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Automatic Generation and Beautification Technology of Landscape Design Based on Deep Learning

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  • Lan Lan

    (University of Sanya, China)

Abstract

Landscape designers play a crucial role in enhancing the quality of living spaces. Traditional design methods, centered around designer experience, are time-consuming and costly, with limitations in design diversity. This paper presents an automatic generation and beautification model for landscape design based on deep learning to improve efficiency and overcome aesthetic limitations. Experimental results show that NLP technology within the model enhances text processing capabilities and reduces data processing errors, while the residual module CNN improves the quality of auto-generated models. Incorporating point cloud technology enhances the depiction of local details in 3D models. Furthermore, the model supports design optimization and style conversion based on textual descriptions, offering diversified design elements for landscape design automation.

Suggested Citation

  • Lan Lan, 2025. "Automatic Generation and Beautification Technology of Landscape Design Based on Deep Learning," International Journal of Ambient Computing and Intelligence (IJACI), IGI Global Scientific Publishing, vol. 16(1), pages 1-21, January.
    • Handle: RePEc:igg:jaci00:v:16:y:2025:i:1:p:1-21
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