由于生理特征，女性在城市公共空间中处于不利地位。然而，针对女性视角下的安全感知评估及其影响因素的研究仍较为有限。尽管机器学习技术取得进展，但高效且准确地量化安全感知仍具挑战性。本研究以武汉市为例，提出一种结合RankNet与Gist特征的方法，用于对女性街道安全感知进行排序。采用全卷积网络-8s（FCN-8s）提取建成环境特征，并运用普通最小二乘法（OLS）回归与地理加权回归（GWR）分析这些特征与女性安全感知之间的关系。研究结果揭示以下关键发现：（1）武汉市的安全感知排名与其多中心城市格局相吻合，中心城区存在显著差异；（2）建成环境特征显著影响女性安全感知，其中天际线视域因子（Sky View Factor）、绿视率（Green View Index）和道路可视性为最具影响力的因素，天际线视域因子对安全感知具有正向影响，其余因素则呈负向影响；（3）建成环境特征对安全感知的影响具有空间异质性，可将研究区域划分为三类：天空与道路主导区、建筑主导区以及绿化主导区。最后，本研究提出了构建更安全、更适于女性的都市公共空间的针对性策略。

Women face disadvantages in urban public spaces due to their physiological characteristics. However, limited attention has been given to assessing safety perceptions from a female perspective and identifying the factors that influence these perceptions. Despite advancements in machine learning (ML) techniques, efficiently and accurately quantifying safety perceptions remains a challenge. This study, using Wuhan as a case study, proposes a method for ranking street safety perceptions for women by combining RankNet with Gist features. Fully Convolutional Network-8s (FCN-8s) was employed to extract built environment features, while Ordinary Least Squares (OLS) regression and Geographically Weighted Regression (GWR) were used to explore the relationship between these features and women’s safety perceptions. The results reveal the following key findings: (1) The safety perception rankings in Wuhan align with its multi-center urban pattern, with significant differences observed in the central area. (2) Built environment features significantly influence women’s safety perceptions, with the Sky View Factor, Green View Index, and Roadway Visibility identified as the most impactful factors. The Sky View Factor has a positive effect on safety perceptions, whereas the other factors exhibit negative effects. (3) The influence of built environment features on safety perceptions varies spatially, allowing the study area to be classified into three types: sky- and road-dominant, building-dominant, and greenery-dominant regions. Finally, this study proposes targeted strategies for creating safer and more female-friendly urban public spaces.