(Enter summary)
Abstract: In this thesis, we develop and test an approach to retrieving images from an image
database based on content similarity. First, each picture is divided into many
overlapping regions. For each region, the sub-picture is filtered and converted into
a feature vector. In this way, each picture is represented by a number of di#erent
feature vectors. The user selects positive and negative image examples to train the
system. During the training, a multiple-instance learning method known as the
... (Update)
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BibTeX entry: (Update)
C. Yang and T. Lozano-Perez, "Image Database Retrieval with Multiple-Instance Learning Techniques", Proc. International Conference on Data Engineering, 2000, pp. 233-243. http://citeseer.ist.psu.edu/yang00image.html More
@inproceedings{ yang00image,
author = "Cheng Yang and Tomas Lozano-Perez",
title = "Image Database Retrieval with Multiple-Instance Learning Techniques",
booktitle = "{ICDE}",
pages = "233-243",
year = "2000",
url = "citeseer.ist.psu.edu/yang00image.html" }
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Solving the multipleinstance problem with axis-parallel rect..
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A framework for multiple-instance learning
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