HIGHLIGHTS
- who: Xinfa Wang et al. from the School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, China Faculty of Engineering and Technology, Sumy National Agrarian University, Sumy, Ukraine have published the research: Lightweight SM-YOLOv5 Tomato Fruit Detection Algorithm for Plant Factory, in the Journal: Sensors 2023, 23, 3336. of /2023/
- what: The authors propose an improved Small MobileNet YOLOv5 (SM-YOLOv5) detection algorithm and model based on YOLOv5 for target detection by tomato-picking robots in plant factories. The experiment showed that the improved SM-YOLOv5 model had a precision of 97 . . .
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