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Bag of Freebies for Training Object Detection Neural Networks
时间 2020-12-23
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李沐等将目标检测绝对精度提升 5%,不牺牲推理速度。 目标检测无疑是计算机视觉领域最前沿的应用之一,吸引了各个领域诸多研究者的目光。最前沿的检测器,包括类似 RCNN 的单(SSD 或 YOLO)或多阶神经网络都是基于图像分类骨干网络,如 VGG、ResNet、Inception 或 MobileNet 系列。 然而,由于模型容量和训练复杂度相对较高,目标检测受到的关注相对较少,从最近的训练微调研
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相关文章
1.
Bag of Freebies for Training Object Detection Neural Networks
2.
论文解读-Bag of Freebies for Training Object Detection Neural Networks
3.
论文笔记:Bag of Freebies for Training Object Detection Neural Networks
4.
《Bag of Freebies for Training Object Detection Neural Networks》论文理解
5.
论文阅读:Bag of Freebies for Training Object Detection Neural Networks
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Bag of Freebies for Training Object Detection Neural Networks 论文笔记
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Bag of Freebies for Training Object Detection Neural Networks学习笔记
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