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Ellixson, A
Midtiby, H.S
Boatswain Jacques, A.A
Mochizuki, R
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Authors
Giselsson, T.M
Jørgensen, R.N
Midtiby, H.S
Mochizuki, R
Han-ya, I
Noguchi, N
Su, B
Ishii, K
Goeringer, P
Ellixson, A
Moyle, J
Ellixson, A
Goeringer, P
Griffin, T
Boatswain Jacques, A.A
Adamchuk, V.I
Cloutier, G
Clark, J.J
Miller, C
Boatswain Jacques, A.A
Diallo, A.B
Cambouris, A
Lord, E
Fallon, E
Lord, E
Boatswain Jacques, A.A
Diallo, A.B
Khakbazan, M
Cambouris, A
Topics
Precision Crop Protection
Remote Sensing Applications in Precision Agriculture
Unmanned Aerial Systems
Standards & Data Stewardship
Robotics, Guidance and Automation
Artificial Intelligence (AI) in Agriculture
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2016
2018
2024
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Filter results7 paper(s) found.

1. Estimating the Plant Stem Emerging Points (PSEPS) of Sugar Beets at Early Growth Stages

Successful intra-row mechanical weed control of sugar beet (beta vulgaris) in early growth stages requires precise knowledge about location of crop plants. A computer vision system for locating Plant Stem Emerging Point (PSEP) of sugar beet in early growth stages was developed and tested. The system is based on detection of individual leaves; each leaf location is described by center of mass and petiole location. After leaf detection the true PSEP locations were annotated manually and... T.M. Giselsson, R.N. Jørgensen, H.S. Midtiby

2. Remote Sensing Imagery Based Agricultural Land Pattern Extraction around Miyajimanuma Wetland

This research aimed to extract agricultural land use pattern around the Miyajimanuma wetland, Hokkaido, Japan. By combining the image segmentation technology - watershed transform and image classification technology- particle swarm optimization (PSO)-k-means based minimum distance classifier, a new method for extracting the agricultural land use information based... R. Mochizuki, I. Han-ya, N. Noguchi, B. Su, K. Ishii

3. Privacy Issues and the Use of UASs/Drones in Maryland

 According to the Federal Aviation Administration (FAA), the lawful use of Unmanned Aerial Vehicles (UAV), also known as Unmanned Aircraft Systems (UAS), or more commonly as drones, are currently limited to military, research, and recreational applications. Under the FAA’s view, commercial uses of drones are illegal unless approved by the Federal government.  This will change in the future.  Congress authorized the FAA to develop regulations for the use of drones by private... P. Goeringer, A. Ellixson, J. Moyle

4. Ownership and Protections of Farm Data

Farm data has been a contentious point of debate with respect to ownership rights and impacts when access rights are misappropriated. One of the leading questions farmers ask deals with the protections provided to farm data. Although no specific laws or precedence exists, the possibility of trade secret is examined and ramifications for damages discussed. Farm management examples are provided to emphasize the potential outcomes of each possible recourse for misappropriating farm data. ... A. Ellixson, P. Goeringer, T. Griffin

5. Development of a Machine Vision Yield Monitor for Shallot Onion Harvesters

Crop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer vision have improved the detection, quality assessment and yield estimation processes for crops, including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have not yet been fully developed.... A.A. Boatswain jacques, V.I. Adamchuk, G. Cloutier, J.J. Clark, C. Miller

6. Incorporating Return on Investment for Profit-driven Management Zones

Adopting site-specific management practices such as profitability zones can help to stabilize long-term profit while also favoring the environment. Profitability maps are used to standardize data by converting variables into economic values ($/ha) for different cropping systems within a field. Thus, profitability maps can be used to define management zones from several years of data and show the regions within a field which are more profitable to invest in for production, or those that can be... A.A. Boatswain jacques, A.B. Diallo, A. Cambouris, E. Lord, E. Fallon

7. Deep Learning for Predicting Yield Temporal Stability from Short Crop Rotations

Investigating the temporal stability of yield in management zones is crucial for both producers and researchers, as it helps in mitigating the adverse impacts of unpredictable disruptions and weather events. The diversification of cropping systems is an approach which leads to reduced variability in yield while improving overall field resilience. In this six-year study spanning from 2016 to 2021, we monitored 40 distinct fields owned by 10 producers situated in Quebec, Canada. These... E. Lord, A.A. Boatswain jacques, A.B. Diallo, M. Khakbazan, A. Cambouris