Correction to: Targets Classification Based on Multi-sensor Data Fusion and Supervised Learning for Surveillance Application
Wireless Personal Communications(2023)
摘要
In surveillance application scenarios, like border security and area monitoring, potential targets to be detected may be either an unarmed person, a soldier carrying ferrous weapon or a vehicle. Detection is the first phase of a monitoring process, followed by the target classification phase and finally their tracking if required. This work focuses on classification step, where we introduce our classification approach not too resource-intensive, easy to implement and suitable for large scale environment. For that, we used probabilistic reasoning techniques to address multi sensing data correlation and take advantage of multi-sensor data fusion, then, based on adopted fusion architecture, we implemented our trained classification model in a fusion node, to make the classification more accurate.
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关键词
Surveillance,Target classification,Probabilistic approach,Data fusion,Machine learning,Wireless sensor network
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