4 citations · 12 across the 5 of their papers we have counts for
5 papers
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes
Ming Zhong, Dehao Liu, Raymundo Arroyave +1
This paper proposes a semi-supervised methodology for training physics-informed machine learning methods. This includes self-training of physics-informed neural networks and physic…
Characteristics-Informed Neural Networks for Forward and Inverse Hyperbolic Problems
Ulisses Braga-Neto
We propose characteristics-informed neural networks (CINN), a simple and efficient machine learning approach for solving forward and inverse problems involving hyperbolic PDEs. Lik…
Assessing The Performance of YOLOv5 Algorithm for Detecting Volunteer Cotton Plants in Corn Fields at Three Different Growth Stages
Pappu Kumar Yadav, J. Alex Thomasson, Stephen W. Searcy +9
The boll weevil (Anthonomus grandis L.) is a serious pest that primarily feeds on cotton plants. In places like Lower Rio Grande Valley of Texas, due to sub-tropical climatic condi…
Computer Vision for Volunteer Cotton Detection in a Corn Field with UAS Remote Sensing Imagery and Spot Spray Applications
Pappu Kumar Yadav, J. Alex Thomasson, Stephen W. Searcy +9
To control boll weevil (Anthonomus grandis L.) pest re-infestation in cotton fields, the current practices of volunteer cotton (VC) (Gossypium hirsutum L.) plant detection in field…
Detecting Volunteer Cotton Plants in a Corn Field with Deep Learning on UAV Remote-Sensing Imagery
Pappu Kumar Yadav, J. Alex Thomasson, Robert Hardin +9
The cotton boll weevil, Anthonomus grandis Boheman is a serious pest to the U.S. cotton industry that has cost more than 16 billion USD in damages since it entered the United State…