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» A Framework for Multiple-Instance Learning
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CVPR
2006
IEEE
15 years 10 months ago
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
FGR
2006
IEEE
147views Biometrics» more  FGR 2006»
15 years 10 months ago
Learning Sparse Features in Granular Space for Multi-View Face Detection
In this paper, a novel sparse feature set is introduced into the Adaboost learning framework for multi-view face detection (MVFD), and a learning algorithm based on heuristic sear...
Chang Huang, Haizhou Ai, Yuan Li, Shihong Lao
ICCV
2005
IEEE
15 years 10 months ago
Learning Effective Image Metrics from Few Pairwise Examples
We present a new approach to learning image metrics. The main advantage of our method lies in a formulation that requires only a few pairwise examples. Apparently, based on the li...
Hwann-Tzong Chen, Tyng-Luh Liu, Chiou-Shann Fuh
ICCV
2005
IEEE
15 years 10 months ago
Learning Non-Generative Grammatical Models for Document Analysis
— We present a general approach for the hierarchical segmentation and labeling of document layout structures. This approach models document layout as a grammar and performs a glo...
Michael Shilman, Percy Liang, Paul A. Viola
WMTE
2005
IEEE
15 years 10 months ago
Innovative Media in Support of Distributed Intelligence and Lifelong Learning
Individual, unaided human abilities are constrained. Media have helped us to transcend boundaries in thinking, working, learning, and collaborating by supporting distributed intel...
Gerhard Fischer, Shin'ichi Konomi