What is overfitting in computer vision models and why does it occur during training? How does overfitting affect the performance of deep learning models on new data? What are the common signs of overfitting in image classification and recognition tasks? What techniques can be used to reduce or prevent overfitting in computer vision models? How do methods like data augmentation, dropout, and regularization help improve model generalization?