arXiv:2101.10815
공식 코드 · Papers with Code
Loss Ensembles for Extremely Imbalanced Segmentation
원문 초록
This short paper briefly presents our methodology details of automatic intracranial aneurysms segmentation from brain MR scans. We use ensembles of multiple models trained from different loss functions. Our method ranked first place in the ADAM challenge segmentation task. The code and trained models are publicly available at https://github.com/JunMa11/ADAM2020.
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Alleviating Textual Reliance in Medical Language-guided Segmentation via Prototype-driven Semantic Approximation
A New Dataset and Performance Benchmark for Real-time Spacecraft Segmentation in Onboard Flight Computers
Seg-Wild: Interactive Segmentation based on 3D Gaussian Splatting for Unconstrained Image Collections
PSAT: Pediatric Segmentation Approaches via Adult Augmentations and Transfer Learning
RSRefSeg 2: Decoupling Referring Remote Sensing Image Segmentation with Foundation Models
Learning Disentangled Stain and Structural Representations for Semi-Supervised Histopathology Segmentation
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