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

In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

Road damage detection is an important task to ensure road safety and realize the timely
repair of road damage. The previous manual detection methods are low in efficiency and …

In this paper, we propose a remote-sensing scene-classification method based on vision
transformers. These types of networks, which are now recognized as state-of-the-art models …

Artificial intelligence (AI) and machine learning (ML) can improve manufacturing efficiency,
productivity, and sustainability. However, using AI in manufacturing also presents several …

A key requirement for the success of supervised deep learning is a large labeled dataset-a
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …

Deep learning (DL) techniques have obtained remarkable achievements on various tasks,
such as image recognition, object detection, and language modeling. However, building a …

Labeled medical imaging data is scarce and expensive to generate. To achieve
generalizable deep learning models large amounts of data are needed. Standard data …

The rice leaves related diseases often pose threats to the sustainable production of rice
affecting many farmers around the world. Early diagnosis and appropriate remedy of the rice …

Recent advances in deep learning for medical image segmentation demonstrate expert-
level accuracy. However, application of these models in clinically realistic environments can …