Training deep convolution network with synthetic data for architectural morphological prototype classification

Training deep convolution network with synthetic data for architectural morphological prototype classification

The use of architectural morphological analysis and generative design is an important strategy to interpret current designs and to propose novel ones. Conventional morphological features are defined based on qualitative descriptions or manually selected indicators, which include subjective bias, thu...

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Bibliographic Details
Main Authors: Chenyi Cai, Biao Li
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2021-06-01
Series:Frontiers of Architectural Research
Subjects:
Deep convolution network
Architectural morphology
Prototype classification
Feature extraction
Generative design
Online Access:http://www.sciencedirect.com/science/article/pii/S209526352030087X

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http://www.sciencedirect.com/science/article/pii/S209526352030087X

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