《Imbalance problems in object detection: A review》笔记
简介 论文《Imbalance problems in object detection: A review》对目标检测中的不平衡问题做了综合的叙述。该论文对目标检测的不平衡问题做了系统性的分类，根据相关的输入属性，把不平衡问题划分成4大类，8个小类。 与类别的不平衡问题相关的输入属性是不同类别的输入的边框数量，这也是这个类别的分类依据。前景类和背景类的边框数不同导致了前景-背景类别不平衡问题。而
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相关文章
- 1. 目标检测中的不平衡问题 open issues：Imbalance Problems in Object Detection: A Review
- 2. (Review cs231n) Object Detection
- 3. 论文笔记：Multiple Object Tracking: A Literature Review
- 4. Object Detection in 20 Years: A Survey
- 5. Overcoming Classififier Imbalance for Long-tail Object Detection with Balanced Group Softmax 阅读笔记
- 6. Object Detection in 20 Years: A Survey 综述论文笔记
- 7. 目标检测Object Detection in 20 Years: A Survey——学习笔记
- 8. DetNet: A Backbone network for Object Detection 笔记
- 9. (Few-shot Detection)Review: Fews-shot Object Detection Feature Reweighting
- 10. (2020.04) Review: YOLOv4: Optimal Speed and Accuracy of Object Detection