Method and system for classifying UI (User Interface) abnormal images based on convolutional neural network

Abstract

The invention discloses a method and a system for classifying UI (User Interface) abnormal images based on a convolutional neural network. The method comprises the steps of enabling a server side to receive to-be-processed UI picture data sent by a client side; calling an abnormality classification model to classify the to-be-processed UI picture data to obtain a picture type of the to-be-processed UI picture data, wherein the abnormality classification model is a convolutional neural network model which is completely trained; and returning the picture type to the client side. According to themethod and the system for classifying the UI (User Interface) abnormal images based on the convolutional neural network, effective features of the UI pictures can be effectively extracted by use of the convolutional neural network, the features do not need to be artificially designed but are learned by training of the convolutional neural network so that the learning features can be guaranteed asa whole to have translation invariance; on the one hand, a certain reusability and universality are possessed, on the other hand, a good classification effect can be achieved through the effective features of the UI pictures, and thus the accuracy for picture classification is greatly improved.

Description

technical field [0001] The invention relates to the technical field of computer vision and deep learning, and in particular, to a method and system for classifying abnormal UI pictures based on a convolutional neural network. Background technique [0002] Image recognition refers to the technology of using computers to process, analyze and understand images to identify targets and objects in different patterns. Existing public technical solutions, such as the image recognition-based anomaly detection method of patent application number CN201710192706.6, use traditional machine learning techniques to detect image anomalies, but this technical solution requires you to design certain classification training. The specific characteristics of the image, and more preprocessing of the image is required, such as the need to first perform grayscale processing, regularization processing, etc., that is, there is a cumbersome artificial feature extractor design; and it is only a binary c...

AI Technical Summary

Problems solved by technology

Existing public technical solutions, such as the anomaly detection method based on image recognition in the patent application number CN201710192706.6, use traditional machine learning technology to detect image anomalies, but this technical solution needs to design some classification training by yourself. The specific characteristics of the image, and more preprocessing of the image is required, such as the need to grayscale the image, regularize it, etc., that is, there is a cumbersome artificial feature extractor design; and it is only a binary classifier, The model does not have a certain degree of reusability and versatility, and cannot be directly applied to other UI abnormalities. At the same time, the above technical solution is not a solution for app UI abnormal image classification

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