Abstract

With the rapid development of artificial intelligence technology, the network image recognition technology of machine learning is intelligent and production and life in computer vision system technology in China have gradually achieved significant success. On this basis, the computer network image recognition system is constructed by machine learning with image features such as cross-verification, fitting, accuracy, feature selection, and dimensionality reduction, and the results show that the machine learning algorithm improves the stability and multi-domain application of computer image recognition through cross-verification and deviation of decision tree units. Recognition technologies such as feature vector extraction, edge information, and texture features of machine learning algorithms improve the accuracy of image recognition.

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