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DIS
2009
Springer
15 years 4 months ago
MICCLLR: Multiple-Instance Learning Using Class Conditional Log Likelihood Ratio
Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
Yasser El-Manzalawy, Vasant Honavar
CVPR
2009
IEEE
15 years 1 months ago
Efficiently training a better visual detector with sparse eigenvectors
Face detection plays an important role in many vision applications. Since Viola and Jones [1] proposed the first real-time AdaBoost based object detection system, much effort has ...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
CVPR
2009
IEEE
16 years 4 months ago
LidarBoost: Depth Superresolution for ToF 3D Shape Scanning
Depth maps captured with time-of-flight cameras have very low data quality: the image resolution is rather limited and the level of random noise contained in the depth maps is v...
Sebastian Schuon (Stanford University), Christian ...
BMCBI
2006
153views more  BMCBI 2006»
14 years 9 months ago
Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive
Background: Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in ...
Hiro Takahashi, Takeshi Nemoto, Teruhiko Yoshida, ...
CIKM
2005
Springer
14 years 11 months ago
Using RankBoost to compare retrieval systems
This paper presents a new pooling method for constructing the assessment sets used in the evaluation of retrieval systems. Our proposal is based on RankBoost, a machine learning v...
Huyen-Trang Vu, Patrick Gallinari