A High Similarity Image Recognition Method Based on Convolutional Neural Network
Considering the high similarity in some images,it can lead to incorrect image classification or im-age confusion.In order to meet the requirements of high similarity image recognition,a high similarity image recognition method based on convolutional neural network is proposed.Based on the preprocessing of high simi-larity images,it will calculate the weighted sum of similarity of image features,and retrieve the similarity of high similarity image features by constructing a frequency histogram of high similarity image features.Based on the sensitivity among image features in neurons,the error function is established,and combined with the sensitivity of image features in the sampling layer,the weights of convolutional neural network are updated.Using iterative analysis method,it will determine the center point of the image,and use the center point as the judgment condi-tion to achieve high similarity image recognition.The experimental results show that the proposed method can recognize images with high similarity and improve the recognition efficiency of images.
high similarityimage recognitionsimilarity retrievalweight updateconvolutional neural network
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