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정민영(CHUNG, Minyoung),이현수(LEE, Hyunsoo) 한국실내디자인학회 2019 한국실내디자인학회 학술대회논문집 Vol.21 No.3
This paper suggests Emotional adjective prediction using a deep learning approach. The color is important since colors help us to identify an object and colors have symbols that interact with emotion. It is difficult to design based emotions that emotional color are not sufficient to analyze color design by intuition. Before it will expand color data, it is necessary to verify throughout variety source qualitative and quantitative research. It is difficult to design based emotions that is necessary to verify throughout variety source qualitative and quantitative research. This research focused on a deep learning method for emotional color classification that can replace thousands of people’s cognition. The input of the fusion is given to a support of Python language for image classification. This research has concluded that it is desirable to use Deep learning for classifying the set of color of images and it helps color analysis efficiently. Deep learning makes the quality of universal perception with computation easier for user experience. This research has concluded that it is desirable to use Deep leaning for classifying the set of color of images. ImageNet with convolutional neural network makes the quality of universal perception with Deep leaning easier for user experience. A designer makes color combinations institutionally that is classified using deep learning, and can be analyzed emotion as A is 90 percentage ordinary and B is 50 percentage extraordinary in two minuits for deep learning thousand emotional colors and classifying over one hundreds color palettes. It is expected to use these results of research have implications for color design and analysis.