Systematic Literature Review of Pedestrian Detection using the YOLO Algorithm

Technology is developing so rapidly at this time. Every time various latest and cutting-edge technologies in various fields transmit life. One of them is in the field of object detection. As technology develops, the need for object detection systems becomes very strong. Object detection or object detection is the lifeblood of Computer Vision and Image Processing. There are 4 main focuses in Computer Vision, namely Recognition, Visual Tracking (visual tracking), Semantic Segmentation (semantic segmentation) and Image Restoration (image restoration). To be able to do these four things, we need an algorithm that can effectively be applied to detect objects, especially pedestrians, so YOLO was chosen as the answer. YOLO is one of several algorithms that are often used in Machine Learning. You Only Live Once or better known as YOLO is a very well-known and widely used algorithm. YOLO is a specific algorithm for object detection. In recent years, the YOLO Algorithm has shown interesting results in various areas of object detection, both large-scale and special, has solved many problems in the field of object detection in general, the detection of license plates of vehicles, pedestrians, etc. Through this systematic literature review, it is hoped that it will be able to provide enlightenment for the development of Object Detection science.