地球资源数据云——数据资源详情
外墙数据集
该数据集《Facades Dataset》主要用于监督学习任务，数据形态以图像为主。 题目说明：CycleGAN's Buildings Facades Dataset 任务类型：图像监督学习。 建议流程：先检查类别分布与脏样本，再用迁移学习（如 ResNet/EfficientNet）建立基线。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：metadata.csv。 Content Facades dataset consists of 506 Building Facades & corresponding Segmentations with split into train and test subsets. Acknowledgements This dataset was obtained from UC Berkeley's official directory of Pix2Pix Datasets. For more details on the dataset refer the related Pix2Pix publication. Work based on the dataset should cite: @inproceedings{isola2017image, title={Image - to - image translation with conditional adversarial networks}, author={Isola, Phillip and Zhu, Jun - Yan and Zhou, Tinghui and Efros, Alexei A}, booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition}, pages={1125 - - 1134}, year={2017} }
摘要概览
该数据集《Facades Dataset》主要用于监督学习任务，数据形态以图像为主。 题目说明：CycleGAN's Buildings Facades Dataset
任务类型：图像监督学习。
建议流程：先检查类别分布与脏样本，再用迁移学习（如 ResNet/EfficientNet）建立基线。
评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。
可用文件：metadata.csv。
Content
Facades dataset consists of 506 Building Facades & corresponding Segmentations with split into train and test subsets.
Acknowledgements
This dataset was obtained from UC Berkeley's official directory of Pix2Pix Datasets. For more details on the dataset refer the related Pix2Pix publication. Work based on the dataset should cite:
@inproceedings{isola2017image, title={Image - to - image translation with conditional adversarial networks}, author={Isola, Phillip and Zhu, Jun - Yan and Zhou, Tinghui and Efros, Alexei A}, booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition}, pages={1125 - - 1134}, year={2017} }