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» Conditional Random Fields for Object Recognition
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ACSW
2004
15 years 3 months ago
Applying Online Gradient Descent Search to Genetic Programming for Object Recognition
This paper describes an approach to the use of gradient descent search in genetic programming (GP) for object classification problems. In this approach, pixel statistics are used ...
William D. Smart, Mengjie Zhang
120
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AAAI
2008
15 years 4 months ago
Hidden Dynamic Probabilistic Models for Labeling Sequence Data
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
Xiaofeng Yu, Wai Lam
CVPR
2010
IEEE
15 years 8 months ago
Towards Semantic Embedding in Visual Vocabulary
Visual vocabulary serves as a fundamental component in many computer vision tasks, such as object recognition, visual search, and scene modeling. While state-of-the-art approaches...
R.-R. Ji, Hongxun Yao, Xiaoshuai Sun
ICIP
2009
IEEE
16 years 3 months ago
Visual Tracking Of Object Silhouettes
In this paper we propose a new method that addresses the problem of tracking the bitmap (silhouette) of an object in a video under very general conditions. We assume a general tar...
ICASSP
2011
IEEE
14 years 6 months ago
MLP based phoneme detectors for Automatic Speech Recognition
Phoneme posterior probabilities estimated using Multi-Layer Perceptrons (MLPs) are extensively used both as acoustic scores and features for speech recognition. In this paper we e...
Samuel Thomas, Patrick Nguyen, Geoffrey Zweig, Hyn...