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In this paper we propose a Hidden Markov Model for modeling and extracting vine structure from images. We built up from previous research to infer connectivity of cane segments extracted from binary images. We use skeletonisation and polylines to model cane segments and we use simulated annealing to optimize an energy function defined in terms of attributes observed for each connection. We formulate...
Model combination is a popular technique to integrate several knowledge sources into automatic speech recognition for better system accuracy. In this paper, we report our recent work on the integration of the hidden Markov model based acoustic model, the multi-layer perceptron based phoneme classifier and Gaussian mixture model based tone classifier in lattice rescoring. Moreover, we use discriminative...
A majority of the approaches to activity recognition in sensor environments are either based on manually constructed rules for recognizing activities or lack the ability to incorporate complex temporal dependencies. Furthermore, in many cases, the rather unrealistic assumption is made that the subject carries out only one activity at a time. In this paper, we describe the use of Markov logic as a...
System call trace is one of the behavior characteristics of system process. Each system call of the trace depends on several previous system calls. Using Markov model to capture such probabilistic characteristic of the system call is time consuming. Thus, we use Probabilistic Suffix Tree to extract this feature. PST is trained with the normal system call traces. We define a new measure of abnormal...
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