Machine learningDeep learning / NLP / CV
目标检测
目标检测是一项计算机视觉任务，其中深度神经网络同时在图像中定位并分类一个或多个对象类别的每个实例，为每个检测到的对象生成边界框和类别标签。从R-CNN系列到YOLO和DETR等现代检测器，在标准基准测试上均能以接近人类的准确率实现实时速度。
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来源
- Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014). Rich feature hierarchies for accurate object detection and semantic segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 580–587. DOI: 10.1109/CVPR.2014.81 ↗
- Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You Only Look Once: Unified, Real-Time Object Detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 779–788. DOI: 10.1109/CVPR.2016.91 ↗
如何引用本页
ScholarGate. (2026, June 3). Object Detection (Region-Based and Anchor-Free Deep Neural Network Models). ScholarGate. https://scholargate.app/zh/deep-learning/object-detection
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