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March 3, 2026
Segmentation and germination prediction with crossover-boosted sunflower optimization for precision agriculture
AM
Asan Nainar Mohamed Mustafa
SA
Samydurai Arumugam
SV
S. Venkatesh
Key Points
Segmentation and germination prediction improved by 35%, enhancing crop yield potential and automation.
Crossover-boosted sunflower optimization algorithm significantly outperformed traditional methods in tests.
Analysis utilized real-time imaging and predictive algorithms on crop data for effective yield assessment.
Improved precision agriculture techniques highlight the importance of advanced computational methods, supporting scalability in farming.
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Segmentation and germination prediction with crossover-boosted sunflower optimization for precision agriculture | Synapse
Cite This Study
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Mustafa et al. (Tue,) studied this question.
synapsesocial.com/papers/69a761c6c6e9836116a2fd6e
https://doi.org/https://doi.org/10.1007/s12530-026-09792-3