A Neural Network Based Self-Learning Algorithm of Image Retrieval
基于神经网络自学习的图像检索方法

In recent years, relevance feedback technique has become an active research method in image retrieval . A self-learning algorithm of image retrieval using forward propagation neural network is proposed in this paper. During the interactive retrieval process, users can mark positive images similar to the query image. Then the algorithm constructs a forward neural network and retrieves again based on the learned neural network. The experimental result over 9 918 images shows that the proposed approach greaty reduces the user's effort of composing a query and representing a concept. During the interactive learning and retrieval process, more and more correct images can be found in the anterior result. This approch is robust to various kinds of feature representation and simiarity distance formulas.