized by using gentle AdaBoost learning algorithm and Local Binary Pattern features. The system is developed on an Android OS platform. The method used consists of two steps: a real-time gesture captured by a smartphone’s camera and the recognition of the hand gestures. It presents a system based on a real-time hand posture recognition algorithm for mobile devices. The aim of this work is to allow the mobile device interpreting the sign made by the user without the need to touch the screen. In this system, the device is able to perform all necessary steps to recognize hand posture without the need to connect to any distant device. © 2018, Springer International Publishing AG, part of Springer Nature.

关键词： Local binary pattern

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Hand Pose Estimation System Based on a Cascade Approach for Mobile Devices 17th

Hand Pose Estimation System Based on a Cascade Approach for ...

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17th International Conference on Intelligent systems Design and Applications, ISDA 2017

ISBN: (纸本)9783319763477

The rise in the use of mobile devices requires finding new ways to interact with this type of devices. Gestures are an effective way to interact with the mobile device and to place order to it. However, gesture recognition in this context constitute a challenging task due the limited computational capacities of this type of devices. In this work, we present a hand pose estimation system for mobile device. The gesture is recognized by using a boosting algorithm and Haar-like features. The system is designed for Android devices. The method used consists of capturing gestures by a smartphone’s camera to recognize the hand sign. It presents a system based on a real-time hand posture recognition algorithm for mobile devices. The aim of this system is to allow the mobile device interpreting hand signs made by users without the need to touch the screen. © 2018, Springer International Publishing AG, part of Springer Nature.

关键词： Adaptive boosting

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Skin Lesion Segmentation Using Multiple Density Clustering Algorithm MDCUT And Region Growing

Skin Lesion Segmentation Using Multiple Density Clustering A...

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International Conference on Computer and information Science (ACIS)

作者： Soumaya Louhichi Mariem Gzara Hanêne Ben Abdallah MIRACL: Multimedia InforRmation systems and Advanced Computing Laboratory Sfax Tunisia High School of Computer Science and Mathematics at the University of Monastir Monastir Tunisia King Abdulaziz University Jeddah KSA

关键词： Image segmentation Clustering algorithms Lesions Image color analysis Skin Feature extraction Shape

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A New Method for the Construction of Evolving Embedded Representations of Words

A New Method for the Construction of Evolving Embedded Repre...

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ACS/IEEE International Conference on Computer systems and Applications

作者： Amal Bouraoui Salma Jamoussi Abdelmajid Ben Hamadou Multimedia InfoRmation systems and Advanced Computing Laboratory MIRACL Sfax-Tunisia Technopole of Sfax Sfax Tunisia

There are several natural language processing tasks such as natural language understanding, information retrieval and social network analysis which require dynamic update of the word embeddings representation so as to keep pace with the words meanings evolving. Thanks to their ability to capture both syntactic and semantic information within language, the continuous bag-of-words, a learning word representation model, has gained a lot of attention from researchers and has been successfully applied to different NLP tasks. However, this model does not adequately capture the change of word semantics over time. This paper provides a new perspective to determine the semantic similarity of words over time by constructing several representations of words that reflect the semantic change of words based on latest embeddings. We examine the performance of our improved CBOW on an evolved data base collected from English Wikipedia pages. Our learned embeddings illustrate the semantic evolution of words better than the original CBOW.

关键词： Semantics Task analysis Vocabulary Computer architecture Natural language processing Encyclopedias

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Novelty detection in data stream clustering using the artificial immune system 13

Novelty detection in data stream clustering using the artifi...

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13th European, Mediterranean and Middle Eastern Conference on information systems, EMCIS 2016

作者： Abid, Amai Jamoussi, Salma Multimedia Information systems and Advanced Computing Laboratory MIRACL Sfax University Tunisia

ISBN: (纸本)9789606897092

Data stream clustering poses many challenges to the data mining community where traditional data mining techniques become infeasible to mine such continuous flow of data. This paper presents a novel method for data stream clustering. In particular, we address the problem of novelty detection in data streams. For this purpose, the proposed method uses the Artificial Immune System meta-heuristic. The latter has been widely used for unsupervised data mining tasks and it owns the property of adaptability required by data stream clustering algorithms. Our method, called AIS-Clus (Artificial Immune System for data stream Clustering), is able to detect novel concepts using the performance of the learning process of AIS meta-heuristic. Furthermore, AIS-Clus has the ability to adapt its model to handle novel arriving items in textual data streams. Experimental results are given for two textual datasets and promising results are obtained. © Proceedings of the 13th European, Mediterranean and Middle Eastern Conference on information systems, EMCIS 2016. All rights reserved.

关键词： Clustering algorithms

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Linear operators in information retrieval

Linear operators in information retrieval

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6th Symposium on Languages, Applications and Technologies, SLATE 2017

作者： Hattab, Hawete Mbarek, Rabeb Umm Al-qura University Al-Jumum University College Department of Mathematics Makkah Saudi Arabia Sfax University Multimedia Information Systems and Advanced Computing Laboratory Sfax Tunisia

ISBN: (纸本)9783959770569

In this paper, we propose a pseudo-relevance feedback approach based on linear operators: vector space basis change and cross product. The aim of pseudo-relevance feedback methods based on vector space basis change IBM (Ideal Basis Method) is to optimally separate relevant and irrelevant documents. Whereas the aim of pseudo-relevance feedback method based on cross product AI (Absorption of irrelevance) is to e ectively exploit irrelevant documents. We show how to combine IBM methods with AI methods. The combination methods IBM+AI are evaluated experimentally on two TREC collections (TREC-7 ad hoc and TREC-8 ad hoc). The experiments show that these methods improve previous works. © Hawete Hattab and Rabeb Mbarek

关键词： Vector spaces

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