Quantifying Legibility of Indoor Spaces Using Deep Convolutional Neural Networks: Case Studies in Train Stations.
Zhoutong WangQianhui LiangFabio DuarteFan ZhangLouis CharronLenna JohnsenBill Yang CaiCarlo RattiPublished in: CoRR (2019)
Keyphrases
- convolutional neural networks
- case study
- convolutional network
- lessons learned
- real world
- open source
- indoor environments
- development process
- knowledge management
- software development
- data sets
- outdoor environments
- topological spaces
- indoor navigation
- information retrieval
- web based collaborative learning environments
- literature review
- software engineering
- ultra wide band