Dense object detectors rely on the sliding-window paradigm that predicts the object over a
regular grid of image. Meanwhile, the feature maps on the point of the grid are adopted to …

Deep learning (DL) has gained popularity in network intrusion detection, due to its strong
capability of recognizing subtle differences between normal and malicious network activities. …

Protection on end users’ data stored in Cloud servers becomes an important issue in today’s
Cloud environments. In this paper, we present a novel data protection method combining …

Data fusion in Vehicle-to-Everything (V2X) networks for different data types coming from
different sources is the foundation for decision making in the smart vehicle driving systems. …

Many infections and stress signals can rapidly activate the NLRP3 inflammasome to elicit
robust inflammatory responses. This activation requires a priming step, which is thought to be …

Background Depression is a heterogeneous disorder, with the exact neuronal mechanisms
causing the disease yet to be discovered. Recent work suggests it is accompanied by neuro-…

Monocular 3D object detection has long been a challenging task in autonomous driving. Most
existing methods follow conventional 2D detectors to first localize object centers, and then …

With the development of modern Intelligent Transportation System (ITS), reliable and efficient
transportation information sharing becomes more and more important. Although there are …

Public resources and services (eg, datasets, training platforms, pre-trained models) have been
widely adopted to ease the development of Deep Learning-based applications. However, …

The presence of DNA in the cytoplasm is normally a sign of microbial infections and is quickly
detected by cyclic GMP-AMP synthase (cGAS) to elicit anti-infection immune responses. …