Multi-sensor systems are proliferating in the asset management industry. Industry 4.0, combined with the Internet of Things (IoT), has ushered in the requirements of prognostics and health management systems to predict the ...

This paper introduces and addresses the implementation of the Multi-Bernoulli Poisson (MBP) filter in multi-target tracking. A performance evaluation in a real scenario, in which a 3D lidar, automotive radar and a video ...

This paper presents a framework to evaluate the probability that a decision error event occurs in wireless sensor networks, including sensing and communication errors. We consider a scenario where sensors need to identify ...

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images ...

Multi-sensor fusion refers to methods used to combine information from multiple (in some cases, different) sensors with the aim of making one sensor compensate for the weaknesses of others or to improve the overall accuracy ...

Multi-sensor information fusion is a rapidly developing research area which forms the backbone of numerous essential technologies such as intelligent robotic control, sensor networks, video and image processing and many ...

Multi-modal depth estimation is one of the key challenges for endowing autonomous machines with robust robotic perception capabilities. There has been an outstan- ding advance in the development of uni-modal depth ...