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Research of Image Affective Semantic Rules Based on Neural Network

机译:基于神经网络的图像情感语义规则研究

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To bridge the semantic gaps between the low-level image visual features and the high-level emotional semantics, the paper describes image features using texture and completes the semantic mapping through BP neural network. On the premise of keeping the accuracy of classification unchanged, the trained feedforward neural network is pruned using RX algorithm. Finally, the rules of IF-THEN which can be understood easily are extracted from pruned neural network model. The experiment shows that the method is effective and the rules extracted are comprehensible.
机译:要在低级图像视觉功能和高级情感语义之间桥接语义间隙,纸张描述了使用纹理的图像特征,并完成通过BP神经网络的语义映射。在保持分类的准确性不变的前提下,使用RX算法修剪训练的前馈神经网络。最后,从修剪的神经网络模型中提取可以容易地理解的IF-DON的规则。实验表明该方法是有效的,提取的规则是可理解的。

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