Published November 30, 2022
| Version v1
Dataset
Open
Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms - CaseStudy
Authors/Creators
- 1. Department of Biological and Agricultural Engineering, University of California, Davis, USA
- 2. Department of Electronic Engineering, Universidad Tecnica Federico Santa Maria, Valparaiso, Chile
- 3. Department of Engineering, Universidad de los Andes, Santiago, Chile
Description
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.
Files
T1.zip
Files
(48.9 GB)
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