• Publications
  • Influence
Texture classification using spectral histograms
  • X. Liu, D. Wang
  • Computer Science, Mathematics
  • IEEE Trans. Image Process.
  • 1 June 2003
Based on a local spatial/frequency representation,we employ a spectral histogram as a feature statistic for texture classification. The spectral histogram consists of marginal distributions ofExpand
  • 210
  • 21
Accurate localization of RFID tags using phase difference
Due to their light weight, low power, and practically unlimited identification capacity, radio frequency identification (RFID) tags and associated devices offer distinctive advantages and are widelyExpand
  • 225
  • 14
Efficient algorithms for inferences on Grassmann manifolds
Linear representations and linear dimension reduction techniques are very common in signal and image processing. Many such applications reduce to solving problems of stochastic optimizations orExpand
  • 106
  • 9
A spectral histogram model for texton modeling and texture discrimination
We suggest a spectral histogram, defined as the marginal distribution of filter responses, as a quantitative definition for a texton pattern. By matching spectral histograms, an arbitrary image canExpand
  • 74
  • 8
SCARECROW, SCR-LIKE 23 and SHORT-ROOT control bundle sheath cell fate and function in Arabidopsis thaliana.
Bundle sheath (BS) cells form a single cell layer surrounding the vascular tissue in leaves. In C3 plants, photosynthesis occurs in both the BS and mesophyll cells, but the BS cells are the majorExpand
  • 54
  • 8
Universal Analytical Forms for Modeling Image Probabilities
Seeking probability models for images, we employ a spectral approach where the images are decomposed using bandpass filters and probability models are imposed on the filter outputs (also calledExpand
  • 121
  • 7
Distinctive Roles of STAT5a and STAT5b in Sexual Dimorphism of Hepatic P450 Gene Expression
Stat5b gene disruption leads to an apparent growth hormone (GH) pulse insensitivity associated with loss of male-characteristic body growth rates and male-specific liver gene expression (Udy, G. B.,Expand
  • 157
  • 6
Face recognition using optimal linear components of range images
This paper investigates the use of range images of faces for recognizing people. 3D scans of faces lead to range images that are linearly projected to low-dimensional subspaces for use in aExpand
  • 44
  • 6
Optimal linear representations of images for object recognition
Simplicity of linear representations (of images) makes them a popular tool in imaging analysis applications such as object recognition and image classification. Although several linearExpand
  • 67
  • 5
Face detection using spectral histograms and SVMs
  • C. Waring, X. Liu
  • Medicine, Computer Science
  • IEEE Transactions on Systems, Man, and…
  • 1 June 2005
We present a face detection method using spectral histograms and support vector machines (SVMs). Each image window is represented by its spectral histogram, which is a feature vector consisting ofExpand
  • 133
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