检索结果-内蒙古大学图书馆

Informatica (Slovenia) 2025年第9期49卷 9-30页

作者： Fakhfakh, Rim Feki, Ghada Amar, Chokri Ben University of Sfax REGIM-Lab Research Groups in Intelligent Machines Tunisia Taif University College of Computers and Information Technology Tunisia

The large scale of image databases opens up new challenges for storing, organizing, and searching for data. The common challenge of image retrieval systems is to emphasize object detection and recognition from images to bridge the semantic gap between the Open-Vocabulary and Visual Content. This paper proposes a framework for a personalized image retrieval system which selects the most relevant images according to the specified query, the user interest, and the semantic interpretation. Our framework is composed of three major modules: (1) Users processing using Movielens as a social database. (2) Query processing and personalization. (3) Images processing by semantic annotation and clustering based on a new semantic similarity measure named SRSiM (Statistical Retina Similarity Measure) using statistical and knowledge-based approaches. The experimental study is performed on the NUS-WIDE dataset, a list of queries covering several social subjects and various user profiles extracted from the MovieLens database. The evaluation of the overall system shows promising results going up to 0.675 in terms of MAP (Mean Average Precision) measurement, which overcomes the score of other works established in the same conditions and using the same databases. The SRSiM measurement also reaches an accuracy of 77.77% compared to Wordnet, Wikipedia, and Retina-based measurements © 2025 Slovene Society Informatika. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

An ensemble learning algorithm based on discretized Time Series: application on smartphone-inertial measurement 27

An ensemble learning algorithm based on discretized Time Ser...

引用

27th International Conference on Knowledge Based and intelligent Information and Engineering Sytems, KES 2023

作者： Taktak, Mariem Triki, Slim Ltifi, Hela Research Groups in Intelligent Machine ReGIM-Lab Sfax University Tunisia National Engineering School of Sfax Sfax University Tunisia

This paper presents a novel learning algorithm formulated as a classification problem with smartphone-inertial measurement as predictor. For this reason, we will focus on the Symbolic Aggregate approXimation (SAX) as a low-cost classification algorithm resulting from its ability of the data dimensionality reduction through symbolic discretization. Since the first publication of the SAX, a lot of extension with novel SAX-distance measure are published. Each of them attempts to integrate additional statistical features in order to improve original SAX average-based feature. However, none of them can fit the overall shape-characteristics of the data and give the superiority to an individual SAX-based classifier. In order to combine the prediction of each single SAX-based classifier, we propose a collection of several SAX-feature to compose a multi-SAX feature ensemble classification. The proposed algorithm is validated on experimental data addressing (i) the character recognition when using a smartphone as a pen and (ii) the road profile estimation using a smartphone mounted in the interior of a vehicle while driving. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Classification Discretization Smartphone-inertial measurement Time Series Data

来源：评论

学校读者我要写书评

暂无评论

A Novel Method for Arabic Text Detection with Interactive Visualization 28

A Novel Method for Arabic Text Detection with Interactive Vi...

引用

28th IEEE Symposium on Computers and Communications, ISCC 2023

作者： Ouali, Imene Fourati, Rahma Ben Halima, Mohamed Wali, Ali University of Sfax REGIM-Lab.: REsearch Groups in Intelligent Machines Tunisia Tunisia

ISBN: (纸本)9798350300482

Text detection, recognition, and visualization from natural scenes are considered significant research topics in the field of information and communication technologies. Written text serves as a crucial source of information that humans rely on in their daily lives. However, detecting text poses several challenges, including variations in writing style, color, size, orientation, and complex backgrounds. In this study, we present a comprehensive application named ATDRV, which aims to address these challenges. For text detection and recognition, we propose a real-Time multi-oriented text deep fully convolutional network system trained end-To-end. Additionally, we implement a visualization module based on Augmented Reality to display the results more clearly to users. The output of our application is a large and clear 3D object that enables easy reading of the text. Our approach improves the user experience and facilitates the reading of Arabic text regardless of color, orientation, writing style, or complex backgrounds. © 2023 IEEE.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Classification of soil texture using machine Learning Technique 17

Classification of soil texture using Machine Learning Techni...

