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首页> 外文期刊>Systems, Man, and Cybernetics: Systems, IEEE Transactions on >Wildfire Smoke Detection Using Computational Intelligence Techniques Enhanced With Synthetic Smoke Plume Generation
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Wildfire Smoke Detection Using Computational Intelligence Techniques Enhanced With Synthetic Smoke Plume Generation

机译:使用计算智能技术增强合成烟羽生成的野火烟雾检测

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摘要

An early wildfire detection is essential in order to assess an effective response to emergencies and damages. In this paper, we propose a low-cost approach based on image processing and computational intelligence techniques, capable to adapt and identify wildfire smoke from heterogeneous sequences taken from a long distance. Since the collection of frame sequences can be difficult and expensive, we propose a virtual environment, based on a cellular model, for the computation of synthetic wildfire smoke sequences. The proposed detection method is tested on both real and simulated frame sequences. The results show that the proposed approach obtains accurate results.
机译:为了评估对紧急情况和破坏的有效响应,必须及早发现野火。在本文中,我们提出了一种基于图像处理和计算智能技术的低成本方法,该方法能够从远距离拍摄的异类序列中适应和识别野火烟雾。由于帧序列的收集可能既困难又昂贵,因此,我们提出了一种基于细胞模型的虚拟环境,用于计算合成野火烟雾序列。在真实帧序列和模拟帧序列上测试了所提出的检测方法。结果表明,该方法取得了准确的结果。

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