Work

Quantifying uncertainty in deep learning models for urban safety perception: An MC Dropout approach

Year: 2026

Type: article

Source: Environment and Planning B Urban Analytics and City Science

DOI: 10.1177/23998083261504070

Authors: Vicente Larraín, Billy Peralta, Hans Lobel

Institutions: Pontificia Universidad Católica de Chile, Universidad Andrés Bello

Language: English

Topic: Adversarial Robustness in Machine Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: closed

Funder: Agencia Nacional de Investigación y Desarrollo

OpenAlex ID: W7225335274

FWCI:

Cites: 12

Cited by:

Related to: 10