7 papers · 1 filter
CycleULM: A unified label-free deep learning framework for ultrasound localisation microscopy
Su Yan, Clara Rodrigo Gonzalez, Vincent C. H. Leung +11
Super-resolution ultrasound via microbubble (MB) localisation and tracking, also known as ultrasound localisation microscopy (ULM), can resolve microvasculature beyond the acoustic…
Leveraging Overfitting for Low-Complexity and Modality-Agnostic Joint Source-Channel Coding
Haotian Wu, Gen Li, Pier Luigi Dragotti +1
This paper introduces Implicit-JSCC, a novel overfitted joint source-channel coding paradigm that directly optimizes channel symbols and a lightweight neural decoder for each sourc…
LotteryCodec: Searching the Implicit Representation in a Random Network for Low-Complexity Image Compression
Haotian Wu, Gongpu Chen, Pier Luigi Dragotti +1
We introduce and validate the lottery codec hypothesis, which states that untrained subnetworks within randomly initialized networks can serve as synthesis networks for overfitted…
Trustworthy Image Super-Resolution via Generative Pseudoinverse
Andreas Floros, Seyed-Mohsen Moosavi-Dezfooli, Pier Luigi Dragotti
We consider the problem of trustworthy image restoration, taking the form of a constrained optimization over the prior density. To this end, we develop generative models for the ta…
SING: Semantic Image Communications using Null-Space and INN-Guided Diffusion Models
Jiakang Chen, Selim F. Yilmaz, Di You +2
Joint source-channel coding systems based on deep neural networks (DeepJSCC) have recently demonstrated remarkable performance in wireless image transmission. Existing methods prim…
A Lightweight Deep Exclusion Unfolding Network for Single Image Reflection Removal
Jun-Jie Huang, Tianrui Liu, Zihan Chen +3
Single Image Reflection Removal (SIRR) is a canonical blind source separation problem and refers to the issue of separating a reflection-contaminated image into a transmission and…