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» Image Retrieval and Annotation Using Maximum Entropy
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SAC
2002
ACM
13 years 7 months ago
Color patterns for pictorial content description
In this paper, we propose a new type of image feature, which consists of patterns of colors and intensities that capture the latent associations among images and primitive feature...
Daniela Stan, Ishwar K. Sethi
TRECVID
2008
13 years 9 months ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...
ICARCV
2002
IEEE
116views Robotics» more  ICARCV 2002»
14 years 15 days ago
Content-based image retrieval in surface inspection
In this paper a prototype system is described for the management and content-based retrieval of defect images in huge image databases. This is a real problem in surface inspection...
Jukka Iivarinen, Jussi Pakkanen, Juhani Rauhamaa
ICCV
2011
IEEE
12 years 7 months ago
Strong Supervision From Weak Annotation: Interactive Training of Deformable Part Models
We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...
Steven Branson, Pietro Perona, Serge Belongie
MM
2009
ACM
269views Multimedia» more  MM 2009»
14 years 2 months ago
Semi-supervised topic modeling for image annotation
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...