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We use the VegAnn dataset, which is a binary segmentation dataset designed to differentiate vegetation, including both healthy and senescent plant parts, from background elements such as soil and crop residues. It comprises 3,775 high-resolution RGB images collected from diverse regions using various acquisition systems and platforms. The dataset encompasses 9 crop types, spanning different growth stages, climatic conditions, and soil types, and includes data from multiple countries such as France, China, Japan, Belgium, Australia, and others. The dataset is partitioned into 3,020 training images and 755 test images.
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