Machine learning with multimodal neuroimaging data to classify stages of Alzheimer's disease: A systematic review and meta-analysis
In recent years, Alzheimer's disease (AD) has been a serious threat to human health.
Researchers and clinicians alike encounter a significant obstacle when trying to accurately …
Researchers and clinicians alike encounter a significant obstacle when trying to accurately …
A small ship object detection method for satellite remote sensing data
X Fan, Z Hu, Y Zhao, J Chen, T Wei… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Satellite remote sensing technology can achieve real-time observation of ships at sea, and
the remote sensing images obtained have the advantages of high contrast and low noise …
the remote sensing images obtained have the advantages of high contrast and low noise …
CrossFuse: A novel cross attention mechanism based infrared and visible image fusion approach
Multimodal visual information fusion aims to integrate the multi-sensor data into a single
image which contains more complementary information and less redundant features …
image which contains more complementary information and less redundant features …
Spatio-temporal fusion methods for spectral remote sensing: A comprehensive technical review and comparative analysis
For many years, spectral remote sensing has been essential for research on the Earth's
surface. The data from a single satellite sensor is sometimes insufficient to fulfil the …
surface. The data from a single satellite sensor is sometimes insufficient to fulfil the …
HS2P: Hierarchical spectral and structure-preserving fusion network for multimodal remote sensing image cloud and shadow removal
Optical remote sensing images are often contaminated by clouds and shadows, resulting in
missing data, which greatly hinders consistent Earth observation missions. Cloud and …
missing data, which greatly hinders consistent Earth observation missions. Cloud and …
A comparative analysis of multi-label deep learning classifiers for real-time vehicle detection to support intelligent transportation systems
D Shokri, C Larouche, S Homayouni - Smart Cities, 2023 - mdpi.com
An Intelligent Transportation System (ITS) is a vital component of smart cities due to the
growing number of vehicles year after year. In the last decade, vehicle detection, as a …
growing number of vehicles year after year. In the last decade, vehicle detection, as a …
TGF: Multiscale transformer graph attention network for multi-sensor image fusion
Multisensor image fusion is a challenging task that aims to produce a composite image by
fusing visible (VI) and infrared (IR) images. Deep neural networks have shown impressive …
fusing visible (VI) and infrared (IR) images. Deep neural networks have shown impressive …
Hybrid cGAN: Coupling global and local features for SAR-to-optical image translation
Z Wang, Y Ma, Y Zhang - IEEE Transactions on Geoscience …, 2022 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) has the advantage of all-weather observation, but its imaging
principle based on the backscattering of electromagnetic waves makes its information less …
principle based on the backscattering of electromagnetic waves makes its information less …
Multimodal fusion-based spatiotemporal incremental learning for ocean environment perception under sparse observation
L Lei, J Huang, Y Zhou - Information Fusion, 2024 - Elsevier
Accurate ocean environment perception is crucial for weather and climate prediction.
Environmental limitations and deployment costs constrain satellite and buoy real-time …
Environmental limitations and deployment costs constrain satellite and buoy real-time …
MBHFuse: A multi-branch heterogeneous global and local infrared and visible image fusion with differential convolutional amplification features
Fusing infrared and visible imagery aims to harness their complementary spectral data,
enhancing output image quality, sharpness, and content. However, convolutional neural …
enhancing output image quality, sharpness, and content. However, convolutional neural …