RoboWeedSupport - Detection of weed locations in leaf occluded cereal crops using a fully convolutional neural network-Reference-Cited by-同舟云学术

RoboWeedSupport - Detection of weed locations in leaf occluded cereal crops using a fully convolutional neural network

Published:2017 Issue:2 Volume:8 Page:842-847
ISSN:2040-4700
Container-title:Advances in Animal Biosciences
language:en
Short-container-title:Advances in Animal Biosciences

Author:

Dyrmann M.,Jørgensen R.N.,Midtiby H.S.

Publisher

Elsevier BV

Reference15 articles.

1. An effective classification system for separating sugar beets and weeds for precision farming applications

2. Dyrmann M , Karstoft H and Midtiby HS 2016. “Plant Species Classification Using Deep Convolutional Neural Network.” Biosystems Engineering.

3. Laursen MS , Jørgensen RN , Dyrmann M and Poulsen RN 2016. “RoboWeedSupport - Sub millimeter weed image acquisition in cereal crops with speeds up till 50 km/h”, European Conference of Precision Agriculture 2016.

4. RoboWeedSupport - Presentation of a cloud based system bridging the gap between in-field weed inspections and decision support systems;Rydahl;European Conference of Precision Agriculture 2016,2016

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