Creative Idea Generation Method Based on Deep Learning Technology

Autor/inn/en	Zhao, Tianjiao; Yang, Junyu; Zhang, Hechen; Siu, Kin Wai Michael
Titel	Creative Idea Generation Method Based on Deep Learning Technology
Quelle	In: International Journal of Technology and Design Education, 31 (2021) 2, S.421-440 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0957 7572
DOI	10.1007/s10798-019-09556-y
Schlagwörter	Concept Formation; Creative Thinking; Stimuli; Design; Databases + Suchen Sie Ihr Suchwort? Concept learning; Begriffsbildung; Kreatives Denken; Anreizsystem; Datenbank
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01