Extrapolating continuous color emotions through deep learning

Extrapolating continuous color emotions through deep learning
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通过深度学习推断连续的色彩情感

DOI:
10.1103/physrevresearch.2.033350
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发表时间:
2020
影响因子:
4.2
通讯作者:
Mohr, Christine
Mohr, Christine
中科院分区:
--
文献类型:
--
作者:
Ram, Vishaal;Schaposnik, Laura P.;Konstantinou, Nikos;Volkan, Eliz;Papadatou-Pastou, Marietta;Manav, Banu;Jonauskaite, Domicele;Mohr, Christine

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通过实验数据集,我们使用深度学习来实现与颜色相关的情感的 RGB(红、绿、蓝)外推,并对通过该神经网络获得的结果进行数学研究。特别是,我们看到男性(类型个体)通常将某种特定的情绪与较暗的颜色联系起来,而女性(类型个体)将其与较亮的颜色联系起来。老年人也观察到类似的趋势以及与浅色的关联。此外,通过我们的分类矩阵,我们可以识别哪些颜色与情绪关联较弱,以及哪些颜色通常会与其他颜色混淆。
By means of an experimental dataset, we use deep learning to implement an RGB (red, green, and blue) extrapolation of emotions associated to color, and do a mathematical study of the results obtained through this neural network. In particular, we see that males (type-individuals) typically associate a given emotion with darker colors, while females (type-individuals) associate it with brighter colors. A similar trend was observed with older people and associations to lighter colors. Moreover, through our classification matrix, we identify which colors have weak associations to emotions and which colors are typically confused with other colors.
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