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168
Voted
CVPR
2006
IEEE
16 years 13 days 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. ...
169
Voted
CVPR
2008
IEEE
16 years 8 months ago
Margin-based discriminant dimensionality reduction for visual recognition
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Hakan Cevikalp, Bill Triggs, Frédéri...
TON
2012
13 years 8 months ago
Opportunistic Flow-Level Latency Estimation Using Consistent NetFlow
—The inherent measurement support in routers (SNMP counters or NetFlow) is not sufficient to diagnose performance problems in IP networks, especially for flow-specific problem...
Myungjin Lee, Nick G. Duffield, Ramana Rao Kompell...
CVPR
2008
IEEE
16 years 26 days ago
Bayesian tactile face
Computer users with visual impairment cannot access the rich graphical contents in print or digital media unless relying on visual-to-tactile conversion, which is done primarily b...
Zheshen Wang, Xinyu Xu, Baoxin Li
ICASSP
2011
IEEE
14 years 10 months ago
Exemplar-based Sparse Representation phone identification features
Exemplar-based techniques, such as k-nearest neighbors (kNNs) and Sparse Representations (SRs), can be used to model a test sample from a few training points in a dictionary set. ...
Tara N. Sainath, David Nahamoo, Bhuvana Ramabhadra...