In this paper, we propose a multipath-assisted device-free localization (DFL) system that includes magnitude and phase information (MAMPI). The DFL system employs ultra-wideband (UWB) channel impulse response (CIR) measurements, enabling the extracti...
The use of remote sensing to monitor coastlines with wide distributions and dynamic changes is significant for coastal environmental monitoring and resource management. However, most current remote sensing information extraction of coastlines is base...
As the basic feature of building, building edges play an important role in many fields such as urbanization monitoring, city planning, surveying and mapping. Building edges detection from high spatial resolution remote sensing (HSRRS) imagery has alw...
The critical problems faced during the machining process of heat resistant superalloys, (HRSA), is the concentration of heat in the cutting zone and the difficulty in dissipating it. The concentrated heat in the cutting zone has a negative influence...
During the study of multimodal brain tumor MR image segmentation, the large differences in the image distributions make the assumption that the conditional probabilities are similar when the edge distributions of the target and source domains are sim...
Spectral features cannot effectively reflect the differences among the ground objects and distinguish their boundaries in hyperspectral image (HSI) classification. Multi-scale feature extraction can solve this problem and improve the accuracy of HSI...
Rejoining oracle bone fragments plays an import role in studying the history and culture of the Shang dynasty by its characters. However, current computer vision technology has a low accuracy in judging whether the texture of oracle bone fragment ima...
While Evidence Theory (also known as Dempster–Shafer Theory, or Belief Functions Theory) is being increasingly used in data fusion, its potentialities in the Social and Life Sciences are often obscured by lack of awareness of its distinctive fe...
The edge devices connected to the Internet of Things (IoT) infrastructures are increasingly susceptible to piracy. These pirated edge devices pose a serious threat to security, as an adversary can get access to the private network through these non-a...
Three-Dimensional High-Efficiency Video Coding (3D-HEVC) efficiently compresses 3D video by incorporating depth map encoding techniques. However, the quadtree partitioning of depth map coding units (CUs) greatly increases computational complexity, co...
We investigate anomaly detection in complex networks through a property-testing-guided graph neural model (PT-GNN) that provides an end-to-end miss-probability certificate (δ+α). The method combines (i) a wedge-sampling tester that estima...
The semantic segmentation of remote sensing images is a significant research direction in digital image processing. The complex background environment, irregular size and shape of objects, and similar appearance of different categories of remote sens...
Object tracking has remained a challenging problem in recent years. Most of the trackers can not work well, especially when dealing with problems such as similarly colored backgrounds, object occlusions, low illumination, or sudden illumination chang...
Radiation anomalies in optical remote sensing images frequently occur due to electronic issues within the image sensor or data transmission errors. These radiation anomalies can be categorized into several types, including CCD, StripeNoise, RandomCod...
Identifying and reducing customer churn have become a priority for financial institutions seeking to retain clients. Our research focuses on customer churn rate analysis using advanced machine learning (ML) techniques, leveraging a synthetic dataset...
Information transfer that characterizes the information feature variation can have a crucial impact on big data analytics and processing. Actually, the measure for information transfer can reflect the system change from the statistics by using the va...
In synthetic aperture radar (SAR) images, pixel-level Ground Truth (GT) is a scarce resource compared to Bounding Box (BBox) annotations. Therefore, exploring the use of unsupervised instance segmentation methods to convert BBox-level annotations int...
A novel bearing vibration signal fault feature extraction and recognition method based on the improved local mean decomposition (LMD), permutation entropy (PE) and the optimized K-means clustering algorithm is put forward in this paper. The improved...
With continuous developments in deep learning, image semantic segmentation technology has also undergone great advancements and been widely used in many fields with higher segmentation accuracy. This paper proposes an image semantic segmentation algo...
The internal growth patterns and surface micromorphology of diamonds provide a record of their multi-stage evolution, from initial formation within the mantle to their eventual ascent to the Earth’s surface via deeply derived kimberlite magmas....
Serious ice accretion will cause structural problems and ice flashover accidents, which result in outdoor insulator string operating problems in winter conditions. Previous investigations have revealed that the thicker and longer insulators are cover...
Currently, deep learning-based segmentation methods are capable of achieving accurate segmentation. However, their deployment and training are costly and resource-intensive. To reduce deployment costs and facilitate the application of segmentation mo...
Dust storms, observed in all seasons, are among the most momentous of Mars’ atmospheric activities. The Entry–Descent–Landing (EDL) activity of a Martian landing mission is influenced by local atmospheric conditions, especially the probability of dus...
Human–object interaction (HOI) detection is important for promoting the development of many fields such as human–computer interactions, service robotics, and video security surveillance. A high percentage of human–object pairs with...
