Deep Learning Techniques for Automation and Industrial Applications

10Fruit Leaf Classification Using Transfer Learning for Automation and Industrial Applications

Inam Ul Haq^1*, Gursimran Kaur² and Adil Husain Rather²

¹FEAT, SGT University Gurgaon Delhi, India

²Dept. of CSE, Chandigarh University, Mohali, India

Abstract

Automation and industrial applications require accurate and efficient identification of objects to improve productivity and reduce errors. Fruit leaf classification is one such application that can benefit from machine learning algorithms. However, building a classification model from scratch can be challenging due to the limited availability of labeled data. In this chapter, we present a solution to this problem using transfer learning. We explain the process of using pre-trained models to classify different types of fruits and leaves accurately. We also discuss the advantages of transfer learning for industrial applications, including improved accuracy, reduced training time, and better utilization of resources. We provide code examples and practical guidance for implementing transfer learning using popular deep learning frameworks like TensorFlow. By the end of this chapter, readers will have a good understanding of how to use transfer learning for fruit leaf classification and how it can be applied in industrial settings.

Keywords: Fruits, leaf, classification, transfer learning, automation, industrial applications

10.1 Introduction

10.1.1 Overview of Fruit Leaf Classification and Its Relevance in Automation and Industrial ...