Assisted Excitation of Activations:A Learning Technique to Improve Object Detectors论文解读
Assisted Excitation of Activations:A Learning Technique to Improve Object Detectors 这是cvpr2019上的一篇文章，以yolo为例，没有修改网络结构，也没有增加额外的计算负担。 （1）目的：解决yolo定位不准确和样本不均匀的问题。 （2）改进点：在训练阶段加入Assisted Excitation（AE）模块，
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相关文章
- 1. Assisted Excitation of Activations: A Learning Technique to Improve Object Detect
- 2. Incremental Learning of Object Detectors without Catastrophic Forgetting 论文阅读
- 3. Incremental Learning of Object Detectors without Catastrophic Forgetting详解
- 4. DSOD： Learning Deeply Supervised Object Detectors from Scratch 论文解读
- 5. 论文阅读：Learning to Segment Object Candidates（DeepMask）
- 6. How To Improve Deep Learning Performance
- 7. 对抗样本(论文解读八):Towards More Robust Adversarial Attack Against Real World Object Detectors
- 8. 论文：Speed/accuracy trade-offs for object detectors
- 9. DSOD: Learning Deeply Supervised Object Detectors from Scratch 论文笔记
- 10. 对抗样本(论文解读一): DPATCH: An Adversarial Patch Attack on Object Detectors