Abstract-Weed control in pasture is a challenging problem that can be expensive and environmentally unfriendly. This paper proposes a novel method for recognition of broad-leaf weeds in pasture such that precision weed control can be achieved with reduced herbicide use. Both conventional machine learning algorithms and deep learning methods have been explored and compared to achieve high detection accuracy and robustness in real-world environments. Inpasture grass/weed image data have been captured for classifier training and algorithm validation. The proposed deep learning method has achieved 96.88% accuracy and is capable of detecting weeds in different pastures under various representative outdoor lighting conditions.
Zhang et al. REF proposed a system for identifying broad-leaf weeds in the pasture.
Broad-Leaf Weed Detection in Pasture
2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)
2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)
Computer Science