artificial intelligence; deep learning; remote sensing; semantic segmentation; flood

This dataset contains image masks from KiTTy obtained by running SAM. In the future, it is planned to add other masks from OpenSEED, SEEM, SAM (new version).

The study is carried out in order to study segmentation on point clouds

This dataset contains image masks from KiTTy obtained by running SAM. In the future, it is planned to add other masks from OpenSEED, SEEM, SAM (new version).

The study is carried out in order to study segmentation on point clouds

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India is a sub-continent that stretches from Ladakh in

the North to Kanyakumari in the South and from

Gujrat in the West to Arunachal Pradesh, Nagaland

and Manipur in the East. India is currently the

seventh largest country by land covering an area of

approximately 32,87,263 kms.

 

India's Space Strengths:

India is the fourth country in the world to have

destroyed a satellite of its own. India built the

record-breaking space capability of launching 104

satellites on a single Polar Satellite Launch Vehicle

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Accurate flood delineation is crucial in many disaster management tasks, including, but not limited to: risk map production and update, impact estimation, claim verification, or planning of countermeasures for disaster risk reduction. Open remote sensing resources such as the data provided by the Copernicus ecosystem enable to carry out this activity, which benefits from frequent revisit times on a global scale. In the last decades, satellite imagery has been successfully applied to flood delineation problems, especially considering Synthetic Aperture Radar (SAR) signals.

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