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ECCV
2010
Springer
15 years 1 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
88
Voted
WWW
2008
ACM
16 years 1 months ago
A graph-theoretic approach to webpage segmentation
We consider the problem of segmenting a webpage into visually and semantically cohesive pieces. Our approach is based on formulating an appropriate optimization problem on weighte...
Deepayan Chakrabarti, Ravi Kumar, Kunal Punera
127
Voted
ICPR
2008
IEEE
16 years 2 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
112
Voted
ICIP
2007
IEEE
15 years 7 months ago
Coding Artifacts Robust Resolution Up-conversion
In this paper, an integrated resolution up-conversion and compression artifacts removal algorithm is proposed. Local image patterns are classified into object details or coding ar...
Ling Shao, Hao Hu, Gerard de Haan
CATE
2004
190views Education» more  CATE 2004»
15 years 2 months ago
Enhancing Online Learning Performance: An Application of Data Mining Methods
Recently web-based educational systems collect vast amounts of data on user patterns, and data mining methods can be applied to these databases to discover interesting associations...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...