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ICONIP
2007
13 years 10 months ago
Using Image Stimuli to Drive fMRI Analysis
We introduce a new unsupervised fMRI analysis method based on Kernel Canonical Correlation Analysis which differs from the class of supervised learning methods that are increasing...
David R. Hardoon, Janaina Mourão Miranda, M...
ICMCS
2009
IEEE
415views Multimedia» more  ICMCS 2009»
13 years 6 months ago
A new localized superpixel Markov random field for image segmentation
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
Xiaofeng Wang, Xiao-Ping Zhang
CVPR
2008
IEEE
14 years 10 months ago
A joint appearance-spatial distance for kernel-based image categorization
The goal of image categorization is to classify a collection of unlabeled images into a set of predefined classes to support semantic-level image retrieval. The distance measures ...
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang,...
NIPS
2004
13 years 10 months ago
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution
Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
Hyun-Jin Park, Te-Won Lee
TITS
2008
250views more  TITS 2008»
13 years 8 months ago
Learning, Modeling, and Classification of Vehicle Track Patterns from Live Video
This paper presents two different types of visual activity analysis modules based on vehicle tracking. The highway monitoring module accurately classifies vehicles into eight diffe...
Brendan Tran Morris, Mohan M. Trivedi