Multimodal medical image fusion integrates complementary information from
different imaging modalities to enhance diagnostic accuracy and treatment
planning. While deep learning methods have advanced performance, existing
approaches face critical l... read more
Recovering fine-grained details in extremely dark images remains challenging
due to severe structural information loss and noise corruption. Existing
enhancement methods often fail to preserve intricate details and sharp edges,
limiting their effec... read more
In cross-modal retrieval tasks, such as image-to-report and report-to-image
retrieval, accurately aligning medical images with relevant text reports is
essential but challenging due to the inherent ambiguity and variability in
medical data. Existin... read more
In recent years,Diffusion models have achieved remarkable progress in the
field of image generation.However,recent studies have shown that diffusion
models are susceptible to backdoor attacks,in which attackers can manipulate
the output by injectin... read more
Weakly supervised visual grounding (VG) aims to locate objects in images
based on text descriptions. Despite significant progress, existing methods lack
strong cross-modal reasoning to distinguish subtle semantic differences in text
expressions due... read more
Inspired by mobile satellite communication systems and the important and
prevalent applications of computational tasks, we consider a distributed source
coding model for compressing vector-linear functions, which consists of
multiple sources, multi... read more
Diffusion models have been firmly established as principled zero-shot solvers
for linear and nonlinear inverse problems, owing to their powerful image prior
and iterative sampling algorithm. These approaches often rely on Tweedie's
formula, which r... read more
Galaxy image translation is an important application in galaxy physics and
cosmology. With deep learning-based generative models, image translation has
been performed for image generation, data quality enhancement, information
extraction, and gener... read more
The accurate state estimation of unknown bodies in space is a critical
challenge with applications ranging from the tracking of space debris to the
shape estimation of small bodies. A necessary enabler to this capability is to
find and track featur... read more
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