Open AccessImage retrieval based on convolutional neural network and linear discriminate analysis
Author(s) -
Wei Xia,
Cong Hu,
Xiawei Cheng,
Peng Chen,
Xing Jin
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/569/5/052052
Subject(s) - computer science , image retrieval , convolutional neural network , artificial intelligence , automatic image annotation , convolution (computer science) , image (mathematics) , pattern recognition (psychology) , visual word , field (mathematics) , artificial neural network , image processing , computer vision , information retrieval , mathematics , pure mathematics
Image retrieval is a hot research topic in the field of computer vision image processing, and the user queries the image database for similar images and produces a list of recommendations. The paper firstly sets forth the research status of image retrieval, then the convolution neural network is briefly introduced. Due to the traditional image retrieval and recommendation system use manual extraction of image features is relatively cumbersome, and the retrieval accuracy is not high research status, the paper proposes an image retrieval method based on the improved convolutional neural network and linear discriminate analysis. Caltech256 and CIFAR-10 datasets were trained using the model in this paper, experimental, results show that the proposed method can effectively improve the performance of retrieval.