Architectural Factors Detection from Plan by Deep Learning Framework

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WEB OF SCIENCE

4
Citations

SCOPUS

4

초록

This study presents the basics of emotion - based technology system by detecting various elements of architectural drawings as the first step of objectification of aesthetic characteristic and design tendency reflecting architect 's design intention by using example - based machine learning. With the development of technology, new software has been introduced in the field of architectural design, which is able to solve the concerns of environmental values and solve problems, and generalize environmental analysis. However, the aesthetic value compatible with it does not meet the needs of the same context due to social recognition and technical limitations. The purpose of this study is to quantify the scope of subjective judgment of architectural design and to objectify it. In other words, the intention of the designer is the process of confirming the inherent attributes of the result of the expressed architectural design.

키워드

aesthetic value; deep learning; object detection; convolutional neural net
제목
Architectural Factors Detection from Plan by Deep Learning Framework
저자
Park, Jinho; Yoon, Doyoung; Lee, Woo-Hyoung
DOI
10.14257/ijgdc.2018.11.1.06
발행일
2018-01
유형
Article
저널명
INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING
권
11
호
1
페이지
57 ~ 64