首个针对青核桃的无人机遥感数据集，助力精准农业算法研究。
WalnutData: A UAV Remote Sensing Dataset of Green Walnuts and Model Evaluation
- 用无人机采集8个样本地块数据，构建高粒度青核桃数据集
- 含30,240张图像、706,208个实例，分4类光照与遮挡场景
- 提供主流算法基准评估，适合农业视觉与无人机应用研究者
无人机技术日益成熟，为智慧农业与精准监测提供强大支持。当前农业计算机视觉领域尚无青核桃相关数据集。为此，我们利用无人机采集8个核桃样本地块的遥感数据，考虑到青核桃受多种光照条件和遮挡影响，构建了具有更高目标特征粒度的大规模数据集 WalnutData。该数据集共包含30,240张图像和706,208个实例，涵盖4类目标：正面光照且无遮挡（A1）、背光且无遮挡（A2）、正面光照且遮挡（B1）、背光且遮挡（B2）。随后，我们在 WalnutData 上评估了多种主流算法，并将其结果作为基线标准。数据集及所有评估结果可于 https://github.com/1wuming/WalnutData 获取。
原文摘要 · Abstract (English)
The UAV technology is gradually maturing and can provide extremely powerful support for smart agriculture and precise monitoring. Currently, there is no dataset related to green walnuts in the field of agricultural computer vision. Thus, in order to promote the algorithm design in the field of agricultural computer vision, we used UAV to collect remote-sensing data from 8 walnut sample plots. Considering that green walnuts are subject to various lighting conditions and occlusion, we constructed a large-scale dataset with a higher-granularity of target features - WalnutData. This dataset contains a total of 30,240 images and 706,208 instances, and there are 4 target categories: being illuminated by frontal light and unoccluded (A1), being backlit and unoccluded (A2), being illuminated by frontal light and occluded (B1), and being backlit and occluded (B2). Subsequently, we evaluated many mainstream algorithms on WalnutData and used these evaluation results as the baseline standard. The dataset and all evaluation results can be obtained at https://github.com/1wuming/WalnutData.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。