Product image classification method and system based on deep learning
A deep learning and classification method technology, applied in the field of image processing, can solve the problems of low work efficiency of the image classification system, achieve the effects of avoiding manual classification problems, improving engineering efficiency, and saving memory
Pending Publication Date: 2022-07-05
武汉思尔朋科技有限公司
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[0003] A product image classification method and system based on deep learning proposed by the present invention solves the problem of low working efficiency of the image classification system in the prior art
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[0033] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.
[0034] refer to Figure 1-2 , a deep learning-based product image classification method, including the following steps:
[0035] Step 1. Establish detailed classification standards according to customer standards;
[0036] Step 2: Establish a neural network model according to the formulated classification standard, and then conduct a large amount of data training, and finally form a graphical analysis model;
[0037] Step 3: Import pictures, the graphic analysis model can identify the imported picture features, and then classify them into a class of pictures;
[0038] Among them, if a single image is imported, the file type will be displ...
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The invention relates to the technical field of image processing, in particular to a product image classification method and system based on deep learning, and aims to solve the problem that an image classification system in the prior art is low in working efficiency, the following scheme is proposed, and the method comprises the following steps: step 1, establishing a detailed classification standard according to a customer standard; 2, establishing a neural network model according to the formulated classification standard, then carrying out a large amount of data training, and finally forming a graphic analysis model; and step 3, importing the pictures, performing feature recognition on the imported pictures by the graphic analysis model, and classifying the pictures into one type of pictures. According to the method, the neural network model is established, then a large amount of data is used for training the model, feature recognition can be carried out on the imported pictures, then the pictures are classified into one type of pictures, and therefore the product picture classification efficiency is greatly improved.
Description
technical field [0001] The invention relates to the field of image processing, in particular to a deep learning-based product image classification method and system. Background technique [0002] Image classification of nonwoven products is a new scene in the field of computer vision, and may become a popular direction of current image research in the future. Deep learning methods have been widely used in image retrieval, image classification, text recognition, video classification and other fields. The most important fields of artificial intelligence are computer vision and image recognition. With the advent of the era of artificial intelligence, people's demand for image processing has grown exponentially, and image recognition technology has also developed rapidly. However, with the innovation of special production requirements or processes, a kind of thorny and common problem has emerged. For example, various types of products formed naturally are mixed together and nee...
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IPC IPC(8): G06V10/764G06V30/14G06V30/19G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06N3/045G06F18/2411
Inventor 郑志力陈馨
Owner 武汉思尔朋科技有限公司