Exemplar：融合经典先验与冻结特征实现显微镜图像少样本分割
原标题：Exemplar: Classical Priors Complement Frozen Features for Few-Shot Microscopy Segmentation at Native Resolution
AI 摘要
捷克理工大学的研究团队提出 Exemplar，一种用于显微镜图像少样本分割的模型，融合冻结的 DINOv3 特征与经典滤波器组，在 11 个生物医学数据集上达到 0.782 的平均分数，优于多种少样本方法。该模型在单张标注掩码下表现优于从头训练的 nnU-Net，但后者在八张掩码时反超。研究强调经典先验与自监督特征在少样本场景下的互补性。
正文节选
Exemplar: Classical Priors Complement Frozen Features for Few-Shot Microscopy Segmentation at Native Resolution Abstract Segmenting a new biomedical dataset usually means a domain-specific model trained on substantial annotation, or a foundation model steered at inference time. We present Exemplar, a few-shot segmenter that fuses a frozen DINOv3 backbone with a fixed bank of classical native-resolution filter responses in one lightweight head, fitted from the support masks alone. In the few-mask