Abstract
Since the beginning of agriculture there have been all kinds of pests that have reduced crop production. Throughout this time, different methods of scarring have been used to control pests and increase crop yields. In the same way today, pest control has other goals compared to before, one of the main objectives is the integrity of the animal to be treated, this is intended to preserve the ecosystem balance and the protection of the environment in which it develops. Pest detection today has become one of the most important factors to consider in this maintenance area in agricultural and fruit fields. This document is mainly focused on the detection of flocks of birds that are considered as pests in apple orchards, in Cuauhtémoc Chihuahua, although, the same method can be applied for different production areas.
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Garcia, H. et al. (2020). Use of Deep Learning for Bird Detection to Reduction of Collateral Damage in Fruit Fields. In: Hassanien, AE., Azar, A., Gaber, T., Oliva, D., Tolba, F. (eds) Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020). AICV 2020. Advances in Intelligent Systems and Computing, vol 1153. Springer, Cham. https://doi.org/10.1007/978-3-030-44289-7_36
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DOI: https://doi.org/10.1007/978-3-030-44289-7_36
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