Plant infestation diagnosis using a high-resolution sensory system for detection of biogenic signals

Pests and diseases are major problem that growers face with plants. Ecoation Innovative Solutions Inc. (EIS) is proposing a solution to this problem that turns to plants as reliable source of information about their own health and well-being. EIS will provide data from different sensory measurements for clean and infested plants. We intend to use recent advances in machine learning to build a model that automatically diagnose the plants from these measurements. The intern will work on developing the model and adapting it for different crops and cultivating environments. Moreover, he will focus on advancing research into transfer learning by focusing on more effective training strategies.

Faculty Supervisor:

Mark Schmidt

Student:

Mohamed Ahmed

Partner:

Ecoation Innovative Solutions Inc

Discipline:

Computer science

Sector:

Agriculture

University:

University of British Columbia