@inproceedings{83f85f7dc7c548ce8ded4b9271b579ca,
title = "Estimation of apple orchard yield using night time imaging",
abstract = "This work investigates the potential of night time imaging for estimating apple orchard yield. Forty two trees were photographed from two sides with cameras mounted at three heights. Each image was analyzed and the results of the six images associated with each tree were summed up to provide a 'tree count'. Fourteen trees were selected randomly in order to calibrate a relationship between the 'tree count' estimate and the actual tree yield. This relationship was then applied to the 'tree count' results of the remaining trees. Although the yield estimate error for a single tree was sometimes large, the overall yield estimate was within 10\% of the actual yield.",
keywords = "Artificial vision, Fruit detection, Image processing",
author = "R. Linker and E. Kelman and O. Cohen",
year = "2015",
doi = "10.3920/978-90-8686-814-8\_66",
language = "الإنجليزيّة",
series = "Precision Agriculture 2015 - Papers Presented at the 10th European Conference on Precision Agriculture, ECPA 2015",
publisher = "Wageningen Academic Publishers",
pages = "533--539",
editor = "Stafford, \{John V.\}",
booktitle = "Precision Agriculture 2015 - Papers Presented at the 10th European Conference on Precision Agriculture, ECPA 2015",
address = "هولندا",
note = "10th European Conference on Precision Agriculture, ECPA 2015 ; Conference date: 12-07-2015 Through 16-07-2015",
}