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CVPR
2010
IEEE
14 years 4 months ago
Reading Between The Lines: Object Localization Using Implicit Cues from Image Tags
Current uses of tagged images typically exploit only the most explicit information: the link between the nouns named and the objects present somewhere in the image. We propose to ...
Sung Ju Hwang, University of Texas, Kristen Grauma...
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
13 years 11 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
SDM
2004
SIAM
194views Data Mining» more  SDM 2004»
13 years 9 months ago
Finding Frequent Patterns in a Large Sparse Graph
Graph-based modeling has emerged as a powerful abstraction capable of capturing in a single and unified framework many of the relational, spatial, topological, and other characteri...
Michihiro Kuramochi, George Karypis
ECCV
2008
Springer
14 years 9 months ago
Simultaneous Detection and Registration for Ileo-Cecal Valve Detection in 3D CT Colonography
Object detection and recognition has achieved a significant progress in recent years. However robust 3D object detection and segmentation in noisy 3D data volumes remains a challen...
Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang...
COMBINATORICS
2006
132views more  COMBINATORICS 2006»
13 years 7 months ago
On Computing the Distinguishing Numbers of Trees and Forests
Let G be a graph. A vertex labeling of G is distinguishing if the only label-preserving automorphism of G is the identity map. The distinguishing number of G, D(G), is the minimum...
Christine T. Cheng