augmentation of pretrained network reducing accuracy

3 次查看（过去 30 天）
new_user
new_user 2021-12-29
回答： Chunru 2021-12-30
Hi, image augmentation using pretrained network is reducing accuracy of network. The file 1060.png is with dataaugmentation which reducces the accuracy as compared to 1061.png which has better accuracy without dataaugmentation.
what can be the reason, I read that augmentation increases accuracy.

请先登录，再回答此问题。

采纳的回答

Chunru
Chunru 2021-12-30
Generally speaking, training with data augmentation will lead to poorer traing accuracy, since the model needs to fit more training data. Data augmentation acts as a regularize and helps reduce overfitting. Therefore, it generally produce better generalization result. If you have different test/validation dataset, it usually improve the test/validation accuracy instead of training accuracy (as you have shown in the attached figure). Try to include some test/validation data in your training to see if the test/validation accuracy improves with data augumentation.

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Deep Learning Toolbox 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by