Sugarcane node feature recognition and positioning method based on convolutional neural network
A convolutional neural network and feature recognition technology, applied in the field of sugarcane node feature recognition and localization based on convolutional neural network, can solve the problems of low efficiency of sugarcane cutting, and achieve high recognition rate, fast response speed, fast and accurate The effect of recognition
Active Publication Date: 2019-09-27
GUANGXI UNIV FOR NATITIES +1
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[0004]
The purpose of the present invention is to provide a method for identifying and locating sugarcane node features based on convolutional neural network, so as to solve the technical problem of low efficiency of cutting sugarcane.
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[0041] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below with reference to the accompanying drawings and preferred embodiments. However, it should be noted that many of the details listed in the specification are only for readers to have a thorough understanding of one or more aspects of the present invention, and these aspects of the present invention can be implemented even without these specific details.
[0042] see figure 1 , the present invention provides a method for identifying and locating sugarcane node features based on a convolutional neural network, the method comprising the steps of:
[0043] Step 1: Set up the camera, sample the video of the sugarcane on the shooting device, the sugarcane is of different varieties and colors, convert the video into a picture, and set the size of the picture. Using sugarcane of different varieties and sugarcane of diffe...
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The invention discloses a sugarcane section feature recognition and positioning method based on a convolutional neural network. The invention discloses a sugarcane feature recognition method, belongs to the technical field of computer vision, and comprises the following steps: carrying out recognition processing on sugarcane image data through a deep convolutional neural network to obtain a sugarcane feature recognition positioning model, and inputting image data of the model to obtain sugarcane surface feature data so as to obtain real coordinate data of features. The method mainly comprises two parts, the first part is establishment and training of an identification positioning system model, and the second part is identification positioning and transmits data to subsequent equipment. The method has the advantages of being high in recognition rate, high in response speed and the like, sugarcane node information can be updated in real time by combining the recognized algorithm, the recognition rate can reach 90% or above, the recognition time is about 50 milliseconds, and therefore sugarcane seed cutting machine intelligentization is achieved, and the production efficiency is greatly improved.
Description
technical field [0001] The invention relates to the technical field of computer vision, in particular to a method for identifying and locating sugarcane node features based on a convolutional neural network. Background technique [0002] The development of the sugar industry is one of the important guarantees for China's grain and food safety, among which sucrose accounts for more than 90% of sugar consumption. Guangxi is the largest sugar cane production base in my country, accounting for more than 60% of the country's sugar cane area and output. In recent years, affected by various factors such as slow advancement of mechanization and low degree of intelligence, sugarcane production efficiency has been low and market competitiveness has declined, which has had a serious impact on the safety of my country's sugar industry. In the past, the production method of artificially identifying and cutting sugarcane can not meet the needs of the times and the needs of social develop...
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IPC IPC(8): G06K9/62G06T7/00
CPCG06T7/0012G06T2207/10004G06T2207/10024G06T2207/20081G06T2207/20084G06T2207/30004G06F18/23213G06F18/241Y02P90/30
Inventor 李尚平李向辉文春明廖义奎李凯华袁泓磊张可张伟黄宗晓向锐
Owner GUANGXI UNIV FOR NATITIES