Authors : Jay Khapare , Dimple Kumar , Komal Bhende, Aarya Babhulkar, Prof.Roshan Kotkondawar
DOI : 10.46335/IJIES.2024.9.8.14
Abstract: Identification of medicinal plants or leaves plays an important role in many fields such as medicine, agriculture and conservation. The routine process of plant identification is often time consuming and requires botanical knowledge. In recent years, deep learning techniques have emerged as a promising method to study these processes. This article provides a comprehensive review of recent research on the use of machine learning techniques to identify leaf patterns. We discuss the problems with traditional methods and how machine learning can solve these problems. We also examine various ML algorithms and techniques used in the recognition process, such as Convolutional Neural Networks (CNN), Resnet50V20. We also highlight the importance of data in training ML models and discuss strategies for data collection and development. We also analyze the images used to evaluate the effectiveness of ML models in page analysis. Finally, we discuss future research directions and potential applications of machine learning in the identification of medicinal plants.
