Improved Agricultural Field Segmentation in Satellite Imagery Using TL-ResUNet Architecture

Improved Agricultural Field Segmentation in Satellite Imagery Using TL-ResUNet Architecture

Currently, there is a growing population around the world, and this is particularly true in developing countries, where food security is becoming a major problem. Therefore, agricultural land monitoring, land use classification and analysis, and achieving high yields through efficient land use are i...

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Bibliographic Details
Main Authors: Furkat Safarov, Kuchkorov Temurbek, Djumanov Jamoljon, Ochilov Temur, Jean Chamberlain Chedjou, Akmalbek Bobomirzaevich Abdusalomov, Young-Im Cho
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Sensors
Subjects:
image segmentation
agriculture
satellite imagery
deep learning
UNet architecture
transfer learning
Online Access:https://www.mdpi.com/1424-8220/22/24/9784

Internet

https://www.mdpi.com/1424-8220/22/24/9784

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