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» Domain Adaptation for Object Recognition: An Unsupervised Ap...
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ECCV
2010
Springer
14 years 10 months ago
Adapting Visual Category Models to New Domains
Abstract. Domain adaptation is an important emerging topic in computer vision. In this paper, we present one of the first studies of domain shift in the context of object recogniti...
Kate Saenko, Brian Kulis, Mario Fritz, Trevor Darr...
DAGM
2001
Springer
15 years 2 months ago
A New Contour-Based Approach to Object Recognition for Assembly Line Robots
A complete processing chain for visual object recognition is described in this paper. The system automatically detects individual objects on an assembly line, identifies their typ...
Markus Suing, Lothar Hermes, Joachim M. Buhmann
117
Voted
CVPR
2012
IEEE
12 years 12 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
80
Voted
DIS
2006
Springer
15 years 1 months ago
Automatic Recognition of Landforms on Mars Using Terrain Segmentation and Classification
Mars probes send back to Earth enormous amount of data. Automating the analysis of this data and its interpretation represents a challenging test of significant benefit to the doma...
Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta
ICASSP
2008
IEEE
15 years 4 months ago
Unsupervised language model adaptation via topic modeling based on named entity hypotheses
Language model (LM) adaptation is often achieved by combining a generic LM with a topic-specific model that is more relevant to the target document. Unlike previous work on unsup...
Yang Liu, Feifan Liu