English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Cloud-based overlays are often present in optical remote sensing images, thuslimiting the application of acquired data. Removing clouds is an indispensablepre-processing step in remote sensing image analysis. Deep learning hasachieved great success in the field of remote sensing in recent years,including scene classification and change detection. However, deep learning israrely applied in remote sensing image removal clouds. The reason is the lackof data sets for training neural networks. In order to solve this problem, thispaper first proposed the Remote sensing Image Cloud rEmoving dataset (RICE).The proposed dataset consists of two parts: RICE1 contains 500 pairs of images,each pair has images with cloud and cloudless size of 512*512; RICE2 contains450 sets of images, each set contains three 512*512 size images. ,respectively, the reference picture without clouds, the picture of the cloudand the mask of its cloud. The dataset is freely available at\url{https://github.com/BUPTLdy/RICE_DATASET}.

A Remote Sensing Image Dataset for Cloud Removal