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» Fine-grained object recognition in underwater visual data
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CVPR
2009
IEEE
16 years 4 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
103
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CONIELECOMP
2011
IEEE
14 years 1 months ago
FPGA design and implementation for vertex extraction of polygonal shapes
This work focuses on developing systems of blocks in SIMULINK and VHDL to reuse on design of applications involving the recognition of polygonal objects. Usage of this work reduce...
Jorge Martínez-Carballido, Jorge Guevara-Es...
CVPR
2006
IEEE
15 years 11 months ago
On-line Boosting and Vision
Boosting has become very popular in computer vision, showing impressive performance in detection and recognition tasks. Mainly off-line training methods have been used, which impl...
Helmut Grabner, Horst Bischof
PAMI
2011
14 years 4 months ago
Multiple Kernel Learning for Dimensionality Reduction
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
ICCV
2003
IEEE
15 years 11 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...