5 datasets found
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Federal
Data and Code from: Smart vision-based monitoring system for AI-driven moth population estimation using camera-equipped trap imaging
Department of Agriculture —
Real-time, image-based monitoring for stored product insect pests could increase timely treatments and protection for postharvest products throughout the supply... -
Federal
Data and code from: AI-based image profiling and detection for the beetle byte quintet using Vision Transformer (ViT) in advanced stored product infestation monitoring
Department of Agriculture —
Managing beetles that infest stored products is crucial for reducing losses in harvest supply chains and improving food security and safety. Successful pest... -
Federal
Data and code from: <i>Tribolium cas</i><i>taneum </i>and <i>T. confusum</i> are preferentially attracted to decomposing wood, their putative historical host
Department of Agriculture —
Tribolium castaneum and T. confusum are important stored grain pests, yet little is known about their life history outside the stored grain environment. Like related... -
Federal
TEAMER: Experimental Validation and Analysis of Deep Reinforcement Learning Control for Wave Energy Converters
Department of Energy —
Through this TEAMER project, Michigan Technological University (MTU) collaborated with Oregon State University (OSU) to test the performance of a Deep Reinforcement... -
Federal
Data and Code From: AI-Based bread quality assessment using image processing techniques and the developed BQe-CNN
Department of Agriculture —
Ensuring consistent bread quality is vital for maintaining industry standards, reducing waste, and keeping consumer satisfaction. Traditional methods of bread quality...
5 datasets found