collaborators

5 papers

cs.CV2026

An Edge-aware Prompt-enhanced SAM for Ultrasound Image Segmentation

Wenhao Li, Fangyi Liu, Bo Du

Ultrasound image segmentation is essential for delineating anatomical structures and lesions, providing the foundation for accurate diagnosis. While the Segment Anything Model (SAM…

cs.CV2026

Echo-DM: Ultrasound Marker Removal via Conditional Latent Diffusion and Region-Aware Fusion

Zhiwei Wang, Tao Huang, Wentao Jiang +7

Clinical ultrasound images often contain artificial markers, such as measurement calipers and text, to assist diagnostic interpretation and comparison. However, these markers can i…

quant-ph2025

AiDE-Q: Synthetic Labeled Datasets Can Enhance Learning Models for Quantum Property Estimation

Xinbiao Wang, Yuxuan Du, Zihan Lou +5

Quantum many-body problems are central to various scientific disciplines, yet their ground-state properties are intrinsically challenging to estimate. Recent advances in deep learn…

quant-ph2025

Demonstration of Efficient Predictive Surrogates for Large-scale Quantum Processors

Wei-You Liao, Yuxuan Du, Xinbiao Wang +5

The ongoing development of quantum processors is driving breakthroughs in scientific discovery. Despite this progress, the formidable cost of fabricating large-scale quantum proces…

cs.LG2025

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging

Anke Tang, Enneng Yang, Li Shen +4

Deep model merging represents an emerging research direction that combines multiple fine-tuned models to harness their specialized capabilities across different tasks and domains.…