The AGV decision making subsystem directly affects the performance of the vehicle. The information it uses can be classified into "Objective Information" and "Subjective Information" two major grou...
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In video surveillance system, detection and tracking of vehicles are two foundational and significant tasks. In this paper, a vehicle detection and tracking method based on rear lamp pairs is proposed. The proposed me...
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Public traffic is required for the convenient travel, reducing traffic congestion and accidents, low-carbon, environmental protection, sustainable development, and traffic demand of giant sports and large business act...
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Pedestrians are key participants in transportation systems, so pedestrian detection in video surveillance systems is of great significance to the research and application of intelligent Transportation systems (ITS). W...
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The multipoint short-term traffic flow forecasting should deal with mass of historical traffic flow data from intersections in an area or urban. So the problem in runtime still remains to be the major obstacle for the...
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Vehicle License Plate Recognition (VLPR) system is a core module in intelligent Transportation systems (ITS). In this paper, a VLPR system is proposed. Considering that license plate localization is the most important...
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The key of designing MCMC algorithm is the choice of acceptance function. In this work, Selection criteria of acceptance function is given, and an improved Multi-point Metropolis algorithm with generic acceptance func...
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Over the last few years, Twitter is increasingly becoming an important source of up-to-date topics about what is happening in the world. In this paper, we propose a dynamic topic association detection model to discove...
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ISBN:
(纸本)9781450312301
Over the last few years, Twitter is increasingly becoming an important source of up-to-date topics about what is happening in the world. In this paper, we propose a dynamic topic association detection model to discover relations between Twitter topics, by which users can gain insights into richer information about topics of interest. The proposed model utilizes a time constrained method to extract event-based spatio-temporal topic association, and constructs a dynamic temporal map to represent the obtained result. Experimental results show the improvement of the proposed model compared to static spatio-temporal method and co-occurrence method. Copyright is held by the author/owner(s).
Most objects with regular regions could be detected as Maximally Stable Extremal Regions (MSER) [20]. In this paper, We formulate object detection as a bi-label (object and non-object regions) segmentation problem, an...
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This paper focuses on a class of unknown discrete-time nonlinear systems with dead-zone control constraints based on adaptive dynamic programming (ADP). The discrete-time Hamilton-Jacobi-Bellman (DTHJB) equation corre...
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