Automatic registration of high-resolution remote sensing images (HRRSIs) has always been a severe challenge due to the local deformation caused by different shooting angles and illumination conditions. A new method of characteristic spatial objects (CSOs) extraction and matching is proposed to deal with this difficulty. Firstly, the Mask R-CNN model is utilized to extract the CSOs and their positioning points on the images automatically.
View Article and Find Full Text PDFDeveloping efficient separation materials for surfactant-stabilized oil/water emulsions is of great importance while significantly challenging. In this work, a sand filter with Janus channels was prepared by simply mixing superhydrophilic and superhydrophobic quartz sand in a mass ratio of 1:1. Due to the imbalanced force of droplets in those Janus channels, better separation performance under gravity was achieved for both surfactant-stabilized oil-in-water and water-in-oil emulsions than the superhydrophilic or superhydrophobic sand filter alone.
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