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214 results on '"Bechikh, Slim"'

7. Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm and Transfer Learning

Author

Louati, Hassen, Louati, Ali, Kariri, Elham, Bechikh, Slim, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Nguyen, Ngoc Thanh, editor, Botzheim, János, editor, Gulyás, László, editor, Nunez, Manuel, editor, Treur, Jan, editor, Vossen, Gottfried, editor, and Kozierkiewicz, Adrianna, editor

Published
2023
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8. Many-Objective Software Remodularization using NSGA-III

Author

Mkaouer, Mohamed Wiem, Kessentini, Marouane, Shaout, Adnan, Koligheu, Patrice, Bechikh, Slim, Deb, Kalyanmoy, and Ouni, Ali

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence
Abstract

Software systems nowadays are complex and difficult to maintain due to continuous changes and bad design choices. To handle the complexity of systems, software products are, in general, decomposed in terms of packages/modules containing classes that are dependent. However, it is challenging to automatically remodularize systems to improve their maintainability. The majority of existing remodularization work mainly satisfy one objective which is improving the structure of packages by optimizing coupling and cohesion. In addition, most of existing studies are limited to only few operation types such as move class and split packages. Many other objectives, such as the design semantics, reducing the number of changes and maximizing the consistency with development change history, are important to improve the quality of the software by remodularizing it. In this paper, we propose a novel many-objective search-based approach using NSGA-III. The process aims at finding the optimal remodularization solutions that improve the structure of packages, minimize the number of changes, preserve semantics coherence, and re-use the history of changes. We evaluate the efficiency of our approach using four different open-source systems and one automotive industry project, provided by our industrial partner, through a quantitative and qualitative study conducted with software engineers., Comment: Mkaouer, Wiem, et al. "Many-objective software remodularization using NSGA-III." ACM Transactions on Software Engineering and Methodology (TOSEM) 24.3 (2015): 1-45

Published
2020
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9. Design and Compression Study for Convolutional Neural Networks Based on Evolutionary Optimization for Thoracic X-Ray Image Classification

Author

Louati, Hassen, Louati, Ali, Bechikh, Slim, Ben Said, Lamjed, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nguyen, Ngoc Thanh, editor, Manolopoulos, Yannis, editor, Chbeir, Richard, editor, Kozierkiewicz, Adrianna, editor, and Trawiński, Bogdan, editor

Published
2022
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10. Evolutionary Optimization for CNN Compression Using Thoracic X-Ray Image Classification

Author

Louati, Hassen, Bechikh, Slim, Louati, Ali, Aldaej, Abdulaziz, Said, Lamjed Ben, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Fujita, Hamido, editor, Fournier-Viger, Philippe, editor, Ali, Moonis, editor, and Wang, Yinglin, editor

Published
2022
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17. Malware Detection Using Rough Set Based Evolutionary Optimization

Author

Jerbi, Manel, Chelly Dagdia, Zaineb, Bechikh, Slim, Ben Said, Lamjed, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Mantoro, Teddy, editor, Lee, Minho, editor, Ayu, Media Anugerah, editor, Wong, Kok Wai, editor, and Hidayanto, Achmad Nizar, editor

Published
2021
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18. Evolutionary Optimization of Convolutional Neural Network Architecture Design for Thoracic X-Ray Image Classification

Author

Louati, Hassen, Bechikh, Slim, Louati, Ali, Aldaej, Abdulaziz, Said, Lamjed Ben, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Fujita, Hamido, editor, Selamat, Ali, editor, Lin, Jerry Chun-Wei, editor, and Ali, Moonis, editor

Published
2021
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19. Software Anti-patterns Detection Under Uncertainty Using a Possibilistic Evolutionary Approach

Author

Boutaib, Sofien, Elarbi, Maha, Bechikh, Slim, Hung, Chih-Cheng, Ben Said, Lamjed, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hu, Ting, editor, Lourenço, Nuno, editor, and Medvet, Eric, editor

Published
2021
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23. Class-Dependent Weighted Feature Selection as a Bi-Level Optimization Problem

Author

Hammami, Marwa, Bechikh, Slim, Hung, Chih-Cheng, Ben Said, Lamjed, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Yang, Haiqin, editor, Pasupa, Kitsuchart, editor, Leung, Andrew Chi-Sing, editor, Kwok, James T., editor, Chan, Jonathan H., editor, and King, Irwin, editor

Published
2020
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35. A Fuzzy Logic-Based Anticipation Car-Following Model

Author

Bennajeh, Anouer, Bechikh, Slim, Said, Lamjed Ben, Aknine, Samir, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Thanh Nguyen, Ngoc, editor, and Kowalczyk, Richard, editor

Published
2018
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37. Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression.

