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» New Features to Identify Computer Generated Images
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CVPR
2007
IEEE
15 years 11 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
ICIP
2009
IEEE
15 years 10 months ago
Face Recognition Using Sift Features
Face recognition has many important practical applications, like surveillance and access control. It is concerned with the problem of correctly identifying face images and assigni...
JVCIR
2006
127views more  JVCIR 2006»
14 years 9 months ago
Automatic liver segmentation for volume measurement in CT Images
Computed tomography (CT) images have been widely used for diagnosis of liver disease and volume measurement for liver surgery or transplantation. Automatic liver segmentation and ...
Seong-Jae Lim, Yong-Yeon Jeong, Yo-Sung Ho
91
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VISUALIZATION
2003
IEEE
15 years 2 months ago
Visualizing Industrial CT Volume Data for Nondestructive Testing Applications
This paper describes a set of techniques developed for the visualization of high-resolution volume data generated from industrial computed tomography for nondestructive testing (N...
Runzhen Huang, Kwan-Liu Ma, Patrick S. McCormick, ...
MICCAI
2004
Springer
15 years 10 months ago
An Uncertainty-Driven Hybrid of Intensity-Based and Feature-Based Registration with Application to Retinal and Lung CT Images
Abstract. A new hybrid of feature-based and intensity-based registration is presented. The algorithm reflects a new understanding of the role of alignment error in the generation o...
Charles V. Stewart, Ying-Lin Lee, Chia-Ling Tsai