To represent and reason with interval-value information of applications in description logic, based on interval-fuzzy set the classical des cription logic ALCN is extended to the fuzzy description logic IFALCN. Its...
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For the low accuracy and imprecise of contour detection evaluation algorithm for a natural image with Ground Truth, we proposed a neighborhood matching algorithm, which had been combined with the original algorithm, a...
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For the low accuracy and imprecise of contour detection evaluation algorithm for a natural image with Ground Truth, we proposed a neighborhood matching algorithm, which had been combined with the original algorithm, and then modified the accuracy of the formula, at last we got the contour detection evaluation algorithm of this paper. Through assessing the contour detection images processed by Canny operator, compared with the original algorithm, The algorithm improved the accuracy value of assessment of contour detection.
In this paper, a novel approach for surveillance video cropping is presented. The basic idea is to obtain a trajectory that a small sub-window can take through the video, selecting the most important regions of the vi...
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In this paper, a novel approach for surveillance video cropping is presented. The basic idea is to obtain a trajectory that a small sub-window can take through the video, selecting the most important regions of the video for display on a smaller monitor. In this framework, the video content is firstly modeled by whether image frames change at each pixel. Then a shortest path algorithm is used to find the globally optimal trajectory for a cropping window. After that a second shortest path formulation is employed to find good cuts from one trajectory to another, improving the coverage of interesting events in the video content. Finally, additional techniques are demonstrated to improve the quality and efficiency of the algorithm, and results are shown on surveillance videos from PETS 2006.
The satisfiability(SAT) problem is an important problem of automated reasoning. In the past decades, many methods of SAT are proposed, such as method based on resolution, method based on tableau and method based on ex...
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In recent years, with the development of the wireless sensor networks, the localization method receives the attention of many researchers. However, due to the network cost and characteristics of sensor nodes, most of ...
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Essential graph is a graphical representation for Markov equivalence classes of Bayesian networks. Learning essential graph can avoid some problems in traditional Bayesian networks learning algorithms: (1) the number ...
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The quantitative understanding of human behavior is a central question of modern science. Because of the complexity of human behavior, it is almost impossible to seek regularities in human dynamics. It is assumed that...
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The quantitative understanding of human behavior is a central question of modern science. Because of the complexity of human behavior, it is almost impossible to seek regularities in human dynamics. It is assumed that human actions are randomly distributed in time in current models for human dynamics. While the characteristics of human behavior combined with the queue model are considered as model for human dynamics based on habit to explain bursts and heavy tails in human dynamics more exactly. Normal distribution is used to simulate intervals of succession of events, and random parameters are set as unexpected events disturbing habit behaviors. Moreover, duration of events are proposed to imitate continual attention to some events in human behaviors.
This paper introduces a qualitative spatial model based on previously developed models for representation and reasoning the spatial information described in natural language. The model is integrated with direction and...
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lti-label learning aims at predicting a proper label set for each unseen *** instance in the dataset is associated with a set of predefined ***-label learning approaches frequently used choose identical feature set to...
lti-label learning aims at predicting a proper label set for each unseen *** instance in the dataset is associated with a set of predefined ***-label learning approaches frequently used choose identical feature set to determine the instance's membership of each label.
Conventional models based on crisp regions can not deal with the Direction Relations between Uncertain Regions (DRUR). Using broad boundary to represent the uncertain boundary, a novel approach is proposed based on mo...
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