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Nielsen, M.R
Nielsen, M.B
Yang, Q
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Authors
Bertelsen, M.G
Nielsen, K
Nielsen, M.R
Nielsen, K
Nielsen, M.R
Zhao, T
Chen, Y
Franzen, J
Gonzalez, J
Yang, Q
Zhao, T
Cisneros, M
Chen, Y
Yang, Q
Zhang, Y
Rydahl, P
Boejer, O
Jensen, N
Hartmann, B
Jorgensen, R
Soerensen, M
Andersen, P
Paz, L
Nielsen, M.B
Topics
Proximal Sensing in Precision Agriculture
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Precision Crop Protection
Type
Oral
Year
2014
2016
2022
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Filter results5 paper(s) found.

1. A Method For Sampling Scab Spots On Apple Leaves In The Orchard Using Machine Vision

Introduction One of the largest threats in apple orchards is scab. Current procedures involve models based on weather data that predict the likelihood of scab attacks. In case of alarm the orchard is sprayed with preventive pesticides and this typically happens 25-30 times per season. The scab attacks the leaves and stays on fallen leaves that reinfect the trees with rainwater, making it an advantage to include a-priori knowledge on previous... M.G. Bertelsen, K. Nielsen, M.R. Nielsen

2. Fusion Of Multi Exposure Stereo Images And Thermography For Obstacle Detection On Agricultural Vehicles

Introduction Over the years agricultural vehicles become increasingly automated with trajectory row tracking and master-slave vehicle configurations, and autoguided vehicles. Safety is an important aspect. Auto guided vehicles exist in industry, where the surroundings are semistructured and flat. Sopme cars have collision sensors. But in agriculture the ground is not flat.  The vehicles are meant to be driven into crops, and there are certain paths... K. Nielsen, M.R. Nielsen

3. Melon Classification and Segementation Using Low Cost Remote Sensing Data Drones

Object recognition represents currently one of the most developing and challenging areas of the Computer Vision. This work presents a systematic study of various relevant parameters and approaches allowing semi-automatic or automatic object detection, applied onto a study case of melons on the field to be counted. In addition it is of a cardinal interest to obtain the quantitative information about performance of the algorithm in terms of metrics the suitability whereof is determined by the final... T. Zhao, Y. Chen, J. Franzen, J. Gonzalez, Q. Yang

4. Almond Canopy Detection and Segmentation Using Remote Sensing Data Drones

The development of Unmanned Aerial System (UAV) makes it possible to take high resolution images of trees easily. These images could help better manage the orchard. However, more research is necessary to extract useful information from these images. For example, irrigation schedule and yield prediction both rely on accurate measurement of canopy size. In this paper, a workflow is proposed to count trees and measure the canopy size of each individual tree. The performances of three different methods... T. Zhao, M. Cisneros, Y. Chen, Q. Yang, Y. Zhang

5. Economic Potential of RoboWeedMaps - Use of Deep Learning for Production of Weed Maps and Herbicide Application Maps

In Denmark, a new IPM ‘product chain’ has been constructed, which starts with systematic photographing of fields and ends up with field- or site-specific herbicide application. A special high-speed camera, mounted on an ATV took sufficiently good pictures of small weed plants, while driving up to 50 km/h. Pictures were uploaded to the RoboWeedMaps online platform, where appointed internal- and external persons with agro-botanical experience executed ‘virtual field inspection’... P. Rydahl, O. Boejer, N. Jensen, B. Hartmann, R. Jorgensen, M. Soerensen, P. Andersen, L. Paz, M.B. Nielsen