Abstract: In precision agriculture, the wheat head detection is very critical as it supports crop yield evaluation, resource optimization, and conservation efforts. Head detection of wheat adopts an amalgamation of simple machine learning models and traditional image processing methods in the most of their works. While these methods are easy to apply in real situations, they have higher drawbacks in terms of efficiency and accuracy when integrated into sophisticated datasets. This highlights the need for innovative solutions capable of overcoming these challenges........
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