EHTracker: Toward Fine-Grained Localization for Satellite Video Target Tracking by Jianwei Yang, Yuhan Liu, Yanxing Liu, Ziming Wang, Jiawei Li, Guangyao Zhou, Wenzhi Wang, Yuxin Hu

“…Second, to enable the regression branch to determine the location of feature-poor small targets more accurately, we introduce a gradual regression strategy (GRS). …”
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Cross-Visual Style Change Detection for Remote Sensing Images via Representation Consistency Deep Supervised Learning by Jinjiang Wei, Kaimin Sun, Wenzhuo Li, Wangbin Li, Song Gao, Shunxia Miao, Yingjiao Tan, Wei Cui, Yu Duan

“…RCCD leverages large-kernel convolutional supervision for local spatial context awareness and global content-aware style transfer for feature harmonization, effectively suppressing interference from background variations. …”
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Cognitive intelligence routing protocol for disaster management and underwater communication system in underwater acoustic network by Kiran Saleem, Lei Wang, Ahmad Almogren, Ernest Ntizikira, Ateeq Ur Rehman, Salil Bharany, Seada Hussen

“…Key features include intelligent node mechanisms, proactive bandwidth and interference management, a multi-hop paradigm, distance-aware longevity strategies, and robust cryptographic protocols. …”
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Knowledge-Driven Flood Intelligent Monitoring (KDFIM) Method: Analyzing the Kakhovka Dam Destruction Incident by Zhijun Jiao, Zhimei Zhang, Biyan Chen, Syed Amer Mahmood, Lixin Wu

“…First, KDFIM integrates both satellite imaging knowledge and ground object scattering knowledge to construct a spatiotemporal SAR feature fusion module, which is designed to mitigate the noise and interference present in the background and to extract multispectral SAR features for flood detection. …”
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Detection of underground personnel safety helmet wearing based on improved YOLOv8n by WANG Qi, XIA Lufei, CHEN Tianming, HAN Hongyin, WANG Liang

“…A convolutional block attention module (CBAM) was integrated into the backbone network to extract key image features and reduce background interference. The CIoU loss function was replaced with the WIoU loss function to improve the model's localization capability for detection targets. …”
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Intelligent identification of electromagnetic radiation signals induced by coal rock fractures using machine learning by LI Baolin, FENG Jiaqi, WANG Enyuan, SUN Xinyu, WANG Shuowei

“…Both the feature set and the choice of machine learning algorithm significantly influenced the identification accuracy of valid and interference signals. …”
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LIO-CSI: LiDAR inertial odometry with loop closure combined with semantic information. by Gang Wang, Saihang Gao, Han Ding, Hao Zhang, Hongmin Cai

“…Moreover, a registration based on a geometric feature is vulnerable to the interference of a dynamic object, resulting in a decline of accuracy. …”
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RaGeoSense for smart home gesture recognition using sparse millimeter wave radar point clouds by Honghong Chen, Xiangyu Wang, Zhanjun Hao, Yuru Lu, Jingyu Li, Haozhe Zhang, Ben Xi

“…Subsequently, the generated point cloud data are processed with sliding sequence sampling and point cloud tiling to extract the spatio-temporal features of the action. To further improve the classification performance, the system proposes an integrated model architecture that combines GBDT and XGBoost for efficient extraction of nonlinear features, and utilizes LSTM gated loop units to classify the gesture sequences, thus realizing the accurate recognition of eight different one-arm gestures. …”
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Research on Unsupervised Domain Adaptive Bearing Fault Diagnosis Method Based on Migration Learning Using MSACNN-IJMMD-DANN by Xiaoxu Li, Jiahao Wang, Jianqiang Wang, Jixuan Wang, Qinghua Li, Xuelian Yu, Jiaming Chen

