A Brief Overview of Deep Learning Methodologies for Analyzing Fruit Image

Deep learning is a groundbreaking advancement in image processing, fruit recognition and categorization, and other fields. This document, in my opinion, is the first of its kind in the food industry. In the past, many machine learning algorithms for fruit classification were presented. With its detection and classification abilities, deep learning can be a powerful engine for providing actionable results in today’s reality. Deep Learning is commonly used to classify items from any image and its properties. The system or application feeds the image of the fruit into the trained model, which extracts and considers features via image processing. The system determines if the fruit is fresh or not based on the input and extracted features. The dataset used for this system is downloaded from Kaggle website. In this model, MobileNet is used as an architecture. The model was developed using TensorFlow and keras.