Machine learningDeep learning / NLP / CV
实例分割迁移学习
实例分割迁移学习复用在大型图像语料库（通常是ImageNet或COCO）上预训练的骨干卷积网络作为特征提取器，用于Mask R-CNN等实例分割模型，然后在一个较小的目标数据集上对整个流程进行微调。这种方法以训练所需标注数据和计算量的一小部分，实现了最先进的每个对象掩码精度。
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来源
- He, K., Gkioxari, G., Dollar, P., & Girshick, R. (2017). Mask R-CNN. Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2961–2969. DOI: 10.1109/ICCV.2017.322 ↗
- Pan, S. J., & Yang, Q. (2010). A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345–1359. DOI: 10.1109/TKDE.2009.191 ↗
如何引用本页
ScholarGate. (2026, June 3). Transfer Learning Applied to Instance Segmentation Networks. ScholarGate. https://scholargate.app/zh/deep-learning/transfer-learning-with-instance-segmentation
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