Dr. Wonsuk "Daniel" Lee

Machine Vision and Precision Agriculture

Dr. Lee is working on developing sensing systems for specialty crops for precision agriculture in Florida. His areas of specialization include: sensing systems, precision agriculture, farm automation, Global Positioning System (GPS), geographic information systems (GIS), near infrared spectroscopy (NIRS), image processing, machine vision, yield monitoring/mapping, variable rate fertilizer application, instrumentation, machinery, and agricultural mechanization. He draws from all these areas to develop solutions for a wide range of agricultural problems.

At the heart of Wonsuk "Daniel" Lee's expertise is the application of sensors, devices which "see" beyond the range of human senses and can deliver information to computers and other devices. Lee's skills also include a wide range of supporting technologies and novel applications, such as autonomous weed control systems, immature green citrus fruit detection, autonomous yield mapping for immature citrus fruit, apple Marssonina blotch (AMB) disease detection, citrus greening disease (Huanglongbing) detection, blueberry fruit detection for yield mapping, citrus black spot (CBS) disease detection, and strawberry flower detection for yield prediction.   

Teaching

  • AOM 3333: Pesticide Application Technology
  • AOM 4434: Precision Agriculture
  • AOM 5435: Advanced Precision Agriculture (Even Years)
  • AOM 5334C: Agricultural Chemical Application Technology

Research

  • Immature green citrus fruit detection from canopy images using various imaging platforms and methods including deep learning technique
  • Postharvest citrus fruit evaluation for packinghouses using machine vision and deep learning
  • Strawberry flower detection for early yield estimation using machine vision
  • Twospotted spider mites detection for strawberry and almonds using a smartphone

Daniel Lee - Professor