Convolutional neural networks for predicting the perceived density of large urban fabrics
Bibliographic Data
| ID | 7150550 |
|---|---|
| Authors | Guy Austern (0000-0003-3377-4814, Technion – Israel Institute of Technology), Roei Yosifof (0000-0002-8943-3712, Technion – Israel Institute of Technology, corresponding author), Tomer Michaeli (0000-0003-0525-8054, Technion – Israel Institute of Technology), Shahar Yadin (Technion – Israel Institute of Technology), Dafna Fisher-Gewirtzman (0000-0003-1260-2896, Technion – Israel Institute of Technology) |
| Year | 2025 |
| Volume | 120 |
| Pages | 102304 |
| Publication date | 2025-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Computers Environment and Urban Systems (JOURNAL) |
| Journal identifiers | ISSN: 0198-9715 • E-ISSN: 1873-7587 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.compenvurbsys.2025.102304 |
| OpenAlex | W4410592895 |
| Language | EN |
| Citations received | 1 |
| References cited | 33 |
Artificial neural network · Cartography · Convolutional neural network · Geography · Computer Science · Impact of Light on Environment and Health · Noise Effects and Management · Urban Design and Spatial Analysis · Artificial Intelligence
Measuring the complexity of urban form and design
ImageNet classification with deep convolutional neural networks
Identifying and Measuring Urban Design Qualities Related to Walkability
To Take Hold of Space
Street design and urban canopy layer climate
Disentangling the Concept of Density
D Visibility Analysis for Evaluating the Attractiveness of Tourism Routes Computed from Social Media Photos
Integrating ‘weighted views’ to quantitative 3D visibility analysis as a predictive tool for perception of space
Hybrid quantitative mesoscale analyses for simulating pedestrians’ visual perceptions
Understanding cities with machine eyes
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |