Image classification method, training method, classification prediction method and related device

Abstract

The invention discloses an image classification method. The method comprises the steps of preprocessing a standard TWSVM algorithm to obtain a preprocessed TWSVM algorithm; executing a binary decisiontree construction operation according to an acquired training data set, and performing training processing according to the preprocessed TWSVM algorithm and non-leaf nodes in a constructed binary decision tree, thereby obtaining a decision function of each non-leaf node; and performing classification prediction processing on to-be-tested samples through the binary decision tree and the decision functions, thereby obtaining a classification result. According to the method, the TWSVM algorithm is expanded based on the binary decision tree; the efficiency of processing the multi-classification problem by the TWSVM algorithm is improved; and the accuracy of solving the nonlinear problem is improved through the binary decision tree constructed by kernel clustering. The invention further discloses an image classification training method, a classification prediction method, an image classification system, an image classification device and a computer readable storage medium, which have the abovementioned beneficial effects.

Description

technical field [0001] The present application relates to the technical field of machine learning, and in particular to an image classification method, a training method, a classification prediction method, an image classification system, an image classification device, and a computer-readable storage medium. Background technique [0002] With the development of technology, the degree of computer intelligence is getting higher and higher. Among them, computer vision is a main direction of computer intelligence research. A core problem in computer vision is the classification of images. Specifically, image classification is an abstract description of the input image, and it is determined whether the image data belongs to a certain category in a given classification. Image classification has many application scenarios in actual operation. Some other computer vision problems, such as object positioning, image segmentation, etc., are all based on image classification. Moreove...

AI Technical Summary

Problems solved by technology

However, due to the relatively simple method used to calculate the maximum distance between classes, the optimal decision tree may not be obtained when facing some problems, especially when dealing with some nonlinear problems.

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