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» Optimizing Learning in Image Retrieval
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ICASSP
2009
IEEE
14 years 5 months ago
Map approach to learning sparse Gaussian Markov networks
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
Narges Bani Asadi, Irina Rish, Katya Scheinberg, D...
MM
2006
ACM
189views Multimedia» more  MM 2006»
14 years 4 months ago
Real-time computerized annotation of pictures
Automated annotation of digital pictures has been a highly challenging problem for computer scientists since the invention of computers. The capability of annotating pictures by c...
Jia Li, James Ze Wang
ICIP
2007
IEEE
14 years 12 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian
ICAT
2003
IEEE
14 years 3 months ago
Distance Learning of Chang'an in an Immersive Environment
We have made a computer graphics model of Chang'an City when it was the capital of China during the Tang Dynasty (7-10th century). The real-time rendered images are projected...
Miho Kobayashi, Kei Utsugi, Masami Yamasaki, Haruo...
CVPR
2006
IEEE
15 years 8 days ago
AnnoSearch: Image Auto-Annotation by Search
Although it has been studied for several years by computer vision and machine learning communities, image annotation is still far from practical. In this paper, we present AnnoSea...
Xin-Jing Wang, Lei Zhang, Feng Jing, Wei-Ying Ma