CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
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id caadria2023_303
authors Hu, Anqi, Yabuki, Nobuyoshi and Fukuda, Tomohiro
year 2023
title Development of a Method for Assessing the View Index of Plants of Interest Using Deep Learning
source Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 585–594
doi https://doi.org/10.52842/conf.caadria.2023.1.585
summary Urban planning often overlooks the diversity of plant species and the perspectives of pedestrians. This study introduces the View Index of Plants of Interest (VIPI) as a new index for evaluating street plants from a pedestrian perspective. VIPI uses image classification and semantic segmentation techniques and was applied to four popular ornamental street plants: cherry trees, maple trees, magnolia trees, and ginkgo trees. The model used achieved a high level of accuracy with a mean intersection over union (mIoU) of 81.06. And the VIPI satisfaction criteria were used to evaluate several cases. The results provide valuable insights for urban planners and policymakers, allowing for a more detailed and accurate evaluation of urban plants from a pedestrian perspective and can guide urban greening actions. Additionally, this study demonstrates the potential of utilizing computer science techniques to inform urban planning and design decisions.
keywords Deep learning, Image classification, Semantic segmentation, View Index of Plants of Interest (VIPI), Street view images, Urban green space
series CAADRIA
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