引用

17th International Conference on INnovations in intelligent SysTems and Applications, INISTA 2023

作者： Ghabi, Marwen Regim-Lab. Research Groups in Intelligent Machines ENET'COM - National School of Electronics and Telecommunications of Sfax Kairouan Tunisia

ISBN: (纸本)9798350338904

The application of machine Learning techniques in various scientific fields has increased rapidly. The increasing availability of soil data and open access algorithms has led to an accelerated adoption of machine Learning techniques to analyse soil data. Soil classification deals with the systematic categorization of soils according to distinct characteristics and criteria. The work presented in this brief is the subject of the use of machine Learning techniques for the classification of soil texture. We will apply the Data Visualization on a set of soil data and then use machine Learning methods that make it easy for us to distinguish different compositions in order to establish a soil type prediction through very precise algorithms like LDA, KNN, etc. The objective of this approach allows us to achieve the best classification algorithm that gives us the best classification of the soil. © 2023 IEEE.

关键词： Data visualization

来源：评论

学校读者我要写书评

暂无评论

Augmented Reality for Scene Text Recognition, Visualization and Reading to Assist Visually Impaired People 26

Augmented Reality for Scene Text Recognition, Visualization ...

引用

26th International Conference on Knowledge-Based and intelligent Information and Engineering Systems, KES 2022

作者： Ouali, Imene Ben Halima, Mohamed Wali, Ali REGIM-Lab: Research Groups in Intelligent Machines National Engineering School of Sfax University of Sfax Tunisia

Reading traffic signs while driving a car for visually impaired people and people with visual problems is a very difficult task for them. This task is encountered every day, sometimes incorrect reading of traffic signs can lead to very serious results. In particular, the Arabic language is very difficult, making recognizing and viewing Arabic text a difficult task. In this context, we are looking for an effective solution to remove errors and results that can sometimes end someone's life. This article aims to correctly read traffic signs with Arabic text using augmented reality technology. Our system is composed of three modules. The first is text detection and recognition. The second is Text visualization. The third is Text to speech methods conversion. With this system, the user can have two different results. The first result is visual with much-improved text and enhancement. The second result is sound, he can hear the text aloud. This system is very applicable and effective for daily life. To assess the effectiveness of our work, we offer a survey to a group of visually impaired people to give their opinion on the use of our application. The results have been good for most people. © 2022 The Authors. Published by Elsevier B.V.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

An ensemble learning algorithm based on discretized Time Series: application on smartphone-inertial measurement

引用

Procedia Computer Science 2023年 225卷 165-176页

作者： Mariem TAKTAK Slim TRIKI Hela Ltifi Research Groups in Intelligent Machine ReGIM-Lab Sfax University Tunisia National Engineering School of Sfax Sfax University Tunisia

关键词： Time Series Data Classification Discretization Smartphone-inertial measurement

来源：评论

学校读者我要写书评

暂无评论

An Automatic Vision Transformer Pruning Method Based on Binary Particle Swarm Optimization 28

An Automatic Vision Transformer Pruning Method Based on Bina...

引用

28th IEEE Symposium on Computers and Communications, ISCC 2023

作者： Tmamna, Jihene Ben Ayed, Emna Fourati, Rahma Ben Ayed, Mounir REGIM-Lab.: REsearch Groups in Intelligent Machines BP 1173 Sfax3038 Tunisia Industry 4.0 Research Lab Sfax3002 Tunisia Jendouba Tunisia Faculty of Sciences of Sfax Sfax Tunisia

ISBN: (纸本)9798350300482

This paper presents an automatic vision transformer pruning method that aims to alleviate the difficulty of deploying vision transformer models on resource-constrained devices. The proposed method aims to automatically search for the optimal pruned model by removing irrelevant units while maintaining the original accuracy. Specifically, the model pruning is formulated as an optimization problem using binary particle swarm optimization. To demonstrate its effectiveness, our method was tested on the DeiT Transformer model with CIFAR-10 and CIFAR-100 datasets. Experimental results demonstrate that our method achieves a significant reduction in computational cost with slight performance degradation. © 2023 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Knowledge reduction by combining interval Type-2 Fuzzy similarity measures and interval Type-2 Fuzzy formal lattice

引用

International Journal of Information Technology (Singapore) 2024年第6期16卷 3723-3728页

