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CVPR
2010
IEEE
16 years 19 days ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
BSN
2009
IEEE
160views Sensor Networks» more  BSN 2009»
15 years 12 months ago
BSN Simulator: Optimizing Application Using System Level Simulation
—A biomonitoring application running on wireless BAN has stringent timing and energy requirements. Developing such applications therefore presents unique challenges in both hardw...
Ioana Cutcutache, Thi Thanh Nga Dang, Wai Kay Leon...
ISBI
2009
IEEE
15 years 12 months ago
Detecting Maximal Directional Changes in Spatial fMRI Response Using Canonical Correlation Analysis
Traditional fMRI analysis has focused on modeling temporal changes in BOLD signals on a voxel-by-voxel basis to infer brain activation. To incorporate spatial information, we have...
Bernard Ng, Rafeef Abugharbieh, Martin McKeown
MMM
2009
Springer
186views Multimedia» more  MMM 2009»
15 years 12 months ago
A New Multiple Kernel Approach for Visual Concept Learning
In this paper, we present a novel multiple kernel method to learn the optimal classification function for visual concept. Although many carefully designed kernels have been propose...
Jingjing Yang, Yuanning Li, YongHong Tian, Lingyu ...
SAC
2009
ACM
15 years 11 months ago
Celling SHIM: compiling deterministic concurrency to a heterogeneous multicore
Parallel architectures are the way of the future, but are notoriously difficult to program. In addition to the low-level constructs they often present (e.g., locks, DMA, and non-...
Nalini Vasudevan, Stephen A. Edwards