Author

Louati, Hassen, Louati, Ali, Kariri, Elham, and Bechikh, Slim

Subjects
DEEP learning, COMPUTER-aided diagnosis, EVOLUTIONARY algorithms, CONVOLUTIONAL neural networks, DIAGNOSIS, LUNGS, LUNG diseases
Abstract

Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues, particularly in the field of lung disease diagnosis. One promising avenue involves the use of chest X-Rays, which are commonly utilized in radiology. To fully exploit their potential, researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic systems. However, constructing and compressing these systems presents a significant challenge, as it relies heavily on the expertise of data scientists. To tackle this issue, we propose an automated approach that utilizes an evolutionary algorithm (EA) to optimize the design and compression of a convolutional neural network (CNN) for X-Ray image classification. Our approach accurately classifies radiography images and detects potential chest abnormalities and infections, including COVID-19. Furthermore, our approach incorporates transfer learning, where a pre-trained CNN model on a vast dataset of chest X-Ray images is fine-tuned for the specific task of detecting COVID-19. This method can help reduce the amount of labeled data required for the task and enhance the overall performance of the model. We have validated our method via a series of experiments against state-of-the-art architectures. [ABSTRACT FROM AUTHOR]

Published
2024
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39. Bi-MOCK: A Multi-objective Evolutionary Algorithm for Bi-clustering with Automatic Determination of the Number of Bi-clusters

Author

Bousselmi, Meriem, Bechikh, Slim, Hung, Chih-Cheng, Said, Lamjed Ben, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Liu, Derong, editor, Xie, Shengli, editor, Li, Yuanqing, editor, Zhao, Dongbin, editor, and El-Alfy, El-Sayed M., editor

Published
2017
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42. On the use of many quality attributes for software refactoring: a many-objective search-based software engineering approach

Author

Mkaouer, Mohamed, Kessentini, Marouane, Bechikh, Slim, Ó Cinnéide, Mel, and Deb, Kalyanmoy

Abstract

Search-based software engineering (SBSE) solutions are still not scalable enough to handle high-dimensional objectives space. The majority of existing work treats software engineering problems from a single or bi-objective point of view, where the main goal is to maximize or minimize one or two objectives. However, most software engineering problems are naturally complex in which many conflicting objectives need to be optimized. Software refactoring is one of these problems involving finding a compromise between several quality attributes to improve the quality of the system while preserving the behavior. To this end, we propose a novel representation of the refactoring problem as a many-objective one where every quality attribute to improve is considered as an independent objective to be optimized. In our approach based on the recent NSGA-III algorithm, the refactoring solutions are evaluated using a set of 8 distinct objectives. We evaluated this approach on one industrial project and seven open source systems. We compared our findings to: several other many-objective techniques (IBEA, MOEA/D, GrEA, and DBEA-Eps), an existing multi-objective approach a mono-objective technique and an existing refactoring technique not based on heuristic search. Statistical analysis of our experiments over 31 runs shows the efficiency of our approach.

Published
2024
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45. A Robust Multi-objective Approach for Software Refactoring under Uncertainty

Author

Mkaouer, Mohamed Wiem, Kessentini, Marouane, Bechikh, Slim, Ó Cinnéide, Mel, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Le Goues, Claire, editor, and Yoo, Shin, editor

Published
2014
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46. On the Use of Machine Learning and Search-Based Software Engineering for Ill-Defined Fitness Function: A Case Study on Software Refactoring

Author

Amal, Boukhdhir, Kessentini, Marouane, Bechikh, Slim, Dea, Josselin, Said, Lamjed Ben, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Le Goues, Claire, editor, and Yoo, Shin, editor

Published
2014
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