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CVPR
2012
IEEE
11 years 11 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
MTA
2000
165views more  MTA 2000»
13 years 8 months ago
Approximating Content-Based Object-Level Image Retrieval
Object-level image retrieval is an active area of research. Given an image, a human observerdoesnot see randomdots of colors. Rather,he she observesfamiliarobjectsin the image. The...
Wynne Hsu, Tat-Seng Chua, Hung Keng Pung
ECCV
2004
Springer
14 years 10 months ago
On the Significance of Real-World Conditions for Material Classification
Classifying materials from their appearance is a challenging problem, especially if illumination and pose conditions are permitted to change: highlights and shadows caused by 3D st...
Eric Hayman, Barbara Caputo, Mario Fritz, Jan-Olof...
CBMS
2006
IEEE
14 years 2 months ago
An Ontology-Driven Mediator for Querying Time-Oriented Biomedical Data
— Most biomedical research databases contain considerable amounts of time-oriented data. However, temporal knowledge about the contextual meaning of such data is not usually repr...
Martin J. O'Connor, Ravi Shankar, Amar K. Das
CBMS
2007
IEEE
14 years 3 months ago
Auto-Extraction, Representation and Integration of a Diabetes Ontology Using Bayesian Networks
This paper describes how high level biological knowledge obtained from ontologies such as the Gene Ontology (GO) can be integrated with low level information extracted from a Baye...
Kenneth McGarry, Sheila Garfield, Stefan Wermter