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ESANN
2006
13 years 9 months ago
Classification of Boar Sperm Head Images using Learning Vector Quantization
We apply Learning Vector Quantization (LVQ) in automated boar semen quality assessment. The classification of single boar sperm heads into healthy (normal) and non-normal ones is b...
Michael Biehl, Piter Pasma, Marten Pijl, Lidia S&a...
ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
14 years 1 months ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
ICMCS
2006
IEEE
104views Multimedia» more  ICMCS 2006»
14 years 1 months ago
A Study on Spatial Scalable Coding using Vector Representation
The major advantage of vector representation of an image is that the image quality is maintained for arbitrary scaling. In recent years, a demand for scalable image coding has bee...
Yuki Yamamoto, Kei Kawamura, Hiroshi Watanabe
ACCV
2007
Springer
14 years 1 months ago
An Occupancy-Depth Generative Model of Multi-view Images
This paper presents an occupancy based generative model of stereo and multi-view stereo images. In this model, the space is divided into empty and occupied regions. The depth of a ...
Pau Gargallo, Peter F. Sturm, Sergi Pujades
WWW
2008
ACM
14 years 8 months ago
Detecting image spam using visual features and near duplicate detection
Email spam is a much studied topic, but even though current email spam detecting software has been gaining a competitive edge against text based email spam, new advances in spam g...
Bhaskar Mehta, Saurabh Nangia, Manish Gupta 0002, ...