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Precision Weed Detection Using Deep Learning
MSc thesis — detecting weeds in crops using deep learning and multispectral UAV imagery
My MSc thesis project completed at Munster Technological University (MTU), supervised by Dr. Yasantha Samarawickrama. Achieved a First Class Honours distinction.
- Developed a deep learning pipeline for automated weed detection in agricultural fields
- Used multispectral UAV (drone) imagery to capture beyond-visible-light crop data
- Trained and evaluated object detection models for precise weed localisation
- Aimed at reducing herbicide usage through targeted, data-driven intervention
- Contributes to the field of precision agriculture and sustainable farming
Combining computer vision, remote sensing, and deep learning to solve a real-world agricultural problem.