Precision Phenotyping Using Low-Cost Drones & Deep Learning

During the Summer of 2017, I used my UAV experience to design, build, and test a low-cost data collection platform for deep learning based phenotyping and disease detection. The project was specifically targeted towards detecting lesions caused by a fungal infection called Northern Leaf Blight (NLB) on corn plants. Harvest losses caused by NLB were estimated at $1.9 billion in 2015 alone. In our work, we identified the specific qualities needed to build a successful data collection platform. To guarantee a high disease-detection accuracy from our deep learning model, our autonomous drone platform had to collect blur-free image data with a high pixel-density. We presented our findings at the Columbia Technology Ventures symposium (see video above).