Image-based Fruit Quality Assessment using Deep Learning Algorithms

In recent years, image based deep learning techniques have gained prominence in various industries, particularly in the field of quality grading. Quality assessment of images plays a pivotal role in various fields including manufacturing, healthcare, agriculture, etc. This paper proposes a model for image-based techniques for quality assessment using deep learning methodologies. It discusses about various deep learning algorithms like Convolution Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Regional Convolution Neural Networks (RCNNs) and Generative Adversarial Networks (GANs) etc. The proposed model makes it easier to work these algorithms that are applied and the Dataset image size is minimized by Dimensionality Reduction, to get the higher accuracy.