Traffic sign classification plays a vital role in autonomous vehicles for its powerful capability
in information representation. However, the low-quality data of traffic signs captured by in …

A multi-sensor medical-image fusion technique, which integrates useful information from
different single-modal images of the same tissue and provides a fused image that is more …

In this paper, a unified optimization model for medical image fusion based on tensor
decomposition and the non-subsampled shearlet transform (NSST) is proposed. The model …

Recently, a multimodal sentiment analysis of social media has attracted increasing attention,
and its core idea is to discovery heuristic fusion strategy to analyze the sentiment …

Face-based recognition methods usually need the image of the whole face to perform, but in
some situations, only a fraction of the face is visible, for example wearing sunglasses or …

Cyber-Manufacturing combines industrial big data with intelligent analysis to find and
understand the intangible problems in decision-making, which requires a systematic method …

In recent years, with the development of deep learning technology, deep neural networks
have been widely used in the field of medical image segmentation. U-shaped Network (U …

Medical image fusion plays an important role in the precise diagnosis, treatment planning,
and follow-up studies of various diseases. While tremendous improvements in medical …

Thick cloud removal for multitemporal remote sensing images (MTRSIs) is a necessary
preprocessing step for subsequent applications. Existing methods for cloud removal ignore …

Positron emission tomography (PET) and computed tomography (CT) scanner image
analysis plays an important role in clinical radiotherapy treatment. PET and CT images …