654 citations · 1.5k across the 27 of their papers we have counts for
30 papers
Edge AI for Internet of Energy: Challenges and Perspectives
Yassine Himeur, Aya Nabil Sayed, Abdullah Alsalemi +2
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). This comprehensiv…
Revolutionizing Customer Interactions: Insights and Challenges in Deploying ChatGPT and Generative Chatbots for FAQs
Feriel Khennouche, Youssef Elmir, Nabil Djebari +2
In the rapidly evolving domain of artificial intelligence, chatbots have emerged as a potent tool for various applications ranging from e-commerce to healthcare. This research delv…
Harnessing Transformers: A Leap Forward in Lung Cancer Image Detection
Amine Bechar, Youssef Elmir, Rafik Medjoudj +2
This paper discusses the role of Transfer Learning (TL) and transformers in cancer detection based on image analysis. With the enormous evolution of cancer patients, the identifica…
An Intelligent Edge-Deployable Indoor Air Quality Monitoring and Activity Recognition Approach
Mohamed Rafik Aymene Berkani, Ammar Chouchane, Yassine Himeur +2
The surveillance of indoor air quality is paramount for ensuring environmental safety, a task made increasingly viable due to advancements in technology and the application of arti…
Federated Learning for Computer Vision
Yassine Himeur, Iraklis Varlamis, Hamza Kheddar +5
Computer Vision (CV) is playing a significant role in transforming society by utilizing machine learning (ML) tools for a wide range of tasks. However, the need for large-scale dat…
Deep Learning for Steganalysis of Diverse Data Types: A review of methods, taxonomy, challenges and future directions
Hamza Kheddar, Mustapha Hemis, Yassine Himeur +2
Steganography and steganalysis are two interrelated aspects of the field of information security. Steganography seeks to conceal communications, whereas steganalysis is aimed to ei…
ECG classification using Deep CNN and Gramian Angular Field
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.…
On the Sensitivity of Deep Load Disaggregation to Adversarial Attacks
Hafsa Bousbiat, Yassine Himeur, Abbes Amira +1
Non-intrusive Load Monitoring (NILM) algorithms, commonly referred to as load disaggregation algorithms, are fundamental tools for effective energy management. Despite the success…
Filter Bubbles in Recommender Systems: Fact or Fallacy -- A Systematic Review
Qazi Mohammad Areeb, Mohammad Nadeem, Shahab Saquib Sohail +5
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 sel…
Crossing Roads of Federated Learning and Smart Grids: Overview, Challenges, and Perspectives
Hafsa Bousbiat, Roumaysa Bousselidj, Yassine Himeur +5
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. The…
Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalization
Hamza Kheddar, Yassine Himeur, Somaya Al-Maadeed +2
Automatic speech recognition (ASR) has recently become an important challenge when using deep learning (DL). It requires large-scale training datasets and high computational and st…
Intelligent edge-based recommender system for internet of energy applications
Aya Sayed, Yassine Himeur, Abdullah Alsalemi +2
Preserving energy in households and office buildings is a significant challenge, mainly due to the recent shortage of energy resources, the uprising of the current environmental pr…
Blockchain-based Recommender Systems: Applications, Challenges and Future Opportunities
Yassine Himeur, Aya Sayed, Abdullah Alsalemi +6
Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the a…
Marketability of building energy efficiency systems based on behavioral change: A case study of a novel micro-moments based solution
Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali +5
In spite of the substantial advance in developing energy-efficient buildings, power demand in the building sector is still remarkably growing due to teleworking and e-learning trig…
An IoT-Based Framework for Remote Fall Monitoring
Ayman Al-Kababji, Abbes Amira, Faycal Bensaali +3
Fall detection is a serious healthcare issue that needs to be solved. Falling without quick medical intervention would lower the chances of survival for the elderly, especially if…
A survey of recommender systems for energy efficiency in buildings: Principles, challenges and prospects
Yassine Himeur, Abdullah Alsalemi, Ayman Al-Kababji +5
Recommender systems have significantly developed in recent years in parallel with the witnessed advancements in both internet of things (IoT) and artificial intelligence (AI) techn…
Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier
Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali +1
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 ef…
Appliance-Level Monitoring with Micro-Moment Smart Plugs
Abdullah Alsalemi, Yassine Himeur, Faycal Bensaali +1
Human population are striving against energy-related issues that not only affects society and the development of the world, but also causes global warming. A variety of broad appro…
Cloud Energy Micro-Moment Data Classification: A Platform Study
Abdullah Alsalemi, Ayman Al-Kababji, Yassine Himeur +2
Energy efficiency is a crucial factor in the well-being of our planet. In parallel, Machine Learning (ML) plays an instrumental role in automating our lives and creating convenient…
The emergence of Explainability of Intelligent Systems: Delivering Explainable and Personalised Recommendations for Energy Efficiency
Christos Sardianos, Iraklis Varlamis, Christos Chronis +5
The recent advances in artificial intelligence namely in machine learning and deep learning, have boosted the performance of intelligent systems in several ways. This gave rise to…
Reshaping consumption habits by exploiting energy-related micro-moment recommendations: A case study
Christos Sardianos, Iraklis Varlamis, Christos Chronis +5
The environmental change and its effects, caused by human influences and natural ecological processes over the last decade, prove that it is now more prudent than ever to transitio…
Energy Data Visualizations on Smartphones for Triggering Behavioral Change: Novel Vs. Conventional
Ayman Al-Kababji, Abdullah Alsalemi, Yassine Himeur +4
This paper conveys the importance of using suitable data visualizations for electrical energy consumption and the effect it carries on reducing said consumption. Data visualization…
Appliance identification using a histogram post-processing of 2D local binary patterns for smart grid applications
Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali +1
Identifying domestic appliances in the smart grid leads to a better power usage management and further helps in detecting appliance-level abnormalities. An efficient identification…
Artificial Intelligence based Anomaly Detection of Energy Consumption in Buildings: A Review, Current Trends and New Perspectives
Yassine Himeur, Khalida Ghanem, Abdullah Alsalemi +2
Enormous amounts of data are being produced everyday by sub-meters and smart sensors installed in residential buildings. If leveraged properly, that data could assist end-users, en…