Due to the strong speckle noise caused by the seabed reverberation which makes it difficult to extract discriminating and noiseless features of a target, recognition and classification of underwater targets using side-scan sonar (SSS) images is a big...
Indoor localization provides robust solutions in many applications, and Wi-Fi-based methods are considered some of the most promising means for optimizing indoor fingerprinting localization accuracy. However, Wi-Fi signals are vulnerable to environme...
All current deep learning-based prediction methods for remaining useful life (RUL) assume that training and testing data have similar distributions, but the existence of various operating conditions, failure modes, and noise lead to insufficient data...
In order to obtain more fine-grained information from multiple sub-feature spaces for domain adaptation, this paper proposes a novel multi-representation joint dynamic domain adaptation network (MJDDAN) and applies it to achieve cross-database facial...
Cross-domain classification with small samples is a more challenging and realistic experimental setup. Until now, few studies have focused on the problem of small-sample cross-domain classification between completely different hyperspectral images (H...
The multi-process manufacturing of steel rolling products requires the cooperation of complicated and variable rolling conditions. Such conditions pose challenges to the fault diagnosis of the key equipment of the rolling mill. The development of tra...
Multi-focus image fusion plays an important role in the application of computer vision. In the process of image fusion, there may be blurring and information loss, so it is our goal to obtain high-definition and information-rich fusion images. In thi...
The rapid growth of scientific literature necessitates effective information extraction. However, existing methods face significant challenges, particularly when applied to multi-domain documents and low-resource languages. For Kazakh and Russian, th...
Federated learning (FL) enables privacy-preserving collaboration for Network Intrusion Detection Systems (NIDSs), but its effectiveness under heterogeneous traffic, severe class imbalance, and domain shift remains insufficiently characterized. We eva...
Parkinson’s disease (PD) is a common neurodegenerative disorder, and accurate identification of PD is critical for clinical diagnosis and disease management. Electroencephalography (EEG) sensors provide reliable real-time brain signal acquisiti...
Conventional few-shot learning (FSL) mainly focuses on knowledge transfer from a single source dataset to a recognition scenario with only a few training samples available but still similar to the source domain. In this paper, we consider a more prac...
Recently, the radar high-resolution range profiles (HRRPs) have gained significant attention in the field of radar automatic target recognition due to their advantages of being easy to acquire, having a small data footprint, and providing rich target...
Motor imagery (MI) brain–computer interfaces (BCIs) have been used for a wide variety of applications due to their intuitive matching between the user’s intentions and the performance of tasks. Applying dry electroencephalography (EEG) electrodes to...
Deep learning excels in the identification of specific plant diseases. However, dealing with multi-domain datasets, which encompass a variety of categories, presents challenges due to limited data availability. (1) Background: In real-world scenarios...
Domain-generalized few-shot text classification (DG-FSTC) is a new setting for few-shot text classification (FSTC). In DG-FSTC, the model is meta-trained on a multi-domain dataset, and meta-tested on unseen datasets with different domains. However, p...
Depth map super-resolution (DSR) is a technique aimed at restoring high-resolution (HR) depth maps from low-resolution (LR) depth maps. In this process, color images are commonly used as guidance to enhance the restoration procedure. However, the int...
As control and execution components within hydraulic systems, hydraulic valves are critical to system efficiency and operational safety. However, existing research primarily focuses on specific valve designs, exhibiting limitations in versatility and...
Pansharpening provides a computational solution to the resolution limitations of imaging hardware by enhancing the spatial quality of low-resolution hyperspectral (LRMS) images using high-resolution panchromatic (PAN) guidance. From an information-th...
Cross-view geolocation is a valuable yet challenging task. In practical applications, the images targeted by cross-view geolocation technology encompass multi-domain remote sensing images, including those from different platforms (e.g., drone cameras...
This paper proposes a new hybrid model for classifying stress states using EEG signals, combining multi-domain transfer entropy (TrEn) with a two-dimensional PCANet (2D-PCANet) approach. The aim is to create an automated system for identifying stress...
The main focus of this paper is the exploration of fault accommodation possibilities in the context of the function development of multi-domain systems. Faults inevitably occur in complex technical systems and may lead, if no accommodation entities o...
Predicting network abnormal events and behavior can enhance security situation awareness and the ability to infer attack intentions. Most of the existing abnormal event prediction methods usually rely on the temporal relationship features between eve...
Radar data mining is the key module for signal analysis, where patterns hidden inside of signals are gradually available in the learning process and its superiority is significant for enhancing the security of the radar emitter classification (REC) s...
Bearing fault diagnosis is critical for the reliability and safety of rotating machinery in industrial applications. Traditional fault diagnosis methods and single-view deep learning models often fail to capture the complex, multi-dimensional nature...
In this study, a hybrid piezo-flexural-hydraulic actuator is modeled and simulated using bond graph methodology. The hybrid actuator comprises piezoelectric stack actuator, mechanical flexural amplifier, and hydraulic piston actuator. The piezoelectr...
