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[HTML][HTML] Comprehensive systematic review of information fusion methods in smart cities and urban environments
Smart cities result from integrating advanced technologies and intelligent sensors into
modern urban infrastructure. The Internet of Things (IoT) and data integration are pivotal in …
modern urban infrastructure. The Internet of Things (IoT) and data integration are pivotal in …
[HTML][HTML] Riverside landslide susceptibility overview: leveraging artificial neural networks and machine learning in accordance with the United Nations (UN) sustainable …
Riverside landslides present a significant geohazard globally, posing threats to
infrastructure and human lives. In line with the United Nations' Sustainable Development …
infrastructure and human lives. In line with the United Nations' Sustainable Development …
[HTML][HTML] A systematic review of data fusion techniques for optimized structural health monitoring
Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
[HTML][HTML] Deep learning for geological hazards analysis: Data, models, applications, and opportunities
As natural disasters are induced by geodynamic activities or abnormal changes in the
environment, geological hazards tend to wreak havoc on the environment and human …
environment, geological hazards tend to wreak havoc on the environment and human …
Iterative integration of deep learning in hybrid Earth surface system modelling
Earth system modelling (ESM) is essential for understanding past, present and future Earth
processes. Deep learning (DL), with the data-driven strength of neural networks, has …
processes. Deep learning (DL), with the data-driven strength of neural networks, has …
Towards neural Earth system modelling by integrating artificial intelligence in Earth system science
Earth system models (ESMs) are our main tools for quantifying the physical state of the Earth
and predicting how it might change in the future under ongoing anthropogenic forcing. In …
and predicting how it might change in the future under ongoing anthropogenic forcing. In …
Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects
Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Priority list of biodiversity metrics to observe from space
Monitoring global biodiversity from space through remotely sensing geospatial patterns has
high potential to add to our knowledge acquired by field observation. Although a framework …
high potential to add to our knowledge acquired by field observation. Although a framework …
Spectral super-resolution meets deep learning: Achievements and challenges
Spectral super-resolution (sSR) is a very important technique to obtain hyperspectral images
from only RGB images, which can effectively overcome the high acquisition cost and low …
from only RGB images, which can effectively overcome the high acquisition cost and low …
Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities
The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …
promises significant advances to support the Sustainable Development Goals (SDGs). New …