Creative idea generation method based on deep learning technology
Generating creative ideas is critical in the design process. Currently, massive amounts of design data are existing and effective use of data can stimulate inspiration. However, there has been relatively little research on large-scale design image materials and creative knowledge mining. Here we rep...
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| Veröffentlicht in: | International journal of technology and design education 2021-04, Vol.31 (2), p.421-440 |
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| container_title | International journal of technology and design education |
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| creator | Zhao, Tianjiao Yang, Junyu Zhang, Hechen Siu, Kin Wai Michael |
| description | Generating creative ideas is critical in the design process. Currently, massive amounts of design data are existing and effective use of data can stimulate inspiration. However, there has been relatively little research on large-scale design image materials and creative knowledge mining. Here we report a creative idea generation method based on deep learning technology. Firstly, we identified the most effective point for presenting image stimuli for inspiration. Then we used artificial selection to construct a substantial database of highly creative image stimuli. Based on the selected images, we used canonical correlation analysis and convolutional neural networks to learn two projections to search for highly creative images in a logo database. The proposed method combines design theory and computational techniques, providing a new creative design thinking method for identifying appropriate stimuli in large databases. |
| doi_str_mv | 10.1007/s10798-019-09556-y |
| format | Article |
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| subjects | Artificial neural networks Concept Formation Correlation analysis Creative Thinking Creativity Deep learning Design Design thinking Education Educational Technology Innovations Inspiration Learning and Instruction Science Education Stimuli |
| title | Creative idea generation method based on deep learning technology |
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