“…Then, the adversarial loss mechanism in DANN is introduced to reduce the interference of weakly correlated domain features for better fault diagnosis and identification. …”
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ShadowFPN-YOLO: A Real-Time NMS-Free Detector for Remote Sensing Ship Detection by Xiao Yang, Ahmad Sufril Azlan Mohamed, Chuanchuan Wang

“…ShadowFPN dynamically applies shadows to multi-scale feature maps by randomly masking contiguous regions, effectively reducing background interference and enhancing the network’s focus on the essential features of target ships. …”
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Dam Crack Instance Segmentation Algorithm Based on Improved YOLOv8 by Shuaisen Ma, Mingyue Xu, Weiwu Feng

“…The method integrates Cascaded Group Attention (CGA) to enhance the perception of global information and features of slender crack. It also employs Diverse Branch Block (DBB) technology to strengthen the convolutional network’s ability to extract subtle crack features without increasing inference costs. …”
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A high-impedance fault location method for resonant grounded distribution networks based on transformer and few-shot learning by Bo Li, Yunyao Tan, Kai Liao, Jianwei Yang, Zhengyou He

“…High-impedance faults (HIFs) in resonant grounded distribution networks have illegible fault features, which are difficult to accurately be located. …”
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Citrus Disease Classification Model Based on Improved ConvNeXt by Jichi Yan, Yongbin Mo, Yannan Yu, Shiqing Dou, Rongfeng Yang

“…Firstly, the attention mechanism is changed to a parallel connection in the convolutional block attention module, and the attention mechanism is incorporated into ConvNeXt, which improves the model’s ability of feature extraction, makes the model focus more on lesion features, and suppresses the interference of background information. …”
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A dual-stream ordered topology-aware network for accurate fish counting in aquaculture environments by Jiaming Xin, Zhengmeng Wu, Tongtong Gu, Yiying Wang, Dashe Li, Bin Wang

“…Second, an Ordered Filtering Attention mechanism enhances feature representation in fish regions through bidirectional sorting and progressive correlation filtering, suppressing background interference. …”
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Research on Fault Diagnosis Method for Marine Diesel Engines Based on Multi-Scale Attention Mechanism Transformer by Manyi Chen, Huibing Gan, Hangjie Wu

“…This multi-scale strategy enhances the extraction of detailed and coarse-grained features, improving the model’s capacity to detect and characterize complex diesel engine faults. …”
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VDMNet: A Deep Learning Framework with Vessel Dynamic Convolution and Multi-Scale Fusion for Retinal Vessel Segmentation by Guiwen Xu, Tao Hu, Qinghua Zhang

“…Firstly, we introduce the Fast Multi-Head Self-Attention (FastMHSA) module to effectively capture both global and local features, enhancing the network’s robustness against complex backgrounds and pathological interference. …”
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Indoor Dynamic Environment Mapping Based on Semantic Fusion and Hierarchical Filtering by Yiming Li, Luying Na, Xianpu Liang, Qi An

“…To address the challenges of dynamic object interference and redundant information representation in map construction for indoor dynamic environments, this paper proposes an indoor dynamic environment mapping method based on semantic fusion and hierarchical filtering. …”
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YConvFormer: A Lightweight and Robust Transformer for Gearbox Fault Diagnosis with Time–Frequency Fusion by Yihang Peng, Jianjie Zhang, Songpeng Liu, Mingyang Zhang, Yichen Guo

“…Finally, the YConvFormer lightweight architecture is proposed, which combines shallow feature processing with global–local modeling, significantly reducing computational load. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

“…This paper addresses the issue of noise interference and variable working conditions in the production and machining environment, which lead to weak tool life features and reduced prediction accuracy. …”
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Exploring Task-Related EEG for Cross-Subject Early Alzheimer’s Disease Susceptibility Prediction in Middle-Aged Adults Using Multitaper Spectral Analysis by Ziyang Li, Hong Wang, Jianing Song, Jiale Gong

“…Electroencephalogram (EEG) data were collected from the Multi-Source Interference Task (MSIT) and Sternberg Memory Task (STMT). …”
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