Machine learningDeep learning / NLP / CV
基于对象检测的迁移学习
基于对象检测的迁移学习始于在大型图像数据集（通常是用于骨干网络的ImageNet或用于完整检测器的COCO）上预训练的深度神经网络，并将其应用于新领域中的对象检测。通过重用学习到的视觉表征，它能够以远少于从头开始训练所需的标注图像获得强大的检测精度。
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来源
- 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 ↗
- Ren, S., He, K., Girshick, R., & Sun, J. (2015). Faster R-CNN: Towards real-time object detection with region proposal networks. Advances in Neural Information Processing Systems (NeurIPS), 28. link ↗
如何引用本页
ScholarGate. (2026, June 3). Transfer Learning Applied to Object Detection. ScholarGate. https://scholargate.app/zh/deep-learning/transfer-learning-with-object-detection
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