RMT and a range of DLC models were applied to the video data with tapping frequencies up to 8Hz to extract movement features.
Convolutional neural network (CNN) models have seen advanced improvements in performance in various domains, but lack of interpretability is a major barrier to assurance and regulation during operation for acceptance and deployment of AI-assisted applications.
Deep supervision, or known as 'intermediate supervision' or 'auxiliary supervision', is to add supervision at hidden layers of a neural network.
In this work, we propose the first-ever Transformer model (POViT) to efficiently design and simulate semiconductor photonic devices with multiple objectives.
Keypoint detection plays an important role in a wide range of applications.
With populations ageing, the number of people with dementia worldwide is expected to triple to 152 million by 2050.
Interestingly, the principal component analysis exactly provides an effective way to define such a frame, i. e. setting the principal components as the frame axes.