Small-object detection based on YOLOv5 in autonomous driving systems

• We discuss the benefits of accurate detection of small objects like traffic signs and traffic lights in autonomous driving . • We analyze the practical limitations of the original YOLOv5 structure. • We propose novel architectural refinements to the same for improving its performance in the detection of small objects. • We perform extensive experimentation over the BDD100K, TT100K, and DTLD datasets. • We further evaluate the generalization ability of the proposed iS-YOLOv5 model in different road weather conditions. With the rapid advancements in the field of autonomous driving, the need for faster and more accurate object detection frameworks has become a necessity. Many recent deep learning-based object…