December 5, 2025Scientific ReportsOpen Access

Deep learning approach for crop-weed segmentation in peanut cultivation using PSPEdgeWeedNet

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Authors

DPDeepthi G. Pai MBMamatha Balachandra RKRadhika Kamath

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Implication

Novel architecture improves weed detection in peanut cultivation using convolutional neural networks, suggesting enhanced precision agriculture practices.

Key Points

Precision agriculture benefits from improved weed management using convolutional neural networks.
PSPEdgeWeedNet enhances crop-weed segmentation significantly over established methods.
Experimental evaluation utilized a curated peanut field dataset for accurate model training.
Edge-aware mechanisms represent a critical advancement in automated weed detection systems.

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Pai et al. (2025) studied this question.

synapsesocial.com/papers/693231308e51979591dce97c https://doi.org/10.1038/s41598-025-24174-6

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Implication

Novel architecture improves weed detection in peanut cultivation using convolutional neural networks, suggesting enhanced precision agriculture practices.

Deep learning approach for crop-weed segmentation in peanut cultivation using PSPEdgeWeedNet

Discussion

Member takes

Implication

Key Points

Cite This Study

Deep learning approach for crop-weed segmentation in peanut cultivation using PSPEdgeWeedNet

Discussion

Member takes

Implication

Key Points

Cite This Study

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Also Consider