… -stream fusion network for solving remote sensing image fusion, ie pan-sharpening problem.
The proposed TFNets was motivated by the recent progresses achieved by deep learning …

… learning methods in image fusion. In this work, this survey reports on the development of
image fusion algorithms based on deep learning … fusion method of infrared and visible images …

… gives the fused image similar histogram distribution with source images, while the gradient
… for multiple image fusion tasks. To make the network adapt to different image fusion tasks, we …

… Existing learning-based IVIF methods tried to design … learning network to realize the IVIF
task, which can automatically discover the modality-oriented feature representation. Our network …

… to-end deep learning network, multi-layer concatenation fusion network (… image fusion
network based on end-to-end deep learning by designing and studying three basic neural network …

… faced in the field of medical image fusion. We characterize the … image fusion research
based on (1) the widely used image fusion methods, (2) imaging modalities, and (3) imaging of …

… images, we innovatively propose a conceptual image fusion architecture for supervised
biomedical image … The architecture has been optimized by testing different fusion schemes within …

… two-layer image fusion using DL to obtain more informative CXR images for a COVID-19 …
, the dataset used for this work includes 87 CXR images acquired from 25 cases, all of which …

… paper, based on deep learning, we … image fusion via generative adversarial networks (MEF-GAN).
In our MEF-GAN, given the overexposed and under-exposed images, the fused image …

… deep learning and maximum avoidance of weak points, we propose an unsupervised learning
network … To realize the infrared and visible image fusion task, we propose a novel network …