PLANT IDENTIFICATION SYSTEM

Abstract

This research focuses on developing a plant recognition system using the deep learning model Inception V3 and deploying it on an iOS platform mobile application using the Swift programming language. To achieve this goal, I utilized the extensive PlantNet-300K dataset containing diverse plant images collected from various sources. The Inception V3 model has proven to be a powerful tool for image recognition and classification. I trained this model on the PlantNet-300K dataset to create a highly accurate plant recognition model. In addition to deploying the model in Swift, I have also built a user-friendly mobile application for plant recognition. This application allows users to capture or upload images of a plant species and returns results regarding the plant's name and detailed information. The results of this research demonstrate the synergy between deep learning technology and mobile applications, making it easy for users to identify and learn about the plant species in their surroundings. This represents a significant step in exploring and preserving the planet's biodiversity. This study contributes to the field of plant recognition and the development of practical applications for environmental education and nature conservation.