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» New Features to Identify Computer Generated Images
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CVPR
2008
IEEE
16 years 8 months ago
Semantic texton forests for image categorization and segmentation
We propose semantic texton forests, efficient and powerful new low-level features. These are ensembles of decision trees that act directly on image pixels, and therefore do not ne...
Jamie Shotton, Matthew Johnson, Roberto Cipolla
ICCV
2005
IEEE
16 years 8 months ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall
CCS
2011
ACM
14 years 6 months ago
PaperSpeckle: microscopic fingerprinting of paper
Paper forgery is among the leading causes of corruption in many developing regions [2]. In this paper, we introduce PaperSpeckle, a robust system that leverages the natural random...
Ashlesh Sharma, Lakshminarayanan Subramanian, Eric...
ICPR
2004
IEEE
16 years 7 months ago
Object Class Recognition using Images of Abstract Regions
lass Recognition using Images of Abstract Regions Yi Li, Jeff A. Bilmes, and Linda G. Shapiro Department of Computer Science and Engineering Department of Electrical Engineering Un...
Jeff A. Bilmes, Linda G. Shapiro, Yi Li
JMLR
2012
13 years 9 months ago
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
We consider the task of estimating, from observed data, a probabilistic model that is parameterized by a finite number of parameters. In particular, we are considering the situat...
Michael Gutmann, Aapo Hyvärinen