Abstract Over the last decade, significant efforts have been dedicated to designing efficient models for the challenge of ultra-high resolution (UHR) semantic segmentation. These models mainly follow the …

Aug 5, 2025 · Key takeaways: Image super-resolution is the task of producing a high-resolution image from a low-resolution input, and deep learning has transformed this field by training models that can …

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May 11, 2023 · Computer architecture is defined as the end-to-end structure of a computer system that determines how its components interact with each other in helping execute the machine’s purpose …

Oct 10, 2025 · Computer architecture defines how a computer’s components communicate through electronic signals to perform input, processing, and output operations. It covers the design and …

Nov 18, 2021 · Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restoration …

Sep 5, 2023 · Building extraction is an essential component of study in the science of remote sensing, and applications for building extraction heavily rely on semantic segmentation of high-resolution …

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Oct 17, 2023 · In this study, the authors developed a high-resolution crack segmentation framework (HRCSF) by tailoring a physical cascade architecture based on a multiscale crack feature extraction …

However, restricting the spatial extent of SA is contradic-tory to the goal of capturing the true long-range pixel rela-tionships, especially on high-resolution images. In this paper, we propose an efficient …