no code implementations • 25 Jul 2024 • Shahab Saquib Sohail, Yassine Himeur, Hamza Kheddar, Abbes Amira, Fodil Fadli, Shadi Atalla, Abigail Copiaco, Wathiq Mansoor
Additionally, DA, which is a subset of DTL, has been modified to enhance the point cloud data's quality by dealing with noise and missing points.
no code implementations • 30 May 2024 • Amine Bechar, Youssef Elmir, Yassine Himeur, Rafik Medjoudj, Abbes Amira
This review article discusses the roles of federated learning (FL) and transfer learning (TL) in cancer detection based on image analysis.
no code implementations • 30 May 2024 • Abdelmalik Ouamane, Ammar Chouchane, Yassine Himeur, Abderrazak Debilou, Abbes Amira, Shadi Atalla, Wathiq Mansoor, Hussain Al Ahmad
Machine learning has revolutionized the field of agricultural science, particularly in the early detection and management of plant diseases, which are crucial for maintaining crop health and productivity.
no code implementations • 18 Mar 2024 • Hamza Kheddar, Yassine Himeur, Abbes Amira, Rachik Soualah
The review concludes with an analysis of the current state of HEP, using DL methodologies.
no code implementations • 13 Feb 2024 • Fodil Fadli, Yassine Himeur, Mariam Elnour, Abbes Amira
Anomaly detection in sport facilities has gained significant attention due to its potential to promote energy saving and optimizing operational efficiency.
no code implementations • 28 Nov 2023 • Yassine Himeur, Aya Nabil Sayed, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira
The digital landscape of the Internet of Energy (IoE) is on the brink of a revolutionary transformation with the integration of edge Artificial Intelligence (AI).
no code implementations • 16 Nov 2023 • Amine Bechar, Youssef Elmir, Rafik Medjoudj, Yassine Himeur, Abbes Amira
This paper analyzes and criticizes each method of TL based on image analysis and compares the results of each method, showing that transformers have achieved the best results with an accuracy of 97. 41% for colon cancer detection and 94. 71% for Histopathological Lung cancer.
no code implementations • 24 Aug 2023 • Yassine Himeur, Iraklis Varlamis, Hamza Kheddar, Abbes Amira, Shadi Atalla, Yashbir Singh, Faycal Bensaali, Wathiq Mansoor
Computer Vision (CV) is playing a significant role in transforming society by utilizing machine learning (ML) tools for a wide range of tasks.
no code implementations • 8 Aug 2023 • Hamza Kheddar, Mustapha Hemis, Yassine Himeur, David Megías, Abbes Amira
The paper provides a systematic review of recent research in the field, including data sets and evaluation metrics used in recent studies.
no code implementations • 25 Jul 2023 • Youssef Elmir, Yassine Himeur, Abbes Amira
This paper study provides a novel contribution to the field of signal processing and DL for ECG signal analysis by introducing a new feature representation method for ECG signals.
no code implementations • 14 Jul 2023 • Hafsa Bousbiat, Yassine Himeur, Abbes Amira, Wathiq Mansoor
Non-intrusive Load Monitoring (NILM) algorithms, commonly referred to as load disaggregation algorithms, are fundamental tools for effective energy management.
no code implementations • 2 Jul 2023 • Qazi Mohammad Areeb, Mohammad Nadeem, Shahab Saquib Sohail, Raza Imam, Faiyaz Doctor, Yassine Himeur, Amir Hussain, Abbes Amira
A filter bubble refers to the phenomenon where Internet customization effectively isolates individuals from diverse opinions or materials, resulting in their exposure to only a select set of content.
no code implementations • 27 Apr 2023 • Hamza Kheddar, Yassine Himeur, Somaya Al-Maadeed, Abbes Amira, Faycal Bensaali
Moreover, DL techniques and machine learning (ML) approaches in general, hypothesize that training and testing data come from the same domain, with the same input feature space and data distribution characteristics.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
no code implementations • 17 Apr 2023 • Hafsa Bousbiat, Roumaysa Bousselidj, Yassine Himeur, Abbes Amira, Faycal Bensaali, Fodil Fadli, Wathiq Mansoor, Wilfried Elmenreich
Consumer's privacy is a main concern in Smart Grids (SGs) due to the sensitivity of energy data, particularly when used to train machine learning models for different services.
no code implementations • 22 Nov 2021 • Yassine Himeur, Aya Sayed, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira, Iraklis Varlamis, Magdalini Eirinaki, Christos Sardianos, George Dimitrakopoulos
Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc.
no code implementations • 10 Mar 2021 • Ayman Al-Kababji, Abbes Amira, Faycal Bensaali, Abdulah Jarouf, Lisan Shidqi, Hamza Djelouat
Fall detection is a serious healthcare issue that needs to be solved.
no code implementations • 9 Feb 2021 • Yassine Himeur, Abdullah Alsalemi, Ayman Al-Kababji, Faycal Bensaali, Abbes Amira, Christos Sardianos, George Dimitrakopoulos, Iraklis Varlamis
Recommender systems have significantly developed in recent years in parallel with the witnessed advancements in both internet of things (IoT) and artificial intelligence (AI) technologies.
no code implementations • 9 Feb 2021 • Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira
Non-intrusive load monitoring (NILM) is a key cost-effective technology for monitoring power consumption and contributing to several challenges encountered when transiting to an efficient, sustainable, and competitive energy efficiency environment.
Non-Intrusive Load Monitoring
Computers and Society
1 code implementation • 10 Dec 2020 • Abdullah Alsalemi, Yassine Himeur, Faycal Bensaali, Abbes Amira
Human population are striving against energy-related issues that not only affects society and the development of the world, but also causes global warming.
no code implementations • 10 Oct 2020 • Christos Sardianos, Iraklis Varlamis, Christos Chronis, George Dimitrakopoulos, Abdullah Alsalemi, Yassine Himeur, Faycal Bensaali, Abbes Amira
Recommendation systems are intelligent systems that support human decision making, and as such, they have to be explainable in order to increase user trust and improve the acceptance of recommendations.
no code implementations • 3 Oct 2020 • Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira
Identifying domestic appliances in the smart grid leads to a better power usage management and further helps in detecting appliance-level abnormalities.
no code implementations • 17 Sep 2020 • Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira
This paper proposes a new appliance identification scheme by introducing a novel approach for extracting highly discriminative characteristic sets that can considerably distinguish between various appliance footprints.
no code implementations • 14 Sep 2020 • Yassine Himeur, Abdullah Alsalemi, Ayman Al-Kababji, Faycal Bensaali, Abbes Amira
Recently, tremendous interest has been devoted to develop data fusion strategies for energy efficiency in buildings, where various kinds of information can be processed.
1 code implementation • 27 Jun 2019 • Sahar Soheilian Esfahani, Xiaojun Zhai, Minsi Chen, Abbes Amira, Faycal Bensaali, Julien AbiNahed, Sarada Dakua, Georges Younes, Robin A. Richardson, Peter V. Coveney
A weakness in the wall of a cerebral artery causing a dilation or ballooning of the blood vessel is known as a cerebral aneurysm.