Large vision-language models (LVLMs) can be adapted to specialized medical imaging tasks via parameter-efficient fine-tuning approaches such as low-rank adaptation (LoRA), leading to a growing ecosystem of expert models tailored to specific imaging modalities and clinical scenari…
Large vision-language models (LVLMs) have achieved strong performance across many medical imaging tasks, yet their application to ultrasound remains limited due to its inherent complexity and variability. In this work, we revisit what is truly needed to enable real-world ultrasou…
Abstract Quantum machine learning (QML) has gained increasing attention as a potential framework to address certain data analysis challenges in the future. Earth observation (EO) has entered the era of Big Data, where increasingly sophisticated deep learning models often require…