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A SIMPLE ARTIFICIAL NEURAL NETWORK FOR FIRE DETECTION USING LANDSAT-8 DATA

机译:使用Landsat-8数据进行防火检测的简单人工神经网络

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Fixed threshold models have been widely used in active fire detection products. However, its accuracy is limited due to the complexity of setting up thresholds. Artificial neural network (ANN) is capable of learning from data and can decide weights automatically. Given enough data, an ANN model is able to optimize itself and quickly find an optimal solution. In this work, a simple ANN model is implemented to classify fire pixels from Landsat-8 data. Experimental results show that our ANN model effectively achieves fire detection and performs better than fixed threshold model in certain circumstances.
机译:固定阈值模型已广泛用于主动火灾探测产品。然而,由于设置阈值的复杂性,其精度受到限制。人工神经网络(ANN)能够从数据学习,可以自动决定权重。给定足够的数据,ANN模型能够优化自己并快速找到最佳解决方案。在这项工作中,实现了一个简单的ANN模型,以将Fire像素分类为Sandsat-8数据。实验结果表明,我们的ANN模型在某些情况下有效地实现了火灾探测并在固定阈值模型中表现优于固定阈值模型。

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