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CVPR
2012
IEEE
13 years 2 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann
CIKM
2009
Springer
15 years 6 months ago
Combining labeled and unlabeled data with word-class distribution learning
We describe a novel simple and highly scalable semi-supervised method called Word-Class Distribution Learning (WCDL), and apply it the task of information extraction (IE) by utili...
Yanjun Qi, Ronan Collobert, Pavel Kuksa, Koray Kav...
ICASSP
2007
IEEE
15 years 6 months ago
Wavelet Footprints and Sparse Bayesian Learning for DNA Copy Number Change Analysis
Alterations in the number of DNA copies are very common in tumor cells and may have a very important role in cancer development and progression. New array platforms provide means ...
Roger Pique-Regi, En-Shuo Tsau, Antonio Ortega, Ro...
LREC
2010
119views Education» more  LREC 2010»
15 years 1 months ago
Predicting Morphological Types of Chinese Bi-Character Words by Machine Learning Approaches
This paper presented an overview of Chinese bi-character words' morphological types, and proposed a set of features for machine learning approaches to predict these types bas...
Ting-Hao Huang, Lun-Wei Ku, Hsin-Hsi Chen
CVPR
2010
IEEE
15 years 8 months ago
Learning Mid-Level Features For Recognition
Many successful models for scene or object recognition transform low-level descriptors (such as Gabor filter responses, or SIFT descriptors) into richer representations of interme...
Y-Lan Boureau, Francis Bach, Yann LeCun, Jean Ponc...