Results 41 to 50 of about 38,453 (306)

XDOcc: An Explainable Artificial Intelligence Empowered Deep Framework for Occupancy Detection and Occupant Count Estimation

IEEE Access
This study introduces explainable deep occupancy, a robust framework empowered by explainable artificial intelligence for high-accuracy occupancy detection and occupant count estimation in smart buildings.
Zeynep Turgut
doaj   +1 more source

Fault Detection and Diagnosis of a Photovoltaic System Based on Deep Learning Using the Combination of a Convolutional Neural Network (CNN) and Bidirectional Gated Recurrent Unit (Bi-GRU)

Sustainability
The meticulous monitoring and diagnosis of faults in photovoltaic (PV) systems enhances their reliability and facilitates a smooth transition to sustainable energy.
Ahmed Faris Amiri, S. Kichou, H. Oudira, A. Chouder, Santiago Silvestre   +4 more
semanticscholar   +1 more source

Two-Stream RNN/CNN for Action Recognition in 3D Videos

, 2018
The recognition of actions from video sequences has many applications in health monitoring, assisted living, surveillance, and smart homes. Despite advances in sensing, in particular related to 3D video, the methodologies to process the data are still ...
Ali, Haider, van der Smagt, Patrick, Zhao, Rui   +2 more
core   +1 more source

Short-Term Three-Phase Load Prediction With Advanced Metering Infrastructure Data in Smart Solar Microgrid Based Convolution Neural Network Bidirectional Gated Recurrent Unit

IEEE Access, 2022
The collaboration development between the power supply, solar power, and storage batteries is a formidable commission in the smart solar microgrid.
Phuong Nguyen Thanh, M. Cho, Chun-Lung Chang, Meng Chen   +3 more
semanticscholar   +1 more source

A novel monitoring system for fall detection in older people [PDF]

, 2018
Indexación: Scopus.This work was supported in part by CORFO - CENS 16CTTS-66390 through the National Center on Health Information Systems, in part by the National Commission for Scientific and Technological Research (CONICYT) through the Program STIC ...
De Albuquerque, V.H.C., Demongeot, J., Fuentes, P., Martinez, F., Munoz, R., Olivares, R., Rodenas, T., Taramasco, C.   +7 more
core   +1 more source

Numerical Weather Prediction Correction Strategy for Short-Term Wind Power Forecasting Based on Bidirectional Gated Recurrent Unit and XGBoost

Frontiers in Energy Research, 2022
Accurate short-term wind power forecasting (WPF) plays a crucial role in grid scheduling and wind power accommodation. Numerical weather prediction (NWP) wind speed is the fundamental data for short-term WPF.
Yu Li, Fei Tang, Xin Gao, Tongyan Zhang, Junfeng Qi, Jiarui Xie, Xinang Li, Yuhan Guo   +7 more
semanticscholar   +1 more source

Seismic phase recognition model with low SNR based on U-net

Geomatics, Natural Hazards & Risk
Aiming at the problem of low recognition accuracy and high missed detection rate of seismic phase recognition of low signal-to-noise ratio seismic signals, a new seismic phase recognition model UBAN (U-net-Bidirectional Gated Recurrent Unit-Attention ...
Jianxian Cai, Zhongjie Sun, Mengying Zhang, Fenfen Yan, Li Wang, Ling Li   +5 more
doaj   +1 more source

Multi-modal gated recurrent units for image description

, 2018
Using a natural language sentence to describe the content of an image is a challenging but very important task. It is challenging because a description must not only capture objects contained in the image and the relationships among them, but also be ...
Li, Xuelong, Lu, Xiaoqiang, Yuan, Aihong
core   +1 more source

Aircraft Trajectory Prediction Based on Bayesian Optimised Temporal Convolutional Network–Bidirectional Gated Recurrent Unit Hybrid Neural Network

International Journal of Aerospace Engineering, 2022
Efficient and accurate flight trajectory prediction is a key technology for promoting intelligent and informative air traffic management and improving the operational capabilities and predictability of air traffic.
Jin Huang, Weijie Ding
semanticscholar   +1 more source

Uncertainty quantification-based framework for predicting degradation trends of proton exchange membrane fuel cell

Green Energy and Intelligent Transportation
Accurately predicting the degradation trends of proton exchange membrane fuel cells (PEMFCs) can provide a solid basis for optimizing the control of vehicles and stations based on PEMFCs.
Bingxin Guo, Changjun Xie, Wenchao Zhu, Yang Yang, Hao Li, Yang Li, Hangyu Wu   +6 more
doaj   +1 more source