Artificial intelligence is set to transform the next generation of intelligent buildings through the application of information and semantic data models and machine learning algorithms. Semantic data models enable the understanding of real-world data...
The decoding of motor imagery (MI) electroencephalogram (EEG) signals is crucial for motor control and rehabilitation. However, as feature extraction is the core component of the decoding process, traditional methods, often limited to single-feature...
In industrial scenarios, bearing fault diagnosis often suffers from data scarcity and class imbalance, which significantly hinders the generalization performance of data-driven models. While generative adversarial networks (GANs) have shown promise i...
This paper proposes a human activity recognition (HAR) method for frequency-modulated continuous wave (FMCW) radar sensors. The method utilizes a multi-domain feature attention fusion network (MFAFN) model that addresses the limitation of relying on...
Accurate classification of import and export goods’ Harmonized System (HS) codes is essential for ensuring tax security. Applying text classification technologies for HS code classification can significantly enhance the prevention and control o...
Accurate fault diagnosis in analog circuits faces significant challenges owing to the inherent complexity of fault data patterns and the limited feature representation capabilities of conventional methodologies. Addressing the limitations of current...
Extracting causal relations from natural language texts is crucial for uncovering causality, and most existing causal relation extraction models are single-task learning-based models, which can not comprehensively address attributes such as part-of-s...
In bearing fault diagnosis, machine learning methods have been proven effective on the basis of the heterogeneous features extracted from multiple domains, including deep representation features. However, comparatively little research has been perfor...
The large amount of information stored in audio and video repositories makes search on speech (SoS) a challenging area that is continuously receiving much interest. Within SoS, spoken term detection (STD) aims to retrieve speech data given a text-bas...
Background: Decoding motor intentions from electroencephalogram (EEG) signals is a critical component of motor imagery-based brain–computer interface (MI–BCIs). In traditional EEG signal classification, effectively utilizing the valuable...
Reliable bearing fault diagnosis plays an important role in maintaining the safety and performance of rotating machinery in industrial systems. Although deep learning models have achieved remarkable success in this field, their dependence on a single...
Aiming to address insufficient feature extraction, vanishing gradients, and low prediction accuracy in tool wear prediction, this paper proposes a hybrid deep neural network based on a Convolutional Neural Network (CNN), Residual Network (ResNet) res...
Interrupted sampling repeater jamming (ISRJ) is characterized by its coherent processing gains and flexible modulation techniques. ISRJ generates spurious targets along the range, which presents significant challenges to the radar systems. However, e...
Facial expression recognition (FER) is a key task in affective computing and human–computer interaction, aiming to decode facial muscle movements into emotional categories. Although deep learning-based FER has achieved remarkable progress, robu...
Human–Computer Interfaces (HCI) deals with the study of interface between humans and computers. The use of radar and other RF sensors to develop HCI based on Hand Gesture Recognition (HGR) has gained increasing attention over the past decade. Today,...
Camera, lidar, and wearable-based gesture recognition technologies face practical limitations such as lighting sensitivity, occlusion, hardware cost, and user inconvenience. Wi-Fi channel state information (CSI) can be used as a contactless alternati...
Large language model (LLM) and Crowd Intelligent Innovation (CII) are reshaping the field of engineering design and becoming a new design context. Generative generic-field design can solve more general design problems innovatively by integrating mult...
Loess deposits in China, covering extensive regions, exhibit distinctive physical and mechanical characteristics, including collapsibility and reduced mechanical strength. These properties contribute to heightened susceptibility to slope-related geol...
Pumped-storage power stations, as a critical resource for supporting secure and stable grid operation, typically adopt a ’single-tunnel-multiple-unit’ configuration, where hydraulic disturbance becomes a key operating condition affecting...
The digital twin model, which serves as a virtual counterpart symmetric to the physical entity, enables high-fidelity simulation and real-time monitoring. However, digital twin implementation for marine steam turbines (MSTs) faces dual multi-domain s...
Multi-domain image-to-image translation with the desired attributes is an important approach for modifying single or multiple attributes of a face image, but is still a challenging task in the computer vision field. Previous methods were based on eit...
Automated electroencephalography (EEG) seizure detection is meaningful in clinical medicine. However, current approaches often lack comprehensive feature extraction and are limited by generic classifier architectures, which limit their effectiveness...
Building performance simulation is crucial for the design and optimization of sustainable buildings. However, the increasing complexity of building systems necessitates advanced modeling techniques capable of handling multi-domain interactions. This...
The evolutionary aspects of cystatins are greatly underexplored in early-emerging metazoans. Thus, we surveyed the gene organization, protein architecture, and phylogeny of cystatin homologues mined from 110 genomes and the transcriptomes of 58 basal...
The advancement of sciences and technologies, economic challenges, increasing expectations, and consumerism result in a radical transformation of health and social care around the globe, characterized by foundational organizational, methodological, a...
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