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» Support vector machine learning for image retrieval
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AAAI
2006
13 years 9 months ago
Learning Noun-Modifier Semantic Relations with Corpus-based and WordNet-based Features
We study the performance of two representations of word meaning in learning noun-modifier semantic relations. One representation is based on lexical resources, in particular WordN...
Vivi Nastase, Jelber Sayyad-Shirabad, Marina Sokol...
IWDW
2005
Springer
14 years 1 months ago
Towards Multi-class Blind Steganalyzer for JPEG Images
In this paper, we use the previously proposed calibrated DCT features [9] to construct a Support Vector Machine classifier for JPEG images capable of recognizing which steganograp...
Tomás Pevný, Jessica J. Fridrich
MM
2009
ACM
209views Multimedia» more  MM 2009»
14 years 2 months ago
Brain state decoding for rapid image retrieval
Human visual perception is able to recognize a wide range of targets under challenging conditions, but has limited throughput. Machine vision and automatic content analytics can p...
Jun Wang, Eric Pohlmeyer, Barbara Hanna, Yu-Gang J...
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 8 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
EMNLP
2008
13 years 9 months ago
Discriminative Learning of Selectional Preference from Unlabeled Text
We present a discriminative method for learning selectional preferences from unlabeled text. Positive examples are taken from observed predicate-argument pairs, while negatives ar...
Shane Bergsma, Dekang Lin, Randy Goebel