Published Paper Details:

Abstract Quality assessment of fruits plays a key part in the global economy's agricultural sector. In recent years, it has been shown that fruits are affected by different diseases, which can lead to widespread economic failure in the agricultural industry. Traditional manual visual grading of fruits could be more accurate, making it difficult for agribusinesses to assess quality efficiently. The quality and safety of food is an important issue to the whole society, since it is at the basis of human health, social development and stability. Ensuring food quality and safety is a complex process, and all stages of food processing must be considered, from cultivating, harvesting and storage to preparation and consumption. However, these processes are often labor-intensive. Nowadays, the development of machine vision can greatly assist researchers and industries in improving the efficiency of food processing. Computer vision based food recognition is a technology that uses machine learning algorithms to identify and classify different types of food in digital images or videos. This technology has a wide range of applications, including dietary analysis and tracking, nutrition labeling, and food safety. One of the key benefits of food recognition is the ability to automatically extract nutritional information from food images.