Cotton crop classification using satellite images with score level fusion based hybrid model

• Published in: Pattern analysis and applications : PAA Vol. 27; no. 2
• Main Authors: Kaur, Amandeep, Singla, Geetanjali, Singh, Manjinder, Mittal, Amit, Mittal, Ruchi, Malik, Varun
• Format: Journal Article
• Language: English
• Published: London Springer London 01.06.2024; Springer Nature B.V
• Subjects: Accuracy; Algorithms; Chlorophyll; Classification; Computer Science; Cotton; Feature extraction; Image classification; Image quality; Image segmentation; Land management; Leaf area index; Optimization models; Pattern Recognition; Preprocessing; Remote sensing; Satellite imagery; Theoretical Advances; Vegetation index; Green chlorophyll index; Cotton crop classification; Hybrid optimization; Vegetation indices; Modified deep joint segmentation

Accurate cotton images are significant component for surveiling cotton development and its precise control. A suitable technique for charting the distribution of cotton at the county or field level must be available to researchers and production managers. The classification of cotton remote sensing...