As an integral part of daily dietary intake, the market demand for fruits and vegetables is
continuously growing. However, traditional methods for assessing the quality of fruits and …

The microwave and millimeter-wave (MMW) imaging technology is gaining increasing
interest for food inspection. It allows for noninvasive, contactless, and fast scanning …

Artificial intelligence (AI) has played a critical role in the enhancement and automation of
global food production and delivery. The assessment of ripeness through microwave images …

Fruit classification is required in many smart-farming and industrial applications. In the
supermarket, a fruit classification system may be used to help cashiers and customer to …

In the food industry, there is a growing demand for cost-effective methods for the inline
inspection of food items able to non-invasively detect small foreign bodies that may have …

The integration of a non-invasive microwave imaging system with a machine learning
algorithm could improve food quality and food safety. In this paper, a S-and C-band …

For improving the quality and profitability of watermelon production, rapid and non-
destructive detection of watermelon ripeness is important. Conventional acoustic and optical …

The simulation of sugar content estimation of sugarcane based on dielectric properties for
microwave imaging technique is proposed in this research. The specific dielectric constant …

This thesis explores two unique ways of using machine learning to improve or facilitate
microwave imaging. The first contribution provides a means of calibration under the …

During the commercial production of watermelons, farmers must swiftly assess fruit ripeness
post-harvest to minimize losses through sorting based on edibility time. This process …