LAUSR

Image recognition tools for weed identification, such as smartphone applications, have the potential to enhance user knowledge, provide early invasive weed alerts, and enable site‐specific weed management. Although numerous studies have reported product development and model accuracy, few have evaluated these tools in practical environments beyond developmental settings. In this study, we developed a weed detector using the You Only Look Once (YOLO) v3 object detection algorithm to identify six noxious weed species. Specifically, we examined the effects of: (i) image collection locations, (ii) target backgrounds, and (iii) camera devices on detection accuracy, assessing applicability through field verification at 68 sites across Japan and controlled garden experiments.