A robust plant localization and identification system for precision farming: The effects of uncontrolled illumination on an end-to-end deep-learning plant detection algorithm

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Abstract

In this research, we investigated the robustness of an end-to-end deep-learning plant detection algorithm with respect to influences from uncontrolled illumination. For this research, we acquired two datasets, one containing images of plants taken under controlled illumination and one dataset with images acquired under uncontrolled illumination. We trained and evaluated the YOLOv3 object detector on both datasets. The object detector scored a mean Average Precision of 0.96 on controlled illumination conditions and 0.90 on the uncontrolled illumination conditions. This difference in performance is significant.

Original languageEnglish
Pages (from-to)383-390
Number of pages8
JournalVDI Berichte
Volume2019
Issue number2361
Publication statusPublished - 2019
Event77th International Conference on Agricultural Engineering, LAND.TECHNIK AgEng 2019 - Hanover, Germany
Duration: 8 Nov 20199 Nov 2019

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