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MICCAI
2010
Springer
15 years 4 months ago
Manifold Learning for Biomarker Discovery in MR Imaging
We propose a framework for the extraction of biomarkers from low-dimensional manifolds representing inter- and intra-subject brain variation in MR image data. The coordinates of ea...
Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Daniel...
WAIM
2010
Springer
15 years 4 months ago
Hotspot District Trajectory Prediction
Trajectory prediction (TP) of moving objects has grown rapidly to be a new exciting paradigm. However, existing prediction algorithms mainly employ kinematical models to approximat...
Hongjun Li, Changjie Tang, Shaojie Qiao, Yue Wang,...
ICASSP
2011
IEEE
14 years 10 months ago
Discriminant binary data representation for speaker recognition
In supervector UBM/GMM paradigm, each acoustic file is represented by the mean parameters of a GMM model. This supervector space is used as a data representation space, which has...
Jean-François Bonastre, Pierre-Michel Bousq...
MM
2005
ACM
178views Multimedia» more  MM 2005»
15 years 12 months ago
Attention region selection with information from professional digital camera
The attentive region extraction is a challenging issue for semantic interpretation of image and video content. The successful attentive region extraction greatly facilitates image...
Song Liu, Liang-Tien Chia, Deepu Rajan
ISBI
2007
IEEE
16 years 21 days ago
Step: Spatial-Temporal Enhancement Pattern, for Mr-Based Breast Tumor Diagnosis
This paper demonstrates the importance of capturing SpatialTemporal Enhancement Pattern (STEP) for completely characterizing breast tumor in contrast-enhanced MR images. STEP capt...
Yuanjie Zheng, Sarah Englander, Mitchell D. Schnal...