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ICIP
2008
IEEE
15 years 21 days ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram
ICMLC
2005
Springer
14 years 4 months ago
Adaptive Online Multi-stroke Sketch Recognition Based on Hidden Markov Model
This paper presents a novel approach for adaptive online multi-stroke sketch recognition based on Hidden Markov Model (HMM). The method views the drawing sketch as the result of a ...
Zhengxing Sun, Wei Jiang, Jianyong Sun
NLPRS
2001
Springer
14 years 3 months ago
A Maximum Entropy Tagger with Unsupervised Hidden Markov Models
We describe a new tagging model where the states of a hidden Markov model (HMM) estimated by unsupervised learning are incorporated as the features in a maximum entropy model. Our...
Jun'ichi Kazama, Yusuke Miyao, Jun-ichi Tsujii
ICASSP
2011
IEEE
13 years 2 months ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien
AAAI
2008
14 years 1 months ago
Towards Faster Planning with Continuous Resources in Stochastic Domains
Agents often have to construct plans that obey resource limits for continuous resources whose consumption can only be characterized by probability distributions. While Markov Deci...
Janusz Marecki, Milind Tambe