To support multi-source data stream generated from Internet of Things devices, edge computing emerges as a promising computing pattern with low latency and high bandwidth compared to cloud computing. To enhanc...
Studying the real-time face expression state of teachers in class was important to build an objective classroom teaching evaluation system based on AI. However, the face-to-face communication in classroom cond...
Due to its low latency and energy consumption, edge computing technology is essential in processing multi-source data streams from intelligent devices. This article investigates a mobile edge computing network...
With the rapid development of information technology, mining valuable information from multi-source data stream is essential for redundant data, particularly in image processing; the image is degraded when the...
Few-shot semantic segmentation (FSS) has been widely used in the field of information medicine and intelligent diagnosis. Due to the high cost of medical data collection and the privacy protection of patients,...
This paper investigates a non-orthogonal multiple access (NOMA)-aided mobile edge computing (MEC) network with multiple sources and one computing access point (CAP), in which NOMA technology is applied to tran...
In smart grid, the neighborhood area network (NAN) serves as a bridge connecting smart meters and meter data management system (MDMS) and is one of the most important components of the smart grid communication...
In the era of the Internet of Everything, various wireless devices and sensors use spectrum, which is a precious and non-renewable resource, to communication. Due to the characteristics of massive, heterogeneo...
It is undeniable that there are a large number of redundant nodes in a wireless sensor network. These redundant nodes cause a colossal waste of resources and seriously threaten the life of the sensor network. ...
Coherent optical orthogonal frequency division multiplexing (CO-OFDM) system is susceptible to nonlinear effects because of its intrinsic high peak-to-average ratio (PAPR). In this paper, two methods based on ...
In order to solve the problem that the original path forwarding traffic caused by congestion that cannot be recovered in time in Smart Grid Communication, a congestion control scheme RFCC (Router Forwarding Co...
With the development of avionics industry, it is difficult for traditional combat equipment node evaluation method to meet our requirements under complex combat system. This paper presents a method of node imp...
Depth–spectral imaging (DSI) is an emerging technology which can obtain and reconstruct the spatial, spectral and depth information of a scene simultaneously. Conventionally, DSI system usually relies on scann...
In bearings-only localization, clustering-based methods have been widely used to remove spurious intersections by fusing multiple bearing measurements from different observation stations. Existing clustering m...
A large number of epidemics, including COVID-19 and SARS, quickly swept the world and claimed the precious lives of large numbers of people. Due to the concealment and rapid spread of the virus, it is difficul...
Relay-based UAV swarm can further expand the surveillance range for more complex missions. Microsatellite swarms provide invulnerability and stability compared to conventional satellites and are selected for m...
The Kmeans clustering algorithm is widely used for the advantages of simplicity and efficient operation. However, the lack of clustering centers in the algorithm usually causes incorrect category of some discr...
Array signal processing plays an important role in many areas. Besides the Uniform Linear Array, there are many sparse array that have been proposed, for example, Minimum-redundancy array, Co-prime array, nest...
Six polarization-shift keying quadrature phase shift keying (6PolSK-QPSK) signal modulation format is formed by different representations of QPSK. A variety of satisfactory single-carrier transmission schemes ...
In computer vision, timely and accurate execution of object identification tasks is critical. However, present road damage detection approaches based on deep learning suffer from complex models and computation...
Multivariate time series are widely used in industrial equipment monitoring and maintenance, health monitoring, weather forecasting and other fields. Due to abnormal sensors, equipment failures, environmental ...