Non-destructive radio frequency sensor methodology for early nematode detection in walnut roots
A novel, non-destructive phenotyping approach that uses a pocket-sized radio frequency tridimensional sensor (Walabot) combined with machine learning algorithms to detect and classify nematode infestation levels in walnu...
Pocket-sized micro-spectrometer for early detection of nematode infestation in walnut trees
A low-cost, pocket-sized near-infrared micro-spectrometer (Scio) combined with machine learning algorithms for early detection of nematode infestation levels in walnut trees. The MESA Lab at Texas A&M has achieved 72% cl...
Intelligent bugs mapping and wiping (ibmw) robotic system for precision pest management in almond orchards
An autonomous robotic system that uses deep learning to detect, map, and surgically treat Navel Orangeworm infestations in almond orchards. The platform combines pheromone-based scouting with variable-height actuators an...
Low-cost RF sensor and machine learning system for early detection of nematode infestation in walnut trees
A pocket-sized radio frequency sensor combined with machine learning algorithms for non-destructive early detection of nematode infestation levels in walnut trees. Current Neural Networks model achieves 82% classificatio...
Ai-driven precision for food safety using advanced image analysis
An AI-driven solution enhances food safety by using machine learning and image analysis to detect critical safety targets. This innovative approach aims to surpass traditional tests in accuracy, providing a scalable and ...
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