Understanding actions in videos remains a significant challenge in computer vision, which
has been the subject of several pieces of research in the last decades. Convolutional neural …

Background The development of fast, efficient, accurate, and reliable techniques and
methods for food authenticity identification is crucial for food quality assurance. Traditional …

We revisit large kernel design in modern convolutional neural networks (CNNs). Inspired by
recent advances in vision transformers (ViTs), in this paper, we demonstrate that using a few …

Recent studies show that transformer has strong capability of building long-range
dependencies, yet is incompetent in capturing high frequencies that predominantly convey …

MetaFormer, the abstracted architecture of Transformer, has been found to play a significant
role in achieving competitive performance. In this paper, we further explore the capacity of …

In this study, we propose a three-dimensional Medical image classifier using Multi-plane
and Multi-slice Transformer (M3T) network to classify Alzheimer's disease (AD) in 3D MRI …

There still remains an extreme performance gap between Vision Transformers (ViTs) and
Convolutional Neural Networks (CNNs) when training from scratch on small datasets, which …

Wearable systems that incorporate soft tactile sensors that transmit spatio-temporal touch
patterns may be useful in the development of biomedical robotics. Such systems have been …

Human vision possesses a special type of visual processing systems called peripheral
vision. Partitioning the entire visual field into multiple contour regions based on the distance …

Breast mass is one of the main clinical symptoms of breast cancer. Recently, many CNN-
based methods for breast mass segmentation have been proposed. However, these …