A survey on deep learning for multimodal data fusion
With the wide deployments of heterogeneous networks, huge amounts of data with
characteristics of high volume, high variety, high velocity, and high veracity are generated …
characteristics of high volume, high variety, high velocity, and high veracity are generated …
Knowledge discovery in smart city digital twins
N Mohammadi, J Taylor - 2020 - scholarspace.manoa.hawaii.edu
Despite the abundance of available urban data and the potential for reaching enhanced
capabilities in the decision-making and management of city infrastructure, current data …
capabilities in the decision-making and management of city infrastructure, current data …
Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions
The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …
lives, including environmental pollution, public security, road congestion, etc. New …
CMGFNet: A deep cross-modal gated fusion network for building extraction from very high-resolution remote sensing images
The extraction of urban structures such as buildings from very high-resolution (VHR) remote
sensing imagery has improved dramatically, thanks to recent developments in deep …
sensing imagery has improved dramatically, thanks to recent developments in deep …
The geopolitics of smart city digital twins: Urban sensing and immersive virtual technologies, spatio-temporal fusion algorithms, and visualization modeling tools
Based on an in-depth survey of the literature, the purpose of the paper is to explore digital
twin modeling, multi-sensor data fusion techniques, and geo-spatial mapping and virtual …
twin modeling, multi-sensor data fusion techniques, and geo-spatial mapping and virtual …
Deep learning city: a big data analytics framework for smart cities
HJ Kim - Informatization Policy, 2017 - koreascience.kr
As city functions develop more complex and advanced, interests in smart cities are also
increasing. Smart cities refer to the cities effectively solving urban problems such as traffic …
increasing. Smart cities refer to the cities effectively solving urban problems such as traffic …
[PDF][PDF] Big data and context–aware computing applications for smart sustainable cities
SE Bibri, J Krogstie - 2nd Norwegian Big Data Symposium …, 2016 - researchgate.net
Information processing is increasingly embedded in the systems and processes of the
contemporary city to enhance its operations, functions, and designs. This has been fueled by …
contemporary city to enhance its operations, functions, and designs. This has been fueled by …
A survey on an emerging area: Deep learning for smart city data
Rapid urbanization has brought about great challenges to our daily lives, such as traffic
congestion, environmental pollution, energy consumption, public safety, and so on …
congestion, environmental pollution, energy consumption, public safety, and so on …
A comparative review on multi-modal sensors fusion based on deep learning
The wide deployment of multi-modal sensors in various areas generates vast amounts of
data with characteristics of high volume, wide variety, and high integrity. However, traditional …
data with characteristics of high volume, wide variety, and high integrity. However, traditional …
: A Deep Learning Architecture for Multiscale Multimodal Multitemporal Satellite Data Fusion
Modern Earth Observation systems provide remote sensing data at different temporal and
spatial resolutions. Among all the available spatial mission, today the Sentinel-2 program …
spatial resolutions. Among all the available spatial mission, today the Sentinel-2 program …