Classifying fluctuating operating wireless environments can be crucial for successfully delivering authentic and confidential packets and for identifying legitimate signals. This study utilizes raw in-phase (I) and quadrature-phase (Q) samples, exclu...
When the spatial distribution of winter wheat is extracted from high-resolution remote sensing imagery using convolutional neural networks (CNN), field edge results are usually rough, resulting in lowered overall accuracy. This study proposed a new p...
Visible and infrared image fusion is a strategy that effectively extracts and fuses information from different sources. However, most existing methods largely neglect the issue of lighting imbalance, which makes the same fusion models inapplicable to...
The transportation of wind turbine blades in remote wind farm areas poses significant safety risks to both personnel and infrastructure. These risks arise from collision hazards, complex terrain, and the difficulty of real-time monitoring under adver...
Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. N...
Precisely identifying cancer drivers helps us to understand the molecular mechanisms of cancer, offering critical targets for early diagnosis. Despite the increasing application of graph neural networks in predicting cancer driver genes, existing app...
Burn injuries are a common traumatic condition, and the early diagnosis of burn depth is crucial for reducing treatment costs and improving survival rates. In recent years, image-based deep learning techniques have been utilized to realize the automa...
The formation of structure in the visual system, that is, of the connections between cells within neural populations, is by and large an unsupervised learning process. In the primary visual cortex of mammals, for example, one can observe during devel...
The emergence of ground-breaking technologies such as artificial intelligence, cloud computing, big data powered by the Internet, and its highly valued real-world applications consisting of symmetric and asymmetric data distributions, has significant...
Accurate and high-throughput identification of the initial anthesis of soybean varieties is important for the breeding and screening of high-quality soybean cultivars in field trials. The objectives of this study were to identify the initial day of a...
The safe and stable operation of critical substation equipment is paramount to the power system, and its intelligent inspection relies on highly efficient and accurate object detection technology. However, the demanding requirements for both accuracy...
As edge computing environments become increasingly dynamic, the need for efficient job scheduling and proactive fault prevention is becoming paramount. In such environments, minimizing machine downtime and maintaining productivity are critical challe...
Nowadays, how to evaluate image quality reasonably is a basic and challenging problem. In view of the present no reference evaluation methods, they cannot reflect the human visual perception of image quality accurately. In this paper, we propose an e...
There is growing evidence that many large coastal boulder deposits found on the exposed rocky ocean shores were deposited by extreme storm waves rather than by catastrophic tsunamis, as previously thought. In addition, before the first discovery in t...
Time series classification is an active research topic due to its wide range of applications and the proliferation of sensory data. Convolutional neural networks (CNNs) are ubiquitous in modern machine learning (ML) models. In this work, we present a...
One primary concern in the field of remote-sensing image processing is the precise classification of hyperspectral images (HSIs). Lately, deep-learning models have demonstrated cutting-edge results in HSI classification. Despite this, researchers con...
Error evaluation is essential for the improvement and application of the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) Version 06 daily precipitation estimates, including early-, late-, and final-run products...
Semantic segmentation of urban scenes from red–green–blue and thermal infrared imagery enables per-pixel categorization, delivering precise environmental understanding for autonomous driving and urban planning. However, existing methods s...
The fish catch in natural upwelling areas, which accounts for only 0.1% of the ocean surface, accounts for more than 40% of the world’s catch. The Zhoushan fishery, which is the largest fishery in China, is mainly formed by a coastal upwelling...
The Bayesian network is a directed, acyclic graphical model that can offer a structured description for probabilistic dependencies among random variables. As powerful tools for classification tasks, Bayesian classifiers often require computing joint...
Deep Neural Networks (DNNs) are the primary approach for enhancing the real-time performance and accuracy of Keyword Spotting (KWS) systems in speech processing. However, the exceptional performance of DNN-KWS faces significant challenges related to...
The acquisition of nighttime remote-sensing visible-light images is often accompanied by low-illumination effects and haze interference, resulting in significant image quality degradation and greatly affecting subsequent applications. Existing low-li...
Edge processing is a trend in developing new technologies that leverage Artificial Intelligence (AI) without transmitting large volumes of data to centralized processing services. This technique is particularly relevant for security applications wher...
This article aims to aid in exploring and forecasting hydrothermal minerals and gold deposits in Central Saudi Arabia (SA), with a focus on structural contexts. Remote sensing (RS) and satellite-based Bouguer gravity (SBG) data were integrated in ord...
Aquifer properties, such as hydraulic transmissivity T and its spatial variability, are fundamental for sustainable groundwater exploitation in arid regions. Especially in karst aquifers, spatial variability can be considerable, and the application o...
Computational linguistics explores how human language is interpreted automatically and then processed. Research in this area takes the logical and mathematical features of natural language and advances methods and statistical procedures for automated...
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