Objective An artificial intelligence-based identification method to effectively differentiate bok choy seedlings from weeds was proposed to facilitate vegetable farm weeding operation.
Methods Bok choy seedlings were recognized by the neural network models to exclude the green pixels from other vegetations considered as weeds by color differentiation. Effectiveness of the convolutional neural networks (CNN) and the emerging transformer models in correctly separating the seedlings and weeds was evaluated.
Result Although both performed acceptable, the YOLOX model delivered a higher average accuracy of 98.1% and a faster speed at 44.8 fps than Deformable DETR in the recognition operation.
Conclusion By defining the green pixels of bok choy seedlings as target color, weeds could be rejected by the AI recognition program providing a robust separation for efficient weeding in the field of the random-planting vegetables such as bok choy.
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