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您好,虽然训练集的准确度看起来很高,但是发现体验并不是很好,像7和9,我的写法基本就没法被正确识别,请问如何进一步提高准确度???
The text was updated successfully, but these errors were encountered:
可以使用更多训练数据和/或更大的网络。 MNIST 中一些数字的写法可能和实际使用者的写法有一些差异:
比如 4 这个数字,MNIST 中的写法为: 而我通常会写为: 导致我写 4 的识别率很低。
解决这一问题的一个方法,是从实际使用者那里收集更多数据用于训练,让训练数据和测试数据来自相同的分布,使模型能够反映实际使用者的书写习惯。
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但是这个工作自己做 emmm 好像有点难 样本量小准确度低 样本量大就很花时间 但是不这么做好像也没其他办法了 ,TFlite 不能训练,可能更好的办法就是模仿mnist的写法 orz
也可以考虑使用 Artificial Data Synthesis 或 Data Augmentation 等方法来生成更多的数据。
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您好,虽然训练集的准确度看起来很高,但是发现体验并不是很好,像7和9,我的写法基本就没法被正确识别,请问如何进一步提高准确度???
The text was updated successfully, but these errors were encountered: