EdgeGAT, combining EdgeConv and graph attention with PCA features, reports mIoU of 93.20% on the Pheno4D maize dataset and 73.35% on the Ao dataset for leaf, stem, and soil segmentation.
Mahlein, Plant disease detection by imaging sensors – parallels and specific demands for precision agriculture and plant phenotyping, Plant Disease 100 (2) (2016) 241–251
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Graph-Based Deep Learning for Component Segmentation of Maize Plants
EdgeGAT, combining EdgeConv and graph attention with PCA features, reports mIoU of 93.20% on the Pheno4D maize dataset and 73.35% on the Ao dataset for leaf, stem, and soil segmentation.