Method for evaluating severity of plant leaf diseases and insect pests based on deep learning
A technology of plant leaves and severity, which is applied in the field of image recognition, can solve the problems of lack of severity of plant diseases and insect pests, and achieve the effect of improving accuracy and good adaptability
Active Publication Date: 2022-03-25
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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[0004]
Aiming at the above-mentioned deficiencies in the prior art, a method for assessing the severity of plant leaf diseases and insect pests based on deep learning provided by the present invention solves the problem of lacking a method for assessing the severity of plant diseases and insect pests
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[0049] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.
[0050] Such as figure 1 As shown, a method for evaluating the severity of plant leaf diseases and insect pests based on deep learning includes the following steps:
[0051] S1. Collect plant leaf images to obtain a plant leaf data set;
[0052] Images of plant leaves were collected by a digital camera. The distance between the digital camera and the plant leaves is 30cm, so that the photographed plant leaves can be comple...
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The invention discloses a method for evaluating severity of plant leaf diseases and insect pests based on deep learning. The method comprises the following steps: S1, collecting a plant leaf image; s2, performing data expansion processing on the plant leaf data set; s3, marking images in the expanded plant leaf data set and the disease and insect pest leaf image set; s4, training two image segmentation models by adopting the annotated extended plant leaf data set and the annotated pest leaf image set; s5, segmenting a to-be-evaluated plant leaf image by using the first image segmentation model to obtain a leaf semantic segmentation map; s6, performing background 0 filling on the leaf semantic segmentation map; s7, segmenting the leaf image data by using a second image segmentation model to obtain leaf images divided into different regions; s8, calculating a disease and insect pest area proportion to obtain the severity of plant leaf diseases and insect pests; the method solves the problem that a method for evaluating the severity of plant diseases and pests does not exist in the prior art.
Description
technical field [0001] The invention relates to the field of image recognition, in particular to a method for evaluating the severity of plant leaf diseases and insect pests based on deep learning. Background technique [0002] Plant diseases are the main cause of plant destruction. Accurate detection of plant diseases can help early treatment strategies and fundamentally prevent the spread of diseases, which is of great significance in reducing economic losses caused by diseases. With the development and application of computer technology, computer vision and image processing are widely used in agricultural species classification and leaf disease identification. Although these techniques are effective in the detection and diagnosis of plant leaf diseases and insect pests, they cannot be used for the assessment of the severity of plant leaf diseases and insect pests. [0003] The prior art methods mark the data sets in the form of "plant category-disease and insect pest ty...
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IPC IPC(8): G06V20/20G06V10/26G06V10/28G06N3/04G06N3/08
CPCG06N3/08G06N3/045
Inventor 兰荻刘勇国朱嘉静张云李巧勤陆鑫傅翀杨尚明
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA