Abstract: This paper proposes a self-supervised framework based on a contrastive auto-encoding and convolutional information exchange for multi-modal medical fusion tasks. It is well known that ...

ABSTRACT: Anomaly detection in complex crowd scenes is a challenging task due to the inherent variability in crowd behaviors, interactions, and scales. This paper proposes a novel hybrid model that ...

Scanning Transmission Electron Microscopy (STEM) is a well-established method for looking into the physical properties of complex nanostructures. However, one major drawback is that acquiring very ...

Multiple studies have attempted to use a single type of data to predict various stages of Alzheimer’s disease (AD). However, combining multiple data modalities can improve prediction accuracy. In this ...

To address the difficulties in fusing multi-mode sensor data for complex industrial machinery, an adaptive deep coupling convolutional auto-encoder (ADCCAE) fusion method was proposed. First, the ...

arXiv provides the world with access to the newest scientific developments. Open Access has a myriad of benefits, in particular, it allows science to be more efficient. Remember to think about the ...