Proceedings

Find matching any: Reset
Stevens, L.J
Stewart, C
Santos, H.P
Add filter to result:
Authors
Benavente, J.C
Cugnasca, C.E
Barros, M.F
Santos, H.P
http://icons.paqinteractive.com/16x16/ac, G
Stevens, L.J
Ferguson, R.B
Franzen, D.W
Kitchen, N.R
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
Sensor Application in Managing In-season Crop Variability
Sensor Application in Managing In-season CropVariability
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2010
2014
2024
Home » Authors » Results

Authors

Filter results3 paper(s) found.

1. Changes Of Data Sampling Procedure To Avoid Energy And Data Losses During Microclimates Monitoring With Wireless Sensor Networks

... J.C. Benavente, C.E. Cugnasca, M.F. Barros, H.P. Santos, G. Http://icons.paqinteractive.com/16x16/ac

2. In-Season Nitrogen Requirement For Maize Using Model And Sensor-Based Recommendation Approaches

Nitrogen (N), an essential element, is often limiting to plant growth.  There is great value in determining the optimum quantity and timing of N application to meet crop needs while minimizing losses.  Low nitrogen use efficiency (NUE) has been attributed to several factors including poor synchrony between N fertilizer and crop demand, unaccounted for spatial variability resulting in varying crop N needs, and temporal variances in crop N needs.  Applying a portion... L.J. Stevens, R.B. Ferguson, D.W. Franzen, N.R. Kitchen

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