Big spatial data for urban and environmental sustainability
Eighty percent of big data are associated with spatial information, and thus are Big Spatial
Data (BSD). BSD provides new and great opportunities to rework problems in urban and …
Data (BSD). BSD provides new and great opportunities to rework problems in urban and …
Virtual Reality and Internet of Things Based Digital Twin for Smart City Cross-Domain Interoperability
G del Campo, E Saavedra, L Piovano, F Luque… - Applied Sciences, 2024 - mdpi.com
Featured Application Management of Smart City services using Digital Twin concept with the
integration of Internet of Things and Virtual Reality. Special focus in interoperability to …
integration of Internet of Things and Virtual Reality. Special focus in interoperability to …
Multimodal deep learning for GeoAI
C Sui, D Hong - Advances in Machine Learning and Image Analysis for …, 2024 - Elsevier
With the rapid advancement in remote sensing (RS) technology, a huge amount of Earth
observation (EO) data featuring considerable and complicated heterogeneity is readily …
observation (EO) data featuring considerable and complicated heterogeneity is readily …
[HTML][HTML] Deep learning in multimodal remote sensing data fusion: A comprehensive review
With the extremely rapid advances in remote sensing (RS) technology, a great quantity of
Earth observation (EO) data featuring considerable and complicated heterogeneity are …
Earth observation (EO) data featuring considerable and complicated heterogeneity are …
Identification of urban functional areas based on the multimodal deep learning fusion of high-resolution remote sensing images and Social Perception Data
L Xie, X Feng, C Zhang, Y Dong, J Huang, K Liu - Buildings, 2022 - mdpi.com
As the basic spatial unit of urban planning and management, it is necessary to know the
distribution status of urban functional areas in time. Due to the complexity of urban land use …
distribution status of urban functional areas in time. Due to the complexity of urban land use …
Cloud-Device Collaborative Learning for Multimodal Large Language Models
The burgeoning field of Multimodal Large Language Models (MLLMs) has exhibited
remarkable performance in diverse tasks such as captioning commonsense reasoning and …
remarkable performance in diverse tasks such as captioning commonsense reasoning and …
Digital twin modeling, multi-sensor fusion technology, and data mining algorithms in cloud and edge computing-based Smart city environments
This article reviews and advances existing literature concerning digital twin modeling, multi-
sensor fusion technology, and data mining algorithms in cloud and edge computing-based …
sensor fusion technology, and data mining algorithms in cloud and edge computing-based …
GAF-Net: improving the performance of remote sensing image fusion using novel global self and cross attention learning
The notion of self and cross-attention learning has been found to substantially boost the
performance of remote sensing (RS) image fusion. However, while the self-attention models …
performance of remote sensing (RS) image fusion. However, while the self-attention models …
Multilevel spatial-channel feature fusion network for urban village classification by fusing satellite and streetview images
Urban villages (UVs) refer to areas of urban informal settlements lagging behind the rapid
urbanization process. Recent studies focus on using satellite images to classify UV …
urbanization process. Recent studies focus on using satellite images to classify UV …
Spatio–temporal–spectral collaborative learning for spatio–temporal fusion with land cover changes
Spatio-temporal fusion by combining the complementary spatial and temporal advantages of
multisource remote-sensing images to obtain time-series high spatial resolution images is …
multisource remote-sensing images to obtain time-series high spatial resolution images is …