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 …

Object detection for industrial applications refers to analyzing the captured images and
videos and finding the relationship between the detected objects for better optimization, data …

The YOLO series has become the most popular framework for real-time object detection due
to its reasonable trade-off between speed and accuracy. However we observe that the …

Weeds are among the major threats to cotton production. Overreliance on herbicides for
weed control has accelerated the evolution of herbicide-resistance in weeds and caused …

目标检测是计算机视觉领域的一个基础任务和研究热点. YOLO 将目标检测概括为一个回归问题
, 实现端到端的训练和检测, 由于其良好的速度-精度平衡, 近几年一直处于目标检测领域的领先 …

For the operation and visual positioning of a banana robot, it is important to accurately
position the rachis and cut off point. However, the main factors that affect the three …

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 …

Object detection is a critical and complex problem in computer vision, and deep neural
networks have significantly enhanced their performance in the last decade. There are two …

At present, the existing methods have many limitations in small target detection, such as low
accuracy, a high rate of false detection, and missed detection. This paper proposes the KPE …

Object detection is a crucial branch of computer vision that aims to locate and classify
objects in images. Using deep convolutional neural networks (CNNs) as the primary …