Most data teams discover quality problems the same way: a dashboard looks wrong, a stakeholder files a ticket, and an engineer traces the damage backward through the pipeline. By then, the bad data ...
Abstract: Developing deep learning models for accurate segmentation of biomedical CT images is challenging due to their complex structures, anatomy variations, noise, and unavailability of sufficient ...
These local LLMs are changing the game in lots of fun ways.
Breast ultrasound interpretation requires simultaneous lesion segmentation and tissue classification, yet conventional multi-task learning approaches suffer from task interference and rigid ...