Waste and Vehicle Detection Using YOLO

Abstract

Abstract: Automatic detection and classification of objects is an important functionality of image analysis. Due to the nature and size of objects and the varied visual features, it becomes challenging to detect and classify objects in aerial images. Manual detection of objects in these images is very time consuming due to the nature and that data captured in these images. It is desirable to automate the detection of various features or objects from these images. The conventional methods for object classification involve two stages: (i) Identify the regions with object presence in the image and (ii) Classify the objects in the regions. Additionally, detection of objects becomes challenging in presence of complexities in background, size, noise, and distance parameters. This work proposes a customized YOLO to detect and classify different objects such as garbage waste, plastic waste and vehicles in the images.