Transfer learning-based automatic tomato disease and insect pest detection method

Abstract

The invention discloses a transfer learning-based automatic tomato disease and insect pest detection method, and belongs to the technical field of images. The method comprises the following steps of: collecting tomato disease and insect pest leaf surface picture training samples, carrying out data enhancement on a picture of each tomato disease and insect pest leaf surface picture training sample, and inputting the data enhanced pictures into a deep learning network in a classification manner; and learning the tomato disease and insect pest leaf surface picture training samples, setting a learning frequency upper limit and a recognition precision threshold value, and when a learning frequency achieves the learning frequency upper limit or a recognition precision achieves the recognition precision threshold value, outputting a connection weight model among layers of a current convolutional neural network to serve as a tomato disease and insect pest leaf surface picture recognition classifier.

Description

technical field [0001] The invention relates to an automatic detection method for tomato diseases and insect pests based on transfer learning, which belongs to the field of image technology. Background technique [0002] The detection of tomato diseases and insect pests is different from other foreign object detection. The pictures of different tomato diseases and insect pests have certain differences, but their similarity will be greater, which makes it very difficult to extract the features of tomato diseases and insect pests. A suitable feature for detection training. The convolutional neural network can solve this problem very well. For the two-dimensional input image of the leaf table of tomato diseases and insect pests, it does not need artificially specific pre-selected features, but directly trains and learns the original image features, and learns independently during the training. New features, and feature learning is constantly updated. [0003] The convolutiona...

AI Technical Summary

Problems solved by technology

[0002] The detection of tomato diseases and insect pests is different from other foreign object detection. The pictures of different tomato diseases and insect pests have certain differences, but their similarity will be greater, which makes it very difficult to extract the features of tomato diseases and insect pests. A suitable feature for detection training

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