Published Paper Details:

The community of plant species that are available to mankind is vast, with many species still undiscovered. Unfortunately, numerous plant species are on the edge of extinction, largely due to deforestation driven by human activities, such as industrial expansion and many more. This destruction of natural habitats disturbs the survival of plants, which are important for ecological balance. Preserving plant species is crucial for future generation and public awareness is essential to prevent further loss. This project aims to develop a system that facilitates easy identification of plant species by reducing the dependence on research papers or books. By using Convolutional Neural Networks (CNNs), the system simplifies the recognition of similar-looking plants and enhances awareness about nature. The model's training process had traditional CNN techniques, with measures such as image augmentation to improve accuracy. The existing system achieved an accuracy of 78.85% in identifying plants. While this accuracy is promising, future improvements can be made by exploring alternative CNN architectures or increasing the dataset size. The project had a structured methodology.