DESIGN AND IMPLEMENTATION OF FRUITS AND VEGETABLE RECOGNITION SYSTEM USING CONVOLUTIONAL NEURAL NETWORK (CNN)
Abstract
This project presents the development of a Recognition System for Fruits and Vegetables using Convolutional Neural Networks (CNNs). The system leverages deep learning techniques to accurately identify and classify various fruits and vegetables from images. The recognition process involves training a CNN on a large dataset consisting of labeled images of different produce items. The architecture of the CNN is designed to efficiently process and extract relevant features from images, enabling the system to distinguish between different categories with high accuracy. The implementation aims to enhance automation in areas such as agriculture, food processing, and retail, where quick and precise identification of fruits and vegetables is essential. Performance evaluation demonstrates the system’s capability to handle diverse image conditions and varying lighting, making it a robust solution for real-time applications.
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