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Toward Unsupervised Energy Consumption Anomaly Detection
Existing high-performance Machine Learning models typically rely on large training datasets with high-quality manual annotations, which are difficult...
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Energy-efficient buildings with energy-efficient optimized models: a case study on thermal bridge detection
Thermographic inspection is particularly effective in identifying thermal bridges because it visualizes temperature differences on the building’s...
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Transformer-Based Anomaly Detection in Energy Consumption Data
As electric energy demand continues to rise, understanding electricity consumption habits and promptly detecting abnormal usage patterns are crucial...
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Occupancy detection via thermal sensors for energy consumption reduction
With the emergence of Internet of Things (IoT), the usage of sensors for controlling and monitoring remote devices to achieve sustainability has...
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Unified ensemble federated learning with cloud computing for online anomaly detection in energy-efficient wireless sensor networks
Anomaly detection in Wireless Sensor Networks (WSNs) is critical for their reliable and secure operation. Optimizing resource efficiency is crucial...
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Detection of Energy Consumption Cyber Attacks on Smart Devices
With the rapid development of the Internet of Things (IoT) technology, intelligent systems are increasingly finding their way into everyday life and...
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Data-Driven Energy Efficiency Evaluation and Energy Anomaly Detection of Multi-type Enterprises Based on Energy Consumption Big Data Mining
In view of the continuous improvement of the current energy consumption data of many types of enterprises, the effective monitoring of enterprise...
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Classification of incunable glyphs and out-of-distribution detection with joint energy-based models
Optical character recognition (OCR) has proved a powerful tool for the digital analysis of printed historical documents. However, its ability to...
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Energy-Constrained Model Pruning for Efficient In-Orbit Object Detection in Optical Remote Sensing Images
Efficient object detection from optical remote sensing (RS) images has always been an important interpretation task for in-orbit RS applications. In...
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Benchmarking of computer vision methods for energy-efficient high-accuracy olive fly detection on edge devices
The automation of insect pest control activities implies the use of classifiers to monitor the temporal and spatial evolution of the population using...
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Anomaly detection in quasi-periodic energy consumption data series: a comparison of algorithms
The diffusion of domotics solutions and of smart appliances and meters enables the monitoring of energy consumption at a very fine level and the...
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CNN-based speech segments endpoints detection framework using short-time signal energy features
The quality of Speech Recognition systems has improved, with a shift focus from short utterance scenarios like Voice Assistants and Voice Search to...
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Cluster head selection and malicious node detection using large-scale energy-aware trust optimization algorithm for HWSN
The widespread use of hierarchical wireless sensor networks (HWSN) in various industries, including environmental monitoring, healthcare, and...
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Fabric defect detection algorithm based on residual energy distribution and Gabor feature fusion
Gabor filter is a time-frequency combined analysis method, which is suitable for detecting local anomalies in periodic textures. Gabor-based methods...
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An energy-efficient and accuracy-aware edge computing framework for heart arrhythmia detection: A joint model selection and task offloading approach
IoT-based arrhythmia detection is one of the delay-sensitive applications that can benefit from edge computing to reduce the processing latency....
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ADEPT: Anomaly Detection, Explanation and Processing for Time Series with a Focus on Energy Consumption Data
Anomaly detection techniques are applicable for recognizing excessive energy consumption and device failure, thereby contributing to the maintenance...
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EnergyCIDN: Enhanced Energy-Aware Challenge-Based Collaborative Intrusion Detection in Internet of Things
With cyber attacks becoming more complex and advanced, a separate intrusion detection system (IDS) is believed to be insufficient for protecting the...
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eSeiz 2.0: An Optimized Pulse Exclusion Mechanism for Accurate and Energy-Efficient Seizure Detection in the IoMT
Approximately, 50 million people worldwide are impacted by epilepsy, necessitating the development of a seizure detection system that is low power,...
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Semantic segmentation supervised deep-learning algorithm for welding-defect detection of new energy batteries
As the main component of the new energy battery, the safety vent usually is welded on the battery plate, which can prevent unpredictable explosion...
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Applications of Machine Learning: Energy Systems
This chapter focuses on machine learning applications in electrical energy systems. The first application is load forecasting, followed by...