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Mathew, J
Arikapudi, R
Jørgensen, R.N
Tharzeen, A
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Authors
Midtiby, H.S
Jørgensen, R.N
Krüger, N
Laursen, M.S
Bøgild, A
Nielsen, S.H
Jacobsen, N.J
Jager-Hansen, C
Jørgensen, R.N
Jensen, K
Jørgensen, O.J
Vougioukas, S.G
Jimenez, F.J
Khosro Anjom, F
Elkins, R
Ingels, C
Arikapudi, R
Das, A
Flores, P
Zhang , Z
Friskop, A
Mathew, J
Agarwal, D
Tharzeen, A
Natarajan, B
Topics
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Food Security and Precision Agriculture
Engineering Technologies and Advances
Applications of Unmanned Aerial Systems
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2014
2022
2024
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Filter results5 paper(s) found.

1. Validation of Modicovi - Monocot and Dicot Coverage Ratio Vision Based Method for Real Time Estimation Canopy Coverage Ratio between Cereal Crops and Dicotyledon Weeds

... H.S. Midtiby, R.N. Jørgensen, N. Krüger, M.S. Laursen

2. A Low Cost, Modular Robotics Tool Carrier for Precision Agriculture Research

Current research within agricultural crop production focus on using autonomous robot technology to optimize the production efficiency, enhance sustainability and minimize tedious, monotonous and wearing tasks. But progress is slow partly... A. Bøgild, S.H. Nielsen, N.J. Jacobsen, C.L. Jaeger-hansen, R.N. Jørgensen, K. Jensen, O.J. Jørgensen

3. Design, Error Characterization And Testing Of A System To Measure Locations Of Fruits In Tree Canopies

Mapping the variability of fruit size and quality within tree canopies in commercial orchards is an important tool for implementing precision horticulture. To do so at a reasonably fast rate requires localization technologies that offer sufficient speed and accuracy, at a range long enough to cover entire trees – or several trees at a time. Existing approaches for measuring fruit locations include: manual (centimeter accuracy and measurement time in the order of minutes per... S.G. Vougioukas, F.J. Jimenez, F. Khosro anjom, R. Elkins, C. Ingels, R. Arikapudi

4. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV Imagery

Goss Wilt has become a common disease in corn fields in North Dakota.  It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of unmanned... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew

5. Active Learning-based Measurements Prediction in Sparsely Observed Agricultural Fields

The sustainability of farming methods relies on the quality of soil health. Rich soil supplies vital nutrients to plants. The soil structure and aggregation possess crucial physical attributes that facilitate the infiltration of water and air, as well as enable roots to explore. Long-term and extensive monitoring of soil data is crucial for obtaining important information into the water dynamics of the land surface. Soil moisture dynamics play a critical role in the hydrothermal process that occurs... D. Agarwal, A. Tharzeen, B. Natarajan