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MM
2010
ACM

Image classification using the web graph

13 years 2 months ago
Image classification using the web graph
Image classification is a well-studied and hard problem in computer vision. We extend a proven solution for classifying web spam to handle images. We exploit the link structure of the web graph: a web page related to a given category is normally linked to other pages describing related objects. Our approach combines information from the webgraph structure with semi-supervised learning from all the unlabeled images to create a superior image-classification model for multimedia data. We show that fusing image, text and web-graph features gives a 12% improvement (in the area under the ROC curve) over content features alone in an adult image-classification experiment. Categories and Subject Descriptors I.5.2 [Pattern Recognition]: Design Methodology-Classifier design and evaluation General Terms Algorithms Keywords Algorithm, image classification, web graph
Dhruv Kumar Mahajan, Malcolm Slaney
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where MM
Authors Dhruv Kumar Mahajan, Malcolm Slaney
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