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Haung, C
Hendrickson, L
Hennessy, P.J
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Authors
Shaver, T
Schmer, M
Irmak, S
Van Donk, S
Wienhold, B
Jin, V
Bereuter, A
Francis, D
Rudnick, D
Ward, N
Hendrickson, L
Ferguson, R.B
Adamchuk, V.I
Hennessy, P.J
Esau, T.J
Schumann, A.W
Farooque, A.A
Zaman, Q.U
White, S.N
Haung, C
Topics
Spatial Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2022
2025
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Filter results3 paper(s) found.

1. Landscape Influences on Soil Nitrogen Supply and Water Holding Capacity for Irrigated Corn

... T. Shaver, M. Schmer, S. Irmak, S. Van donk, B. Wienhold, V. Jin, A. Bereuter, D. Francis, D. Rudnick, N. Ward, L. Hendrickson, R. Ferguson, V.I. Adamchuk

2. Meta Deep Learning Using Minimal Training Images for Weed Classification in Wild Blueberry

Deep learning convolutional neural networks (CNNs) have gained popularity in recent years for their ability to classify images with high levels of accuracy. In agriculture, they have been applied for disease identification, crop growth monitoring, animal behaviour tracking, and weed classification. Datasets traditionally consisting of thousands of images of each desired target are required to train CNNs. A recent survey of Nova Scotia wild blueberry (Vaccinium angustifolium Ait.) fields,... P.J. Hennessy, T.J. Esau, A.W. Schumann, A.A. Farooque, Q.U. Zaman, S.N. White

3. Development of Temperature and Humidity Sensor Calibration Procedure for Multifunctional Orchid Greenhouse Monitoring System

Bacterial soft rot and bacterial brown spot are primary diseases that threaten orchid cultivation, often resulting in substantial economic losses. To address labor shortages and environmental challenges in recent years, the orchid industry is increasingly adopting intelligent disease management systems that combine sensing technologies and data analytics as part of its transformation strategy. The multifunctional monitoring system was developed as an economical, integrating sensors for temperature,... C. Haung