Weed Detection in Images of Carrot Fields Based on Improved YOLO v4

The accurate weed detection is the premise for precision prevention and control of weeds in fields. Machine vision offers an effective means to detect accurately. For various carrot fields, this paper improves You Only Look Once v4 (YOLO v4) into a lightweight model called YOLO v4-weeds among seedlings. Specifically, backbone network original YOLOv4 was replaced with MobileNetV3-Small. Combined depth-wise separable convolution inverted residual structure, attention mechanism introduced reduce memory required process images, making more efficient. research results provide reference detection, robot weeding, selective spraying.