Detecting tomato diseases using hyper-spectral imaging and deep learning
Sensor technology for greenhouses is a subject which is still in its infancy. Although a wide variety of crop and environment parameters are being collected, it requires the skilled eye of the cultivator to properly analyze and control the quality.
The interuniversity (of applied sciences) project SCOUT has the primary goal to automate, integrate and to control the product quality parameters of a tomato greenhouse.
One of the tasks is to detect tomato diseases at an early stage. Gall mite, invisible to the naked eye, causes great damage to the tomato plants in a greenhouse. It is hard to detect and a plant cannot be saved anymore once it is noticed.
Using technology such as hyper-spectral imaging and deep learning this quality parameter can be detected at an early stage. This presentation will guide you through the process.Download slides