Abstract: Synthetic aperture radar (SAR) imaging provides a distinct advantage in scene understanding due to its capability for all-weather data acquisition. However, in comparison to easily annotated ...

Abstract: Satellite communication offers the prospect of service continuity over uncovered and under-covered areas, service ubiquity, and service scalability. However, several challenges must first be ...

Book Abstract: "In a world of huge, interconnected networks that can be completely blacked out by disturbances, POWER SYSTEM PROTECTION offers you an improved understanding of the requirements ...

Abstract: The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology ...

Abstract: The penetration of distributed energy resources in electrical grids has been steadily increasing in an effort to reduce greenhouse gas emissions. Inverters, as interfaces between distributed ...

Book Abstract: In 1971 Dr. Paul C. Lauterbur pioneered spatial information encoding principles that made image formation possible by using magnetic resonance signals. Now Lauterbur, "father of the MRI ...

Abstract: Although the problem of determining the minimum cost path through a graph arises naturally in a number of interesting applications, there has been no underlying theory to guide the ...

Abstract: The transportation department relies on accurate traffic forecasting for effective decision-making. However, determining relevant parameters for existing traffic flow prediction models poses ...

Abstract: The goal of Optimal Transport (OT) is to define geometric tools that are useful to compare probability distributions. Their use dates back to 1781. Recent years have witnessed a new ...

Abstract: Existing object-level SLAM methods often overlook the correspondence between semantic information and geometric features, resulting in a significant gap between them within SLAM frameworks.

Abstract: Medical image segmentation has made significant strides with the development of basic models. Specifically, models that combine CNNs with transformers can successfully extract both local and ...

Abstract: Existing unsupervised salient object detection (USOD) methods usually rely on low-level saliency priors, such as center and background priors, to detect salient objects, resulting in ...