【论文笔记】Objects365: A Large-scale, High-quality Dataset for Object Detection(ICCV 2019)
内容:It is the largest object detection dataset (with full annotation) so far and establishes a more challenging benchmark for the community.

【论文笔记】Objects365: A Large-scale, High-quality Dataset for Object Detection(ICCV 2019)
作为预训练模型有更好的精确率和更快的收敛速度!
【论文笔记】Objects365: A Large-scale, High-quality Dataset for Object Detection(ICCV 2019)
介绍数据集的标注过程这样更清晰!

最大的亮点就是对数据集迁移能力的分析:
【论文笔记】Objects365: A Large-scale, High-quality Dataset for Object Detection(ICCV 2019)
【论文笔记】Objects365: A Large-scale, High-quality Dataset for Object Detection(ICCV 2019)
【论文笔记】Objects365: A Large-scale, High-quality Dataset for Object Detection(ICCV 2019)
【论文笔记】Objects365: A Large-scale, High-quality Dataset for Object Detection(ICCV 2019)
【论文笔记】Objects365: A Large-scale, High-quality Dataset for Object Detection(ICCV 2019)
Iterations

所谓iterations就是完成一次epoch所需的batch个数。

刚刚提到的,batch numbers就是iterations。

简单一句话说就是,我们有2000个数据,分成4个batch,那么batch size就是500。运行所有的数据进行训练,完成1个epoch,需要进行4次iterations。

参考资料

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