[null,null,["上次更新時間：2025-01-18 (世界標準時間)。"],[[["Overfitting in convolutional neural networks can be mitigated by using techniques like data augmentation and dropout regularization."],["Data augmentation involves creating variations of existing training images to increase dataset diversity and size, which is particularly helpful for smaller datasets."],["Dropout regularization randomly removes units during training to prevent the model from becoming overly specialized to the training data."],["When dealing with large datasets, the need for dropout regularization diminishes and the impact of data augmentation is reduced."]]],[]]
圖 7. 針對單一狗狗圖片進行資料增強 (摘錄自 Kaggle 提供的「Dogs vs. Cats」資料集)。左側：訓練集的原始狗狗圖片。右圖：使用隨機轉換功能，從原始圖片產生九張新圖片。