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Study on modeling of multispectral emissivity and optimization algorithm

机译:多光谱发射率建模与优化算法研究

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Target's spectral emissivity changes variously, and how to obtain target's continuous spectral emissivity is a difficult problem to be well solved nowadays. In this letter, an activation-function-tunable neural network is established, and a multistep searching method which can be used to train the model is proposed. The proposed method can effectively calculate the object's continuous spectral emissivity from the multispectral radiation information. It is a universal method, which can be used to realize on-line emissivity demarcation.
机译:目标的光谱发射率变化很大,如何获得目标的连续光谱发射率是当今亟待解决的难题。在本文中,建立了一个激活函数可调神经网络,并提出了一种可用于训练模型的多步搜索方法。该方法可以有效地根据多光谱辐射信息计算出物体的连续光谱发射率。它是一种通用方法,可用于实现在线发射率标定。

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