Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms - CaseStudy

The dataset "Case Study" consists of image sequences (videos) for apple detection and tracking and its corresponding ground truth. The ground truth is presented in MOT format. This dataset is part of the paper: Villacrés, J., Viscaino, M., Delpiano, J., Vougioukas, S. & Cheein, F. A. (2022). Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms. Computers and Electronics in Agriculture. The article is currently accepted. For a better reference format, please refer to the journal's official website. If you have used the material presented in this data set, please cite the previous article. For more information regarding the dataset, please refer to the paper mentioned below.

本数据集"案例研究（Case Study）"包含用于苹果检测与追踪的图像序列（视频）及其对应的真实标注（ground truth），其真实标注采用MOT格式组织。本数据集隶属于以下论文：Villacrés J、Viscaino M、Delpiano J、Vougioukas S、Cheein F A，2022年发表于《计算机与农业电子学（Computers and Electronics in Agriculture）》的《基于深度学习策略的苹果园产量估算：基于检测的追踪算法对比研究》，该论文目前已被正式录用。若需获取规范的参考文献著录格式，请查阅该期刊的官方网站。若您使用了本数据集包含的相关素材，请引用上述论文。若需了解本数据集的更多详情，请参阅上述论文。