Deep learning methods for medical image fusion: A review
T Zhou, QR Cheng, HL Lu, Q Li, XX Zhang… - Computers in Biology and …, 2023 - Elsevier
The image fusion methods based on deep learning has become a research hotspot in the
field of computer vision in recent years. This paper reviews these methods from five aspects …
field of computer vision in recent years. This paper reviews these methods from five aspects …
Satellite video super-resolution via multiscale deformable convolution alignment and temporal grouping projection
As a new earth observation tool, satellite video has been widely used in remote-sensing
field for dynamic analysis. Video super-resolution (VSR) technique has thus attracted …
field for dynamic analysis. Video super-resolution (VSR) technique has thus attracted …
Image super-resolution with an enhanced group convolutional neural network
CNNs with strong learning abilities are widely chosen to resolve super-resolution problem.
However, CNNs depend on deeper network architectures to improve performance of image …
However, CNNs depend on deeper network architectures to improve performance of image …
A review of aquaculture: From single modality analysis to multimodality fusion
Efficient management and accurate monitoring are crucial for the sustainable development
of the aquaculture industry. Traditionally, monitoring methods have relied on single-modality …
of the aquaculture industry. Traditionally, monitoring methods have relied on single-modality …
Deep blind super-resolution for satellite video
Recent efforts have witnessed remarkable progress in satellite video super-resolution
(SVSR). However, most SVSR methods usually assume the degradation is fixed and known …
(SVSR). However, most SVSR methods usually assume the degradation is fixed and known …
Feature dynamic alignment and refinement for infrared–visible image fusion: Translation robust fusion
Translational displacement between source images from different sensors is a general
phenomenon, which will cause performance degradation on image fusion. To tackle this …
phenomenon, which will cause performance degradation on image fusion. To tackle this …
Temporal consistency learning of inter-frames for video super-resolution
Video super-resolution (VSR) is a task that aims to reconstruct high-resolution (HR) frames
from the low-resolution (LR) reference frame and multiple neighboring frames. The vital …
from the low-resolution (LR) reference frame and multiple neighboring frames. The vital …
Deep learning in medical image super resolution: a review
H Yang, Z Wang, X Liu, C Li, J Xin, Z Wang - Applied Intelligence, 2023 - Springer
Super-resolution (SR) reconstruction is a hot topic in medical image processing. SR implies
reconstructing corresponding high-resolution (HR) images from observed low-resolution …
reconstructing corresponding high-resolution (HR) images from observed low-resolution …
[HTML][HTML] 数据驱动的多源遥感信息融合研究进展
张良培， 何江， 杨倩倩， 肖屹， 袁强强 - 2022 - xb.chinasmp.com
多源遥感信息融合技术是突破单一传感器的观测局限, 实现多平台多模态观测信息互补利用,
生成大场景高“时-空-谱” 无缝的观测数据的重要手段. 随着人工智能理论与技术的日益完善 …
生成大场景高“时-空-谱” 无缝的观测数据的重要手段. 随着人工智能理论与技术的日益完善 …
Deep object co-segmentation and co-saliency detection via high-order spatial-semantic network modulation
Object co-segmentation (CSG) is to segment the common objects of the same category in
multiple relevant images while the co-saliency detection (CSD) aims to discover the salient …
multiple relevant images while the co-saliency detection (CSD) aims to discover the salient …