The INRIA Aerial Image Labeling dataset is comprised of 360 RGB tiles of 5000×5000px with a spatial resolution of 30cm/px on 10 cities across the globe. Half of the cities are used for training and are associated to a public ground truth of building foo
数据集内容:城市建筑物检测的遥感图像数据集,标记只有建筑/非建筑两种,且是像素级别,用于语义分割。该数据集于 2017 年由 Inria 发布 数据集功能:语义分割 下载链接: 链接:https://pan.baidu.com/s/1G_HyEFjv6lq1hbT8JaZhPA 提取码:0wa8 彩蛋1: 算法工程师开发重磅福利: (1)算法工程师模型部署利器,算法...
In this paper, we propose an aerial image labeling dataset that covers a wide range of urban settlement appearances, from different geographic locations. Moreover, the cities included in the test set are different from those of the training set. We also experiment with convolutional neural ...
In this paper, we propose an aerial image labeling dataset that covers a wide range of urban settlement appearances, from different geographic locations. Moreover, the cities included in the test set are different from those of the training set. We also experiment with convolutional neural ...
Can Semantic Labeling Methods Generalize to Any City? The Inria Aerial Image Labeling Benchmark 笔记 作者的认为现在遥感领域的算法受限于数据集。 数据集所涵盖的面积比较小,遥感数据和地点关系比较大,所以算法的泛化能力也受到了数据集的限制。 those images cover limited geographic areas and the evaluation pr...
Can Semantic Labeling Methods Generalize to Any City? The Inria Aerial Image Labeling Benchmark 笔记 作者的认为现在遥感领域的算法受限于数据集。 数据集所涵盖的面积比较小,遥感数据和地点关系比较大,所以算法的泛化能力也受到了数据集的限制。 those images cover limited geographic areas and the evaluation pr...
AerialImageDataset arrow_right folder test arrow_right folder train Summary arrow_right folder 539 files lightbulb See what others are saying about this dataset What have you used this dataset for? Learning 0Research 0Application 0LLM Fine-Tuning 0 ...
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Input DATASETS inria-aerial-image-labeling-dataset Tags Scheduled Language Python License This Notebook has been released under the Apache 2.0 open source license. Continue exploring Input1 file arrow_right_alt Output0 files arrow_right_alt Logs19.9 second run - successful arrow_right_alt Comments...