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. &amp; Cheein, F. A. (2022). Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms. <em>Computers and Electronics in Agriculture</em>. 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.本数据集命名为「案例研究（Case Study）」，包含用于苹果检测与跟踪的图像序列（视频）及其对应的基准真值标注（ground truth），该标注采用MOT格式存储。本数据集隶属于以下论文：Villacrés, J., Viscaino, M., Delpiano, J., Vougioukas, S. & Cheein, F. A. (2022). 《基于深度学习策略的苹果果园产量估算：跟踪-检测算法对比》，刊载于《计算机与农业电子学（Computers and Electronics in Agriculture）》，目前该论文已被正式录用。如需获取更规范的参考文献格式，请查阅该期刊的官方网站。若您使用了本数据集的相关素材，请引用上述论文。如需了解本数据集的更多详情，请参阅上述提及的论文。