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» Texture classification using invariant ranklet features
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CVPR
2010
IEEE
15 years 5 months ago
Unsupervised Learning of Invariant Features Using Video
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
David Stavens, Sebastian Thrun
ICIP
2001
IEEE
15 years 11 months ago
Indoor vs outdoor classification of consumer photographs using low-level and semantic features
Scene categorization to indoor vs outdoor may be approached by using low-level features for inferring high-level information about the image. Low-level features such as color and ...
Jiebo Luo, Andreas E. Savakis
MVA
2000
234views Computer Vision» more  MVA 2000»
14 years 9 months ago
An automatic assessment scheme for steel quality inspection
This paper presents an automatic system for steel quality assessment, by measuring textural properties of carbide distributions. In current steel inspection, specially etched and p...
Klaus Wiltschi, Axel Pinz, Tony Lindeberg
ICIP
1997
IEEE
15 years 11 months ago
Surrounding Region Dependence Method for Detection of Clustered Microcalcifications on Mammograms
Clustered microcalcifications on X-ray mammograms are an important feature in the detection of breast cancer. For the detection of the clustered microcalcifications on digitized m...
Jong-Kook Kim, Hyun Wook Park
TIP
2002
111views more  TIP 2002»
14 years 9 months ago
Synergizing spatial and temporal texture
Temporal texture accounts for a large proportion of motion commonly experienced in the visual world. Current temporal texture techniques extract primarily motion-based features for...
Chin-Hwee Peh, Loong Fah Cheong