YOLO has become a central real-time object detection system for robotics, driverless cars,
and video monitoring applications. We present a comprehensive analysis of YOLO's …

This is a comprehensive review of the YOLO series of systems. Different from previous
literature surveys, this review article reexamines the characteristics of the YOLO series from …

Today's deep learning methods focus on how to design the objective functions to make the
prediction as close as possible to the target. Meanwhile, an appropriate neural network …

Over the past years, YOLOs have emerged as the predominant paradigm in the field of real-
time object detection owing to their effective balance between computational cost and …

Whole-body pose estimation localizes the human body, hand, face, and foot keypoints in an
image. This task is challenging due to multi-scale body parts, fine-grained localization for …

In recent years, YOLO object detection models have undergone significant advancement
due to the success of novel deep convolutional networks. The success of these YOLO …

In recent years, the realm of deep learning has witnessed significant advancements,
particularly in object detection algorithms. However, the unique challenges posed by remote …

As an essential component of the new energy vehicle battery, current collectors affect the
performance of battery and are crucial to the safety of passengers. The significant …

Ship detection plays a crucial role in ensuring maritime transportation and navigation safety.
However, accurately detecting multiscale ships remains a challenge due to the diversity of …

This review presents an investigation into the incremental advancements in the YOLO (You
Only Look Once) architecture and its derivatives, with a specific focus on their pivotal …