Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …

The comprehensive intelligent development of the manufacturing industry puts forward new
requirements for the quality inspection of industrial products. This paper summarizes the …

To solve the problems of low accuracy, low real-time performance, poor robustness and
others caused by the complex environment, this paper proposes a face mask recognition …

Achieving the rapid and accurate detection of apple flowers in natural environments is
essential for yield estimation and the development of an automatic flower thinner. A real-time …

Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …

In object detection, keypoint-based approaches often experience the drawback of a large
number of incorrect object bounding boxes, arguably due to the lack of an additional …

Alternaria leaf spot, Brown spot, Mosaic, Grey spot, and Rust are five common types of apple
leaf diseases that severely affect apple yield. However, the existing research lacks an …

Aiming at the problems of high missed detection rates of the YOLOv7 algorithm for vehicle
detection on urban roads, weak perception of small targets in perspective, and insufficient …

Detecting objects remains one of computer vision and image understanding applications'
most fundamental and challenging aspects. Significant advances in object detection have …

Deep neural networks (DNNs) have shown prominent performance in the field of object
detection. However, DNNs usually run on powerful devices with high computational ability …