Earth observation relies on diverse imaging systems whose varying spatial, spectral, radiometric, and temporal ...

This repository contains the code base and examples for Building Aggregates with a Neighborhood Kernel and Spatial Yardstick developed for: BANKSY: A Spatial Clustering Algorithm that Unifes Cell ...

Abstract: In this paper, an approximate Schur decomposition-based spatial domain blind color image watermarking method is proposed to protect the copyright of color images, which has low computation ...

Identifying spatial domains is the first important step in spatial transcriptomics (ST). Histological information can provide insights beyond gene expression profiles. To make the most of this ...

Convolutional Neural Network (CNN) is widely used in seismic data denoising due to its simplicity and effectiveness. However, traditional seismic denoising methods based on CNN ignore multi-scale ...

Abstract: Defect detection is a crucial but challenging task in thin film transistor liquid crystal display (TFT-LCD) manufacturing. Existing vision-based methods focus on either spatial domain or ...

It is practically impossible and unnecessary to obtain spatial-temporal information of any given continuous phenomenon at every point within a given geographic area. The most practical approach has ...