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» Multiscale Conditional Random Fields for Image Labeling
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ICCV
2009
IEEE
15 years 1 months ago
Factorizing Scene Albedo and Depth from a Single Foggy Image
Atmospheric conditions induced by suspended particles, such as fog and haze, severely degrade image quality. Restoring the true scene colors (clear day image) from a single imag...
Louis Kratz, Ko Nishino
ACCV
2009
Springer
14 years 3 months ago
Weighted Map for Reflectance and Shading Separation Using a Single Image
In real world, a scene is composed by many characteristics. Intrinsic images represent these characteristics by two components, reflectance (the albedo of each point) and shading (...
Sung-Hsien Hsieh, Chih-Wei Fang, Te-Hsun Wang, Chi...
MICCAI
2002
Springer
14 years 9 months ago
Validation of Tissue Modelization and Classification Techniques in T1-Weighted MR Brain Images
Abstract. We propose a deep study on tissue modelization and classification Techniques on T1-weighted MR images. Three approaches have been taken into account to perform this valid...
Meritxell Bach Cuadra, Bram Platel, Eduardo Solana...
ICASSP
2011
IEEE
13 years 8 days ago
Using residual vector quantization for image content classification
Multistage residual vector quantizers (RVQ) with optimal direct sum decoder codebooks have been successfully designed and implemented for data compression. Due to its multistage s...
Syed Irteza Ali Khan, Christopher F. Barnes
CIKM
2008
Springer
13 years 10 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan