Weed–Crop Segmentation in Drone Images with a Novel Encoder–Decoder Framework Enhanced via Attention Modules

The rapid expansion of the world’s population has resulted in an increased demand for agricultural products which necessitates the need to improve crop yields. To enhance crop yields, it is imperative to control weeds. Traditionally, weed control predominantly relied on the use of herbicides; howeve...

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Vydané v:	Remote sensing (Basel, Switzerland) Ročník 15; číslo 23; s. 5615
Hlavní autori:	Khan, Sultan Daud, Basalamah, Saleh, Lbath, Ahmed
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.12.2023
Predmet:	Agricultural production Agricultural products Coders color Comparative analysis Computer vision Corn Crop yield Crops data collection Datasets Deep learning Drone aircraft Health hazards Herbicides Identification and classification Image enhancement Image processing Image segmentation Localization Machine learning Machine vision Methods Modules Neural networks Occlusion Population remote sensing semantic segmentation Semantics smart agriculture Spatial data Support vector machines texture Unmanned vehicles Weed control Weeds Pakistan
ISSN:	2072-4292, 2072-4292
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