Cascaded Detection Method for Ship Targets Using High-Frequency Surface Wave Radar in the Time–Frequency Domain by Zhiqing Yang, Hao Zhou, Yingwei Tian, Gan Liu, Bing Zhang, Yao Qin, Peng Li, Weimin Huang

“…Compact high-frequency surface wave radars (HFSWRs) utilize miniaturized antennas, resulting in lower antenna gain and a reduced signal-to-noise ratio (SNR) for target echoes. Due to noise interference, ship echoes in the noise region often fall below the detection threshold, leading to missed detections. …”
Get full text

MCFNet: Multi-Scale Contextual Fusion Network for Salient Object Detection in Optical Remote Sensing Images by Jinting Ding, Yueqian Quan, Honghui Xu

“…In addition, MCFNet integrates a Contextual Interconnection Module (CIM), which promotes effective fusion of local and global contextual features. By facilitating cross-layer interactions and adopting a multiscale refinement strategy, CIM enriches texture representations while suppressing background interference, leading to smoother object boundaries and more precise delineation of salient regions. …”
Get full text

Small object detection in side-scan sonar images based on SOCA-YOLO and image restoration by Xiaodong Cui, Jiale Zhang, Lingling Zhang, Qunfei Zhang, Jing Han

“…The SOCA-YOLO framework first constructs a high-resolution SSS (sidescan sonar image) enhancement pipeline through image restoration techniques to extract fine-grained features of micro-scale targets. Subsequently, the SPDConv (Space-to-Depth Convolution) module is incorporated to optimize the feature extraction network, effectively preserving discriminative characteristics of small targets. …”
Get full text

Multi-Dimensional Fuzzy Clustering-Based Trajectory Initialization Algorithm for Infrared Weak Target Trajectories in Robust Clutter Environments by Ziqian Yang, Hongbin Nie, Yiran Li, Chunjiang Bian

“…The algorithm utilizes multidimensional feature information of the target, such as speed and irradiance, to determine point trajectory affiliation by assigning weights based on the clustering center of each feature type. …”
Get full text

Problems of Formation of a Multipolar Financial System under the Centralisation of Global Capital by A. V. Kuznetsov

“…The purpose of author’s research was the identification of the institutional features of the centralisation of global capital at the present stage of development of financial globalisation processes and identification of China’s potential, as a leader of the global economy, in creating a systemic counterweight to Anglo-Saxon domination in the global monetary and financial system.Methodology. …”
Get full text

An adaptive hexagonal deployment model for resilient wireless sensor networks in precision agriculture by Zhang Yinjun

“…The AFHSS mechanism dynamically adjusts frequency channels, mitigating interference and fortifying the network’s robustness against external disruptions. …”
Get full text

Research on CNC Machine Tool Spindle Fault Diagnosis Method Based on DRSN–GCE Model by Xiaoxu Li, Jiahao Wang, Jianqiang Wang, Jixuan Wang, Jiaming Chen, Xuelian Yu

“…Secondly, a convolutional gated layer is added to the deep residual network (DRSN), which suppresses the noise interference. The residual connection structure has also been improved in order to improve the transfer of features. …”
Get full text

Intelligent Recognition of Road Internal Void Using Ground-Penetrating Radar by Qian Kan, Xing Liu, Anxin Meng, Li Yu

“…However, due to noise interference during detection, accurately identifying void areas based on GPR-collected images remains a significant challenge. …”
Get full text

An adaptive assessment method of power system transient stability considering PMU data loss by Binyu Ma, Jun Yang, Xiaotao Peng, Kezheng Jiang, Dan Liu, Kan Cao

“…The effect of the proposed method shows high accuracy and strong anti‐noise interference ability in case of data loss.…”
Get full text

A Focal Attention-Based Large Convolutional Kernel Network for Anomaly Detection of Coated Fuel Particles by Zhaochuan Hu, Jiang Yu, Hang Zhang, Jian Liu, Ning Chen, Rong Li

“…First, incomplete particles in edge regions introduce significant interference. Second, some anomalies exhibit weak morphological features, making them difficult to detect. …”
Get full text

