Study on image retrieval system base on multi-objective and multi-instance learning
Ke Chen, Zhiping Peng, Wende Ke · International Journal of Wireless and Mobile Computing · 2013
In this paper, the multi-instance learning algorithm is improved under the image retrieval framework based on contents, and the improved multi-instance learning algorithm is applied to image retrieval to better handle the ambiguity of the image. In this method, the image is used as the multi-instance bag and is divided into multiple instances by image segmentation algorithm, and then the multi-instance learning is performed with the multi-objective-diversedensity algorithm. The learning results are ordered by image similarity using the vector space model. Finally, relevant feedback is given in accordance with the positive bag and negative bag chosen by the user to provide satisfactory results to the user.