Recyclable garbage image classification method and system based on artificial intelligence
A technology of artificial intelligence and classification methods, which is applied in the direction of instruments, biological neural network models, character and pattern recognition, etc., can solve the problems of privacy cloud computing distrust, cloud computing service prices, etc., to improve efficiency and garbage classification effect is good , The effect of improving the probability of correct garbage classification
Pending Publication Date: 2020-10-13
SHANGHAI JIAO TONG UNIV
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Problems solved by technology
The disadvantage is that the price of cloud computing services is high, and there are relatively strict requirements for the network conditions of the deployment environment. In addition, users who are sensitive to privacy will have distrust of cloud computing.
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[0060] Such as figure 1 , figure 2 As shown, according to the recyclable garbage image classification system based on the Jetson Nano development board provided by the present invention, intelligent detection and automatic classification can be performed, including the following steps:
[0061] Step S1, deploying the hardware environment, establishing the connection between the camera, the main body of the Jetson Nano development board and the external display device;
[0062] Step S2, initialize the system, wait for the user to deliver the garbage and sort it;
[0063] Step S3, the user triggers the system, and the camera starts to work;
[0064] Step S4, the camera takes 3 pictures, and transmits the pictures to the mainboard preprocessing module for processing;
[0065] Step S5, according to the preset sharpness discrimination standard, compare the sharpness of the three pictures in S4, and select the picture with the highest clearness;
[0066] Step S6, performing bac...
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The invention provides a recyclable garbage image classification method and system based on artificial intelligence, and the method comprises the steps: S1, deploying a hardware environment, and building the connection among a camera, a development board main body and external display equipment; S2, shooting pictures after detecting garbage by using the camera; S3, preprocessing the pictures, comparing the sharpness of the shot pictures according to a preset sharpness judgment standard, and screening out the picture with the highest sharpness; S4, carrying out background segmentation on the screened pictures, and cutting out objects contained in the pictures; S5, putting the separated object pictures into a convolutional neural network for picture classification, and outputting corresponding probability distribution; and S6, judging the probability distribution and taking corresponding measures. According to the invention, the garbage classification efficiency of a user is improved, sothat the probability of correct garbage classification is improved.
Description
technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to an artificial intelligence-based recyclable garbage image classification method and system. Background technique [0002] With the rapid development of society and the continuous improvement of people's living standards, the consumption ability of residents is also constantly improving. The most obvious thing is that the material products that can be obtained in daily life are constantly increasing. However, the great abundance of materials has brought about a sharp increase in the amount of waste generated by consumption. The intuitive manifestation is that in large and medium-sized cities, the amount of domestic waste has increased extremely rapidly. According to the report of the Ministry of Ecology and Environment of the People's Republic of China in 2019, in 2018, 200 large and medium-sized cities produced 211.473 million tons of domestic waste. Among...
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Login to View More IPC IPC(8): G06K9/00G06K9/34G06K9/40G06K9/62G06N3/04
CPCG06V20/10G06V10/267G06V10/30G06N3/045G06F18/2415
Inventor 孙锬锋赵泽宇蒋兴浩许可
Owner SHANGHAI JIAO TONG UNIV