Multimodal data fusion: an overview of methods, challenges, and prospects
In various disciplines, information about the same phenomenon can be acquired from
different types of detectors, at different conditions, in multiple experiments or subjects …
different types of detectors, at different conditions, in multiple experiments or subjects …
Data fusion approaches for structural health monitoring and system identification: Past, present, and future
RT Wu, MR Jahanshahi - Structural Health Monitoring, 2020 - journals.sagepub.com
During the past decades, significant efforts have been dedicated to develop reliable
methods in structural health monitoring. The health assessment for the target structure of …
methods in structural health monitoring. The health assessment for the target structure of …
A deep translation (GAN) based change detection network for optical and SAR remote sensing images
With the development of space-based imaging technology, a larger and larger number of
images with different modalities and resolutions are available. The optical images reflect the …
images with different modalities and resolutions are available. The optical images reflect the …
Advanced multi-sensor optical remote sensing for urban land use and land cover classification: Outcome of the 2018 IEEE GRSS data fusion contest
This paper presents the scientific outcomes of the 2018 Data Fusion Contest organized by
the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and …
the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and …
Data fusion and remote sensing: An ever-growing relationship
Characterized by a certain focus on the heavily discussed topic of image fusion in its
beginnings, sensor data fusion has played a significant role in the remote sensing research …
beginnings, sensor data fusion has played a significant role in the remote sensing research …
A deep multitask learning framework coupling semantic segmentation and fully convolutional LSTM networks for urban change detection
M Papadomanolaki, M Vakalopoulou… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this article, we present a deep multitask learning framework able to couple semantic
segmentation and change detection using fully convolutional long short-term memory …
segmentation and change detection using fully convolutional long short-term memory …
Hierarchical attention feature fusion-based network for land cover change detection with homogeneous and heterogeneous remote sensing images
Deep learning techniques have become popular in land cover change detection (LCCD)
with remote sensing images (RSIs). However, many existing networks mostly concentrate on …
with remote sensing images (RSIs). However, many existing networks mostly concentrate on …
3D change detection–approaches and applications
Due to the unprecedented technology development of sensors, platforms and algorithms for
3D data acquisition and generation, 3D spaceborne, airborne and close-range data, in the …
3D data acquisition and generation, 3D spaceborne, airborne and close-range data, in the …
Hyperspectral and LiDAR data fusion: Outcome of the 2013 GRSS data fusion contest
C Debes, A Merentitis, R Heremans… - IEEE Journal of …, 2014 - ieeexplore.ieee.org
The 2013 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC)
of the IEEE Geoscience and Remote Sensing Society aimed at investigating the synergistic …
of the IEEE Geoscience and Remote Sensing Society aimed at investigating the synergistic …
A change detection approach to flood mapping in urban areas using TerraSAR-X
L Giustarini, R Hostache, P Matgen… - IEEE transactions on …, 2012 - ieeexplore.ieee.org
Very high resolution synthetic aperture radar (SAR) sensors represent an alternative to
aerial photography for delineating floods in built-up environments where flood risk is …
aerial photography for delineating floods in built-up environments where flood risk is …