The recent hype about artificial intelligence has sparked renewed interest in applying the
successful deep learning (DL) methods for image recognition, speech recognition, robotics …

Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …

Deep network architectures struggle to continually learn new tasks without forgetting the
previous tasks. A recent trend indicates that dynamic architectures based on an expansion …

We present in this paper a new architecture, named Convolutional vision Transformer (CvT),
that improves Vision Transformer (ViT) in performance and efficiency by introducing …

This paper presents a new vision Transformer, called Swin Transformer, that capably serves
as a general-purpose backbone for computer vision. Challenges in adapting Transformer …

Masked image modeling (MIM) as pre-training is shown to be effective for numerous vision
downstream tasks, but how and where MIM works remain unclear. In this paper, we compare …

Plants contribute significantly to the global food supply. Various Plant diseases can result in
production losses, which can be avoided by maintaining vigilance. However, manually …

Plants are a major source of food for the world population. Plant diseases contribute to
production loss, which can be tackled with continuous monitoring. Manual plant disease …

In the past decade, advances in deep learning have resulted in breakthroughs in a variety of
areas, including computer vision, natural language understanding, speech recognition, and …

Understanding the world in 3D is a critical component of urban autonomous driving.
Generally, the combination of expensive LiDAR sensors and stereo RGB imaging has been …