Detecting small or tiny objects is always a difficult and challenging issue in computer vision.
In this paper, we provide a latest and comprehensive survey of deep learning-based …

This exploration primarily aims to jointly apply the local FCN (fully convolution neural
network) and YOLO-v5 (You Only Look Once-v5) to the detection of small targets in remote …

UAV technology is a basic technology aiming to help realize smart living and the
construction of smart cities. Its vigorous development in recent years has also increased the …

The depth synthesis of image texture is neglected in the current image visual communication
technology, which leads to the poor visual effect. Therefore, the design method of film and …

Studying the representational capacity of neural networks to learn nonlinear rewards is
necessary in a complex and nonlinear environment. Over recent years, the maximum …

Aerial image target detection is a challenging task due to the complex backgrounds, dense
target distribution, and large-scale differences often present in aerial images. Existing …

Vat photopolymerization is characterized by its high precision and efficiency, making it a
highly promising technique in ceramic additive manufacturing. However, the process faces a …

At present, the existing algorithm for detecting the parabola of tennis serves neglects the pre‐
estimation of the global motion information of tennis balls, which leads to great error and low …

Deep learning models have become the mainstream algorithm for processing computer
vision tasks. In the tasks of object detection, the detection box is usually set as a rectangular …

With the development of deep learning, target detection from vision sensor has achieved
high accuracy and efficiency. However, small target detection remains a challenge due to …