Data files for Sheehan et al. 2023 'City Scale Traffic Monitoring Using WorldView Satellite Imagery and Deep Learning: A Case Study of Barcelona' DOI: https://doi.org/10.3390/rs15245709

Data files for Sheehan et al. (2023) City Scale Traffic Monitoring Using WorldView Satellite Imagery and Deep Learning: A Case Study of Barcelona. Remote Sensing. 15(24) DOI: https://doi.org/10.3390/rs15245709 Description of contents: xView-YOLOv3_Model6_Barcelona_weights.pt This file contains the pre-trained weights for the xView-YOLOv3 model (model code available here: https://github.com/ultralytics/xview-yolov3). These weights were trained on a manually created training data set of vehicles present in WorldView 2/3 imagery covering the city of Barcelona. The weights relate to Model 6 set up: a single vehicle class (parked, static and moving), RGB imagery, Barcelona training data set derived anchor boxes, 1500 x 1500 pixel sized images and to 1000 epochs.本数据集配套于Sheehan等人(2023)发表于《Remote Sensing》的论文《使用WorldView卫星影像与深度学习开展城市规模交通监测：以巴塞罗那为例》，该论文卷期为15(24)，DOI：https://doi.org/10.3390/rs15245709。 内容描述： xView-YOLOv3_Model6_Barcelona_weights.pt 该文件存储xView-YOLOv3模型（模型代码可通过https://github.com/ultralytics/xview-yolov3 获取）的预训练权重。此类权重基于手动构建的训练数据集训练所得，该数据集涵盖覆盖巴塞罗那市的WorldView 2/3影像中的车辆样本。该权重对应Model 6的配置方案：仅包含单一车辆类别（涵盖停放、静态及行驶状态的车辆）、RGB影像、基于巴塞罗那训练数据集生成的锚框、1500×1500像素尺寸的输入图像，且训练至1000个训练轮次。