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Wang, D.R
Sun, X
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Authors
Rai, N
Zhang, Y
Quanbeck, J
Christensen, A
Sun, X
Pathak, H
Warren, C.J
Buckmaster, D
Wang, D.R
Topics
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Type
Oral
Year
2022
2024
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1. Spotweeds: a Multiclass UASs Acquired Weed Image Dataset to Facilitate Site-specific Aerial Spraying Application Using Deep Learning

Unmanned aerial systems (UASs)-based spot spraying application is considered a boon in Precision Agriculture (PA). Because of spot spraying, the amount of herbicide usage has reduced significantly resulting in less water contamination or crop plant injury. In the last demi-decade, Deep Learning (DL) has displayed tremendous potential to accomplish the task of identifying weeds for spot spraying application. Also, most of the ground-based weed management technologies have relied on DL techniques... N. Rai, Y. Zhang, J. Quanbeck, A. Christensen, X. Sun

2. Advancing Adaptive Agricultural Strategies: Unraveling Impacts of Climate Change and Soils on Corn Productivity Using APSIM

With unprecedented challenges to achieve sustainable crop productivity under climate change and dynamic soil conditions, adaptive management strategies are required for optimizing cropping systems. Using sensors, cropping systems can be continuously monitored and the data collected by them can be analyzed for making informed adaptive management decisions to enhance productivity and environmental sustainability. But sensors can only tell the past and decisions bring implications into the future.... H. Pathak, C.J. Warren, D. Buckmaster, D.R. Wang