To ensure good performance, modern machine learning models typically require large
amounts of quality annotated data. Meanwhile, the data collection and annotation processes …

Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is
based on the social value of Generation Z that online and offline selves are not different …

Deep learning algorithms have exhibited impressive performance across various computer
vision tasks; however, the challenge of overfitting persists, especially when dealing with …

Deep learning has achieved remarkable results in many computer vision tasks. Deep neural
networks typically rely on large amounts of training data to avoid overfitting. However …

To solve object detection issues in infrared images, such as a low recognition rate and a
high false alarm rate caused by long distances, weak energy, and low resolution, we …

Mixup-based augmentation has been found to be effective for generalizing models during
training, especially for Vision Transformers (ViTs) since they can easily overfit. However …

Foreign objects in coal seriously affect the efficiency and safety of clean coal production.
Currently, the removal of foreign objects in coal preparation plant mainly depends on …

Data augmentation is key to improving the generalization ability of deep learning models.
Mixup is a simple and widely-used data augmentation technique that has proven effective in …

Neural networks are prone to overfitting and memorizing data patterns. To avoid over-fitting
and enhance their generalization and performance, various methods have been suggested …

The identification of corn leaf diseases in a real field environment faces several difficulties,
such as complex background disturbances, variations and irregularities in the lesion areas …