Stable Diffusion-Driven Conditional Image Augmentation for Transformer Fault Detection by Wenlong Liao, Yiping Jiang, Rui Liu, Yun Feng, Yu Zhang, Jin Hou, Jun Wang

“…The proposed method incorporates the Low-Rank Adaptation (LoRA) concept to fine-tune the pre-trained Stable Diffusion model weights, significantly reducing training requirements while effectively integrating the essential features of transformer equipment image data. To minimize interference from complex backgrounds, the Segment Anything Model (SAM) is employed for preprocessing, thereby enhancing the quality of generated image data. …”
Get full text

An Aerodynamic Method for the Analysis of Isolated Horizontal-Axis Wind Turbines by Christian Masson, Idriss Ammara, Ion Paraschivoiu

“…In most existing performance-analysis methods, wind turbines are considered isolated so that interference effects caused by other rotors or by the site topology are neglected. …”
Get full text

An adaptive continuous threshold wavelet denoising method for LiDAR echo signal by Dezhi Zheng, Tianchi Qu, Chun Hu, Shijia Lu, Zhongxiang Li, Guanyu Yang, Xiaojun Yang

“…In this paper, a novel adaptive continuous threshold wavelet denoising algorithm is proposed to filter out the noise. The algorithm features an adaptive threshold and a continuous threshold function. …”
Get full text

Charcot-Marie-Tooth disease: from historical landmarks in Brazil to current care perspectives by Eduardo Boiteux Uchôa Cavalcanti, Rita de Cássia Carvalho Leal, Wilson Marques Junior, Osvaldo José Moreira do Nascimento

“…Also, with discoveries in the field of genetics, including RNA interference and gene editing techniques, new treatment perspectives begin to emerge. …”
Get full text

InvMOE: MOEs Based Invariant Representation Learning for Fault Detection in Converter Stations by Hao Sun, Shaosen Li, Hao Li, Jianxiang Huang, Zhuqiao Qiao, Jialei Wang, Xincui Tian

“…To overcome these issues, we propose InvMOE, a novel fault detection algorithm with two core components: (1) invariant representation learning, which captures task-relevant features and mitigates background noise interference, and (2) multi-task training using a mixture of experts (MOE) framework to adaptively optimize feature learning across tasks and address label sparsity. …”
Get full text

AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. To address these challenges, this paper proposes AC-YOLO, a novel lightweight SAR ship detection model based on YOLO11. …”
Get full text

Deep learning-enhanced signal detection for communication systems. by Yang Liu, Peng Liu, Yu Shi, Xue Hao

“…Traditional communication signal detection heavily relies on manually designed features, making it difficult to fully characterize the essential characteristics of the signal, resulting in limited detection accuracy. …”
Get full text

Anomaly Detection of Acoustic Signals in Ultra-High Voltage Converter Valves Based on the FAVAE-AS by Shuyan Pan, Mingzhu Tang, Na Li, Jiawen Zuo, Xingpeng Zhou

“…However, the voiceprint signals collected by converter stations under complex operating conditions are often affected by background noise, spikes, and nonlinear interference. Traditional methods make it difficult to achieve high-precision detection due to the lack of feature extraction ability and poor noise robustness. …”
Get full text

FCA-STNet: Spatiotemporal Growth Prediction and Phenotype Extraction from Image Sequences for Cotton Seedlings by Yiping Wan, Bo Han, Pengyu Chu, Qiang Guo, Jingjing Zhang

“…A novel STNet structure is designed to enhance the representation of spatiotemporal dependencies, while an Adaptive Fine-Grained Channel Attention (FCA) module is integrated to capture both global and local feature information. This attention mechanism focuses on individual cotton plants and their textural characteristics, effectively reducing the interference from common field-related challenges such as insufficient lighting, leaf fluttering, and wind disturbances. …”
Get full text

soundscape_IR: A source separation toolbox for exploring acoustic diversity in soundscapes by Yi‐Jen Sun, Shih‐Ching Yen, Tzu‐Hao Lin

“…However, assessing the diversity of animal vocalizations remains challenging due to the interference of environmental and anthropogenic noise. …”
Get full text