Snail Detection using YOLO
Analyn N. Yumang, Justin A. Bautista, Juan Ricardo I. Borreta
Abstract
Snails are distinct mollusks with a notable feature of their spiral shells. They are detected and monitored with specific intentions such as ecosystem management or pest detection in agriculture. Despite much research on computer vision, snail detection and its possible applications have yet to be studied. Using a detection model based on Tiny-YOLOv4 and a dataset of snail images was used to train a model, we created a detection system with a Raspberry Pi. The results showed images with labeled bounding boxes around the snails. The snail detection model showed an accuracy of 92.89%, an acceptable outcome with potential for future works on snail detection and small object detection.