Non-destructive Infield Quality Estimation of Strawberries using Deep Architectures

Strawberries have a short shelf-life time and thus need to be harvested at the right time to reduce waste. To this end, information about quality attributes is useful. Recently, many computer vision methods have been proposed. Most literature analyzes postharvest, which means that strawberries can only be analyzed after harvesting. As a result,...

The Effect of Color Spaces and Spectra on a Strawberry Prediction Model

The purpose of this research is to reduce food waste by monitoring the ripening process of strawberries in order to optimize the harvesting time. To improve the moment of harvest, we need to know the ripeness of a strawberry. Using data from different color ranges and spaces we should be able to predict the ripeness of a strawberry on a 1-10...

Detecting strawberries using different Convolutional Neural Networks

This paper tries to combat the food waste of strawberries during the harvesting steps.<br/>An automatic pipeline must be established to combat this food waste.<br/>One of the steps needed in this pipeline is detecting strawberries in images.<br/>Therefore, this paper aims to find out which Convolutional Neural Network (CNN) can be best used to...

Identifying and designing a new application for the Hortimotion robot

Hortimotion is a startup company, developing automated solutions for horticultural environments. With the robot initially being developed around the cleanligh UV light, this graduation project focussed on identifying and designing a new application for the robot. This because the focus had shifted away from the cleanlight UV light, for good...