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ICCV
2011
IEEE
14 years 6 months ago
Annotator Rationales for Visual Recognition
Traditional supervised visual learning simply asks annotators “what” label an image should have. We propose an approach for image classification problems requiring subjective...
Jeff Donahue, Kristen Grauman
MMM
2011
Springer
234views Multimedia» more  MMM 2011»
14 years 9 months ago
Image Super-Resolution by Vectorizing Edges
As the resolution of output device increases, the demand of high resolution contents has become more eagerly. Therefore, the image superresolution algorithms become more important....
Chia-Jung Hung, Chun-Kai Huang, Bing-Yu Chen
ICMCS
2006
IEEE
124views Multimedia» more  ICMCS 2006»
16 years 2 days ago
Combining Textual and Visual Ontologies to Solve Medical Multimodal Queries
In order to solve medical multimodal queries, we propose to split the queries in different dimensions using ontology. We extract both textual and visual terms depending on the ont...
Saïd Radhouani, Joo-Hwee Lim, Jean-Pierre Che...
MVA
1994
142views Computer Vision» more  MVA 1994»
15 years 7 months ago
The Evaluation of Textile Design's Visual Feature by Using a Genetic Algorithm
The designs that have been stored in early days are often used as a reference when textile designs are created. To effectively use these resources, a wellequipped design database ...
Ken'ichi Ohta, Kouichi Nishida, Fujio Miyawaki, Ka...
TMI
2008
122views more  TMI 2008»
15 years 6 months ago
The Elliptical Cone of Uncertainty and Its Normalized Measures in Diffusion Tensor Imaging
Diffusion tensor magnetic resonance imaging (DT-MRI) is capable of providing quantitative insights into tissue microstructure in the brain. An important piece of information offere...
Cheng Guan Koay, U. Nevo, Lin-Ching Chang, Carlo P...