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Found 16 papers, 2 papers with code
Edge AI for Internet of Energy: Challenges and Perspectives
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).
Federated Learning for Computer Vision
Computer Vision (CV) is playing a significant role in transforming society by utilizing machine learning (ML) tools for a wide range of tasks.
Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalization
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)
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Crossing Roads of Federated Learning and Smart Grids: Overview, Challenges, and Perspectives
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.
Scheduling Techniques for Liver Segmentation: ReduceLRonPlateau Vs OneCycleLR
The reported results that have the same number of maximum epochs (75), and are the average of 5-fold cross-validation, indicate that ReduceLRonPlateau converges faster while maintaining a similar or even better loss score on the validation set when compared to OneCycleLR.
Blockchain-based Recommender Systems: Applications, Challenges and Future Opportunities
Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc.
Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations
Machine learning and computer vision techniques have grown rapidly in recent years due to their automation, suitability, and ability to generate astounding results.
An IoT-Based Framework for Remote Fall Monitoring
Fall detection is a serious healthcare issue that needs to be solved.
Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier
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
A survey of recommender systems for energy efficiency in buildings: Principles, challenges and prospects
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.
Appliance-Level Monitoring with Micro-Moment Smart Plugs
Human population are striving against energy-related issues that not only affects society and the development of the world, but also causes global warming.
The emergence of Explainability of Intelligent Systems: Delivering Explainable and Personalised Recommendations for Energy Efficiency
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.
Appliance identification using a histogram post-processing of 2D local binary patterns for smart grid applications
Identifying domestic appliances in the smart grid leads to a better power usage management and further helps in detecting appliance-level abnormalities.
Improving in-home appliance identification using fuzzy-neighbors-preserving analysis based QR-decomposition
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.
Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations
Recently, tremendous interest has been devoted to develop data fusion strategies for energy efficiency in buildings, where various kinds of information can be processed.
HEMELB Acceleration and Visualization for Cerebral Aneurysms
A weakness in the wall of a cerebral artery causing a dilation or ballooning of the blood vessel is known as a cerebral aneurysm.
