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3D point cloud enhancement using unsupervised anomaly detection
(
Institute of Electrical and Electronics Engineers Inc. (IEEE)
, 2019 , Conference Paper)
3D point cloud is increasingly getting attention for perceiving 3D environment which is needed in many emerging applications. This data structure is challenging due to its characteristics and the limitation of the acquisition ...
Exploring 2D Representation and Transfer Learning Techniques for People Identification in Indoor Localization
(
Institute of Electrical and Electronics Engineers Inc. (IEEE)
, 2023 , Conference Paper)
Indoor localization is a crucial aspect of various disciplines in our daily lives. It enables efficient administration tasks and improves safety by identifying the position of items or people inside spaces, making it useful ...
Recommendation System Towards Residential Energy Saving Based on Anomaly Detection
(
Institute of Electrical and Electronics Engineers Inc. (IEEE)
, 2022 , Conference Paper)
This paper presents a recommender system to promote energy consumption reduction behaviors in residential buildings. The system exploits data stream processing methods jointly with machine learning algorithms on real-time ...
Point-Denoise: Unsupervised outlier detection for 3D point clouds enhancement
(
Springer Nature
, 2021 , Article)
3D point cloud denoising is an increasingly demanding field as such type of data structure is getting more attention in perceiving the 3D environment for diverse applications. Despite their novelty, recently proposed ...
Exploring Deep Time-Series Imaging for Anomaly Detection of Building Energy Consumption
(
Institute of Electrical and Electronics Engineers Inc. (IEEE)
, 2022 , Conference Paper)
Although deep anomaly detection (DAD) is crucial to optimize energy management in smart buildings, there is a lack of efficient research investigating DAD of energy consumption time-series. Besides, analyzing one-dimensional ...
An innovative deep anomaly detection of building energy consumption using energy time-series images
(
Elsevier
, 2023 , Article)
Deep anomaly detection (DAD) is essential in optimizing building energy management. Nonetheless, most existing works concerning this field consider unsupervised learning and involve the analysis of sensor readings through ...
A Two-Stage Energy Anomaly Detection for Edge-based Building Internet of Things (BIoT) Applications
(
Institute of Electrical and Electronics Engineers Inc. (IEEE)
, 2022 , Conference Paper)
The Building Internet of Energy (BIoE) is quite promising for curtailing energy consumption, reducing costs, and promoting building transformation. Integrating Artificial Intelligence into the BIoE is essential for big ...