Differentiate the Varieties of Plants Using Leaf Images with YOLOv4 - Widjaja, Prya Artha; Ardilla, Veronica Yose; Amelia, Sabrina Yose (JURNAL SISFOTEK GLOBAL, 2024)
There are many types of plant, not all recognized by people. Indonesia has many varieties of plants across the country, from Sabang to Merauke. Often, we find some fruits or plants that grow in different areas called by different names. The goal of this research is to create an application that can recognize plant types from their characteristics. These characteristics can be leaves, fruit, flowers or roots. Current research focuses on distinguishing several types of plants including their varieties using leaf images. It is hoped that apart from being able to determine the mango plant, we can also determine the type of mango, such as manalagi, harum manis, as well as guava and orange. To be able to recognize these types of plants, an object recognition algorithm based on CNN (Convolutional Neural Network) will be used. The algorithm that will be used is YOLO (You Only Look Once) version 4. Method in this research includes data collection, all data was taken using webcam or mobile phone camera. The next step is data preparation and creating a bounding box. Next step is creating model using training data and the last step was compare model with testing data, The result we got is really encouraging with almost 100 percent accuracy. The lowest accuracy is 98 percent for jambu air. This research show us that YOLOv4 can be used to differentiate varieties of plants.