  This thesis is divided into two parts:Part I: Analysis of Fruits, Vegetables,
Cheese and Fish based on Image Processing using Computer Vision and Deep
Learning: A Review. It consists of a comprehensive review of image processing,
computer vision and deep learning techniques applied to carry out analysis of
fruits, vegetables, cheese and fish.This part also serves as a literature
review for Part II.Part II: GuavaNet: A deep neural network architecture for
automatic sensory evaluation to predict degree of acceptability for Guava by a
consumer. This part introduces to an end-to-end deep neural network
architecture that can predict the degree of acceptability by the consumer for a
guava based on sensory evaluation.
