標題: A multiple-instance neural networks based image content retrieval system
作者: Chuang, Shun-Chin
Xu, Yeong-Yuh
Fu, Hsin Chia
Huang, Hsiang-Cheh
資訊工程學系
Department of Computer Science
公開日期: 2006
摘要: In this paper, we proposed a Multiple-Instance Neural Network (MINN) for content-based image retrieval (CBIR). In order to represent the rich content of an image without precisely image segmentation, the image retrieval problem is considered as a multiple-instance learning problem. A set of exemplar images are selected by a user, each of which is labelled as conceptual related (positive) or conceptual unrelated (negative) image. Then, the proposed MINN is trained by using the proposed learning algorithm to learn the user's preferred image concept from the positive and negative examples. Experimental results show that: (1) without image segmentation and using only the color histogram as the image feature, the MINN without relevance feedback performs slightly inferior to some leading image retrieval methods, and (2) the MINN with the relevance feedback can significantly improve the retrieving performance from 40.3% to 59.3%, which outperforms to the results of some leading image retrieval methods.
URI: http://hdl.handle.net/11536/17349
ISBN: 0-7695-2616-0
期刊: ICICIC 2006: First International Conference on Innovative Computing, Information and Control, Vol 2, Proceedings
起始頁: 412
結束頁: 415
Appears in Collections:Conferences Paper