Analysis of Construction Orchard Trunk Shrub Dataset and Target Detection

Intelligence is the inevitable demand of agricultural modernization, and the target detection system has a broad application prospect. The deep learning perception algorithm requires a large number of datasets for training, and it is the prerequisite and foundation constructing an orchard environment to accurately identify shrubs and tree trunks datasets. A large amount of image is collected, the dataset is labeled to train the model, and the data is also analyzed using confidence, accuracy, recall and other indicators to ensure the reliability and accuracy. The intelligent algorithm based on YOLOv8 handles the complex orchard scene in real time, accurately identifies shrubs and tree trunks, and automatically adjusts the paths to avoid collision. The results show that the algorithm has good target detection and recognition ability, and its deployment can improve the efficiency of orchard management and reduce labor costs, which provides a strong support for the realization of agricultural automation.