Deep Learning with Unsupervised Data Labeling for Weed Detection in Line Crops in UAV Images

Autor: M Dian Bah, Adel Hafiane, Raphael Canals

Publikováno v: Remote Sensing, Vol 10, Iss 11, p 1690 (2018)

In recent years, weeds have been responsible for most agricultural yield losses. To deal with this threat, farmers resort to spraying the fields uniformly with herbicides. This method not only requires huge quantities of herbicides but impacts the en

Externí odkaz: https://doaj.org/article/4d02e8baa9a44a5c97104c9e43bbbe28

Deep Learning Based Classification System for Identifying Weeds Using High-Resolution UAV Imagery

Autor: Raphael Canals, Adel Hafiane, Eric Dericquebourg, M. Dian Bah

Publikováno v: Advances in Intelligent Systems and Computing ISBN: 9783030011765
Computing Conference
Computing Conference, Jul 2018, Londres, United Kingdom. pp.176-187, ⟨10.1007/978-3-030-01177-2_13⟩

In recent years, weeds is responsible for most of the agricultural yield losses. To deal with this problem Omega, farmers resort to spraying pesticides throughout the field. Such method not only requires huge quantities of herbicides but impact envir

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12b373d032b39bc900de34b59549c2ee
https://doi.org/10.1007/978-3-030-01177-2_13

Weeds detection in UAV imagery using SLIC and the hough transform

Autor: Adel Hafiane, Raphael Canals, M. Dian Bah

Publikováno v: 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA)
2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), Nov 2017, Montreal, Canada. pp.1-6, ⟨10.1109/IPTA.2017.8310102⟩
IPTA

Traditional weeds controlling tended to be spraying herbicides in all the fields. Such method not only requires huge quantities of herbicides but impact environment and humans health. In this paper, we propose a new method of crop/weeds discriminatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5538f795fdebc2de5859883cd40922a
https://hal.archives-ouvertes.fr/hal-03299526

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