Sorting of Fruits/Vegetables using Convolutional Neural Network: A Review

This study presents a review of recent research works using convolutional neural networks (CNNs) for sorting fruits and vegetables. The authors discuss about the various approaches that have been proposed, including image-based methods and sensor-based methods, and evaluate their performance in terms of accuracy, speed, and robustness. The paper also highlights the challenges that remain in this area of research, such as handling variations in lighting and texture, and discusses potential future directions for improving the performance of CNN-based fruit and vegetable sorting systems. Overall, the paper provides a comprehensive overview of the current state of the art in this field and offers insights for researchers and practitioners working on developing automated fruit and vegetable sorting systems.