14 datasets found

The CDD dataset contains 11 pairs of bi-temporal images obtained from Google Earth in different seasons with a spatial resolution ranging from 3 to 100 cm per pixel.

Change detection is a crucial but extremely challenging task in remote sensing image analysis, and much progress has been made with the rapid development of deep learning....

The DSIFN-CD dataset is a collection of high-resolution images with seasonal changes in different cities.

The proposed SMDNet model is used for change detection in high-resolution remote sensing images.

The CDD dataset is a collection of remote sensing images with seasonal changes and different lighting conditions.

The Sardinia dataset consists of bi-temporal SAR images, acquired by the RADARSAT at the area of Sardinia in September 1995 and July 1996, respectively.

The Yellow River dataset consists of bi-temporal SAR images, acquired by Radarsat-2 at the region of Yellow River Estuary in China in June 2008 and June 2009, respectively.

The Bern dataset consists of bi-temporal SAR images, acquired by the European Remote Sensing 2 satellite SAR sensor at the region of Bern, Switzerland, in April and May 1999,...

The Ottawa dataset consists of bi-temporal SAR images, acquired by the RADARSAT at the area of Ottawa in May 1997 and August 1997, respectively.

Change Detection (CD) is an important problem in remote sensing in which our goal is to identify relevant changes in bi-temporal remote sensing images that can help in various...

Remote-sensing (RS) Change Detection (CD) aims to de-tect “changes of interest” from co-registered bi-temporal images. The performance of existing deep supervised CD methods is...

DE-CD(3.3×) is a dataset for cross-resolution change detection.

SV-CD(8×) is a dataset for cross-resolution change detection.

LEVIR-CD(4×) is a dataset for cross-resolution change detection.