A Comprehensive Study on Plant Classification Using Machine Learning Models

Plant classification is a critical task with many practical applications, including agriculture, environmental management, and biodiversity conservation. Traditional methods of plant classification can be time-consuming and require considerable expertise. In recent years, machine learning models have shown great promise for automating the plant classification process. This paper provides a comprehensive survey of the existing literature on plant classification using machine learning models. This paper discusses the most commonly used machine learning algorithms, feature extraction and selection techniques, publicly available datasets, and evaluation metrics, also examines the potential applications of plant classification using machine learning models, and identifies the major challenges and future directions for research in this field. Overall, this review highlights the importance of machine learning methods for plant classification and their potential to revolutionize this field in the future.