Research on DETR-based Weed Detection Algorithm
DOI:
https://doi.org/10.54097/7n2ye068Keywords:
Transformer, CBAM, Focal Point Loss, Weed DetectionAbstract
To address the problem of complex field conditions and high similarity between corn seedlings and weeds, this study proposes an improved DETR (Detection Transformer) model for weed detection in corn fields, which uses the CBAM convolutional attention mechanism in the DETR model, and uses a focal loss function instead of the traditional cross-entropy loss function to balance the number of positive and negative class samples of the data. Compared with the original model, the mAP (Mean Average precision) of the improved model was increased by 1.12% to 91.56%.
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