作者： Cherif, Sahar Baklouti, Nesrine Alimi, Adel M. REGIM-Lab.: Research Groups in Intelligent Machines University of Sfax National School of Engineers of Sfax (ENIS) Sfax 3038 Tunisia Department of Electrical and Electronic Engineering Science Faculty of Engineering and the Built Environment University of Johannesburg Johannesburg South Africa

Knowledge and concepts play a crucial role in human language processing. Human behavior varies in different environments, making it difficult to convey uniform definitions of these abstract notions. Furthermore, human language’s ambiguity can lead to different interpretations of a concept depending on the context. In knowledge representation, multiple context implications often increase time complexity and cause misunderstanding. To reduce and represent knowledge in concepts, we propose a hybrid technique that involves calculating concept similarity, estimating typicality, identifying concept prototypes and constructing the Interval Type-2 Fuzzy Formal Lattice (IT-2F²L). Experiments were carried out using real-world data to explore concepts lexicalized in natural language. The experimental findings demonstrate that our method, which combines Interval Type-2 Fuzzy Similarity Measures and Interval Type-2 Fuzzy Formal Lattice for concepts factorization, is a powerful tool with applications in various areas of conceptual psychology. The IT-2F²L is both interpretative and objective, making it a valuable tool for analysis and decision-making. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.

关键词： Concepts Interval Type-2 Fuzzy logic Knowledge Lattice Reduction Similarity Measures

来源：评论

学校读者我要写书评

暂无评论

Data Analysis of Electromyostimulation Training Effect on Muscles and Sports Performance 28

Data Analysis of Electromyostimulation Training Effect on Mu...

引用

28th IEEE Symposium on Computers and Communications, ISCC 2023

作者： Kallel, Syrine Fourati, Rahma Higher Institute of Computer Science and Multimedia University of Sfax Sfax Tunisia REGIM-Lab.: REsearch Groups in Intelligent Machines BP 1173 Sfax3038 Tunisia Jendouba Tunisia

ISBN: (纸本)9798350300482

This paper investigates the effect of modern lifestyles on physical activity and the rise of time-saving exercise protocols to improve health and performance. Such protocols, Bio Impedance Analysis (BIA), and Electrical Muscle Stimulation (EMS) are explored in detail. BIA is a non-invasive and painless technology that accurately evaluates the amount of water, proteins, minerals, and fat masses in the body. EMS involves applying electrical currents to muscles through electrodes to induce involuntary contractions and is being used for muscle rehabilitation, treating obesity, and improving body shape. The manufacturers of EMS devices claim that 20 minutes of electro-stimulation work is equivalent to 4 hours of traditional sports. The emergence of new technologies such as INTEGRAL-EMS, a combination of portable electro-stimulation with an integrated, wireless, high-performance generator, is making it increasingly accessible for people to achieve their health and fitness goals in a more efficient and convenient manner. © 2023 IEEE.

关键词： Muscle

来源：评论

学校读者我要写书评

暂无评论

Computational Complexity Analysis of Ant Colony Clustering Algorithms: Application to Student's Grouping Problem

Computational Complexity Analysis of Ant Colony Clustering A...

引用

2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Chniter, Malak Abid, Abir Kallel, Ilhem Kanoun, Slim Mir@cl Lab: Multimedia InfoRmation Systems and Advanced Computing Laboratory University of Sfax ReGIM-Lab: Research Groups in Intelligent Machines Tunisia

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

The task of assessing, grouping and arranging data into meaningful groups or clusters based on their similarities/dissimilarities measures known as cluster analysis. Thereby, there are numerous clustering algorithms: hierarchical and partitional. In the last decade, clustering using bio-inspired algorithms received more attention, specifically the ant clustering algorithms. Regardless, they have required a lot of processing power due to the massive amount of data that has been generated during the last years. As a consequence, determining the computational cost of these algorithms is one of the most interesting tasks in the quest for optimal clustering solutions in a real-time system. This study presents a research guide for the researchers working in the same field. A series of experiments are elaborated to investigate the computational complexity of the most promising algorithms applied to students grouping problem. The results indicate two challenges that arise when using ant clustering algorithms: the difficulty in adjusting parameters and extended computation time. © 2022 IEEE.

关键词： Computational complexity

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：