"Quantifying Legibility of Indoor Spaces Using Deep Convolutional Neural ..."

Zhoutong Wang et al. (2019)

> Home

Details and statistics

DOI: —

access: open

type: Informal or Other Publication

metadata version: 2022-10-19

- view
  - electronic edition @ arxiv.org (open access)
- export record
  dblp key:
  - journals/corr/abs-1901-10553
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/corr/abs-1901-10553
Zhoutong Wang, Qianhui Liang, Fabio Duarte, Fan Zhang, Louis Charron, Lenna Johnsen, Bill Yang Cai, Carlo Ratti:
Quantifying Legibility of Indoor Spaces Using Deep Convolutional Neural Networks: Case Studies in Train Stations. CoRR abs/1901.10553 (2019)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.