Tomato leaf insect pest region segmentation method based on improved Deeplabv3 + model

• Main Authors: FENG LIANGFENG, DU QILIANG, TIAN LIANFANG
• Format: Patent
• Language: Chinese; English
• Published: 14.07.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; PHYSICS

The invention discloses a tomato leaf pest region segmentation method based on an improved Deeplabv3 + model. The method comprises the following steps: constructing an original data set; performing data enhancement on the original data set, and constructing a training data set, a verification data set and a test data set; performing size conversion and data normalization processing on the training data set; training parameters are set for the improved Deeplabv3 + model, a training data set and a verification data set are used for training and verification, and an optimal model is stored; and performing size conversion and data normalization processing on a to-be-identified image in the test data set, and inputting the to-be-identified image into the stored model to complete accurate segmentation of the tomato leaf insect pest area. The invention provides a new method for treating tomato insect pests, and effectively protects the growth of tomatoes. 本发明公开了一种基于改进deeplabv3+模型的番茄叶片虫害区域分割方法，包括：构建原始数据集；对原始数据集进行数据增强