activity
20182026
most citedImage quality assessment for machine learning tasks using meta-reinforcement learning

51 citations · 178 across the 33 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.CV2025

Learning to learn skill assessment for fetal ultrasound scanning

Yipei Wang, Qianye Yang, Lior Drukker +3

Traditionally, ultrasound skill assessment has relied on expert supervision and feedback, a process known for its subjectivity and time-intensive nature. Previous works on quantita…

cs.CV2025

Neural Collapse-Inspired Multi-Label Federated Learning under Label-Distribution Skew

Can Peng, Yuyuan Liu, Yingyu Yang +3

Federated Learning (FL) enables collaborative model training across distributed clients while preserving data privacy, but remains challenging when client data are highly heterogen…

eess.IV2025★ 1 cited

Latent Motion Profiling for Annotation-free Cardiac Phase Detection in Adult and Fetal Echocardiography Videos

Yingyu Yang, Qianye Yang, Kangning Cui +6

The identification of cardiac phase is an essential step for analysis and diagnosis of cardiac function. Automatic methods, especially data-driven methods for cardiac phase detecti…

eess.IV2025

Asynchronous Federated Continual Segmentation with Evolving Clients and Label Spaces

Can Peng, Qianhui Men, Pramit Saha +5

Federated learning seeks to foster collaboration among distributed clients while preserving the privacy of their local data. Traditional federated learning methods typically assume…

cs.CV2025

Tell2Reg: Establishing spatial correspondence between images by the same language prompts

Wen Yan, Qianye Yang, Shiqi Huang +6

Spatial correspondence can be represented by pairs of segmented regions, such that the image registration networks aim to segment corresponding regions rather than predicting displ…