Jeremy Karouta

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About

Jeremy Karouta is a researcher at the forefront of precision agriculture, specializing in the integration of computer vision and robotics for sustainable crop management. His primary research areas include weed identification using deep learning, site-specific weed management, and agricultural robotics. Karouta’s most impactful contribution is his pioneering work on applying convolutional neural networks (CNNs) to distinguish weeds from crops in maize, sunflower, and potato fields—a study that has garnered 92 citations and directly addresses global concerns over herbicide overuse and food safety. By enabling precise, patch-only herbicide application, his research reduces chemical reliance and supports environmentally friendly farming. Additionally, his work on agricultural robotics, including an introductory topic on robotics in site-specific agriculture, lays foundational knowledge for integrating autonomous systems into farming practices. With a growing citation record, Karouta is recognized for bridging cutting-edge AI with practical agronomic solutions, making him a key figure in the movement toward smarter, more sustainable food production.