Straw mushroom growth state identification method based on convolutional neural network

Abstract

The invention discloses a volvariella volvacea growth state recognition method based on a convolutional neural network, and the method comprises the steps: 1) collecting images of volvariella volvacea planted in a greenhouse, carrying out the classification according to the growth state of the volvariella volvacea in the images, and constructing an original data set; 2) performing data enhancement on the original data set by using a data enhancement means according to the environment in the greenhouse and the growth characteristics of straw mushrooms, and constructing a training data set; 3) performing size conversion and data normalization processing on the training data set; 4) improving the ResNet model of the convolutional neural network; (5) training parameters are set for the improved ResNet model, a training data set is used for training, and an optimal model is stored; and 6) after carrying out size conversion and data normalization processing on a to-be-identified image, inputting the to-be-identified image into the stored model for forward reasoning, so that the model can deduce the overall growth state of the volvariella volvacea in the to-be-identified image, and completing identification of the growth state of the volvariella volvacea. According to the invention, high-precision straw mushroom growth state identification can be realized.

Description

technical field [0001] The invention relates to the technical field of pattern recognition and artificial intelligence, in particular to a method for recognizing the growth state of straw mushrooms based on a convolutional neural network. Background technique [0002] Straw mushroom is an edible fungus produced in hot summer. It is rich in nutrients. It is an edible fungus with a short cultivation period, high economic benefits and a very broad development prospect. Straw mushrooms have extremely strict requirements on the environment during the growth process, and are especially sensitive to the temperature, humidity, oxygen and carbon dioxide in the greenhouse mushroom room. Therefore, it is necessary to accurately identify the growth state of straw mushrooms during the cultivation process of straw mushrooms, and strictly control the greenhouse mushrooms. The temperature, humidity, oxygen and carbon dioxide in the room provide suitable environmental conditions in different...

AI Technical Summary

Problems solved by technology

The environment of the greenhouse mushroom house, such as temperature, humidity, oxygen concentration, and carbon dioxide concentration, can be precisely regulated through monitoring equipment and control equipment, but the identification of the growth status of straw mushrooms still remains at the stage of manual identification by growers. This kind of judgment method is not only inefficient, but also the accuracy rate of manual identification is not high, and it is difficult to meet the requirements of precise control of the straw mushroom planting industry

In recent years, with the development of smart agriculture, computer vision technology and artificial intelligence technology have gradually designed the agricultural field, and the straw mushroom planting industry can also introduce related technologies to solve the current problems of low efficiency and low accuracy in manually identifying the growth status of straw mushrooms

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