Abstract: Hyperspectral image (HSI) classification is crucial in the remote sensing (RS) community. In recent years, Transformers have been popular in this field due to their global information ...

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 ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6731005 ...

Book Abstract: This advanced text and reference covers the design and implementation of integrated circuits for analog-to-digital and digital-to-analog conversion. It begins with basic concepts and ...

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 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: We consider the problem of partitioning the nodes of a graph with costs on its edges into subsets of given sizes so as to minimize the sum of the costs on all edges cut. This problem arises ...

Abstract: Real-time image dehazmg is crucial for applications such as autonomous driving, surveillance, and remote sensing, where haze can significantly reduce visibility. However, many deep learning ...

This book presents an original generalized transmission line approach associated with non-resonant structures that exhibit larger bandwidths, lower loss, and higher design flexibility. It is based on ...

Abstract: The complexity of data and limited model generalization significantly hinder prediction accuracy. A physics-informed long short-term memory model with adaptive weight assignment (PILSTM-AWA) ...

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 ...