Semantic segmentation of remote sensing images is pivotal for comprehensive Earth observation, but the demand for interpreting new object categories, coupled with the high expense of manual annotation ...
Introduction: Quantifying adiposity, a key biomarker of metabolic health, typically requires imaging that involves radiation, high costs, and manual effort. We developed an AI framework to segment ...
ABSTRACT: Spatial transcriptomics is undergoing rapid advancements and iterations. It is a beneficial tool to significantly enhance our understanding of tissue organization and relationships between ...
URL: Access Paper Abstract: Semantic communication (SC) has emerged as an effective paradigm for reducing the bandwidth needs of wireless services by exploiting the so-called "semantics" or meaning ...
Underwater images segmentation is essential for tasks such as underwater exploration, marine environmental monitoring, and resource development. Nevertheless, given the complexity and variability of ...
Purpose: White matter hyperintensities (WMH), also known as leukoaraiosis (LA), are common brain abnormalities in elderly individuals. Evaluating LA on CT is challenging due to the less ...
ABSTRACT: The rise of social media platforms has revolutionized communication, enabling the exchange of vast amounts of data through text, audio, images, and videos. These platforms have become ...
Abstract: This paper addresses the semantic segmentation of synthetic aperture radar (SAR) images through the combination of ful-ly convolutional networks (FCN s), hierarchical probabilistic graphical ...
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