Proceedings :: International Society of Precision Agriculture

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Potlapally, A

Pantel, M

Pfeiffer, J

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Authors

Bedard, F

Reichert, G

Dobbins, R

Pantel, M

Smith, J

Pfeiffer, J

Gandorfer, M

Ettema, J.F

Waltz, L

Khanal, S

Katari, S

Hong, C

Anup, A

Colbert, J

Potlapally, A

Dill, T

Porter, C

Engle, J

Stewart, C

Subramoni, H

Machiraju, R

Ortez, O

Lindsey, L

Nandi, A

Topics

Remote Sensing Applications in Precision Agriculture

Precision Dairy and Livestock Management

Artificial Intelligence (AI) in Agriculture

Type

Oral

Year

2010

2018

2024

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Filter results3 paper(s) found.
1. Timely, Objective, And Accurate Crop Area Estimations And Mapping Using Remote Sensing And Statistical Methods For The Province Of Prince Edward Island, Canada The provincial government of Prince Edward Island, Canada, required timely, objective, and accurate annual crop area statistics and mapping for 2006 to 2008. Consequently, Statistics Canada conducted a survey incorporating medium- resolution satellite imagery (10 to 30 m) and statistical survey methods. The objective was to produce crop area estimates with a coefficient of variation (CV) as a measure of accuracy, and to produce maps showing the distribution and location of different crops and... F. Bedard, G. Reichert, R. Dobbins, M. Pantel, J. Smith Download paper
2. Economic Evaluation of Automatic Heat Detection Systems in Dairy Farming Although heat detection makes a relevant contribution to good reproduction performance of dairy cattle, available studies on the economic evaluations of automatic heat detection systems are limited. Therefore, the objective of this article is to provide an economic evaluation of using automatic heat detection. The effect of different heat detection rates on gross margin is modelled with SimHerd (SimHerd A/S, Denmark). The analysis considers all additional investment costs in automatic heat detection.... J. Pfeiffer, M. Gandorfer, J.F. Ettema Download paper
3. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and Vision Advancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi Download paper

Filter results3 paper(s) found.

1. Timely, Objective, And Accurate Crop Area Estimations And Mapping Using Remote Sensing And Statistical Methods For The Province Of Prince Edward Island, Canada

The provincial government of Prince Edward Island, Canada, required timely, objective, and accurate annual crop area statistics and mapping for 2006 to 2008. Consequently, Statistics Canada conducted a survey incorporating medium- resolution satellite imagery (10 to 30 m) and statistical survey methods. The objective was to produce crop area estimates with a coefficient of variation (CV) as a measure of accuracy, and to produce maps showing the distribution and location of different crops and... F. Bedard, G. Reichert, R. Dobbins, M. Pantel, J. Smith

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2. Economic Evaluation of Automatic Heat Detection Systems in Dairy Farming

Although heat detection makes a relevant contribution to good reproduction performance of dairy cattle, available studies on the economic evaluations of automatic heat detection systems are limited. Therefore, the objective of this article is to provide an economic evaluation of using automatic heat detection. The effect of different heat detection rates on gross margin is modelled with SimHerd (SimHerd A/S, Denmark). The analysis considers all additional investment costs in automatic heat detection.... J. Pfeiffer, M. Gandorfer, J.F. Ettema

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3. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and Vision

Advancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi

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