deep-learning - YOLO 会受到未标记图像的负面影响吗？
问题描述
我有两个与交通相关的数据集。一个包含交通标志和其他交通信号灯。我想合并这两个数据集并训练模型来检测它们。
红绿灯数据集中未标记的交通标志是否会影响训练过程，反之亦然？
从我目前所读到的内容中，YOLO 还学习了有关对象的上下文信息，这就是为什么要关注的原因。
解决方案
As you mentioned and as I found there, "YOLO sees the entire image during training and test time so it implicitly encodes contextual information about classes as well as their appearance", but I see that the meaning is that it considers the direct areas around the labels to add their information to the trained network, thus, you will likely only lose the information from the unlabeled items, but it will not impact the labeled items negatively.