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Full-Text Articles in Computer Engineering
Comparison Of Object Detection And Patch-Based Classification Deep Learning Models On Mid- To Late-Season Weed Detection In Uav Imagery, Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric T. Psota, Amit J. Jhala, Joe D. Luck, Yeyin Shi
Comparison Of Object Detection And Patch-Based Classification Deep Learning Models On Mid- To Late-Season Weed Detection In Uav Imagery, Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric T. Psota, Amit J. Jhala, Joe D. Luck, Yeyin Shi
Biological Systems Engineering: Papers and Publications
Mid- to late-season weeds that escape from the routine early-season weed management threaten agricultural production by creating a large number of seeds for several future growing seasons. Rapid and accurate detection of weed patches in field is the first step of site-specific weed management. In this study, object detection-based convolutional neural network models were trained and evaluated over low-altitude unmanned aerial vehicle (UAV) imagery for mid- to late-season weed detection in soybean fields. The performance of two object detection models, Faster RCNN and the Single Shot Detector (SSD), were evaluated and compared in terms of weed detection performance using mean …
In-Field Fuel Use And Load States Of Agricultural Field Machinery, Santosh Pitla, Joe D. Luck, Jared Werner, Nannan Lin, Scott A. Shearer
In-Field Fuel Use And Load States Of Agricultural Field Machinery, Santosh Pitla, Joe D. Luck, Jared Werner, Nannan Lin, Scott A. Shearer
Biological Systems Engineering: Papers and Publications
The ability to define in-field tractor load states offers the potential to better specify and characterize fuel consumption rate for various field operations. For the same field operation, the tractor experiences diverse load demands and corresponding fuel use rates as it maneuvers through straight passes, turns, suspended operation for adjustments, repair and maintenance, and biomass or other material transfer operations. It is challenging to determine the actual fuel rate and load states of agricultural machinery using force prediction models, and hence, some form of in-field data acquisition capability is required. Controller Area Networks (CAN) available on the current model tractors …