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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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. …”
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YOLO-HVS: Infrared Small Target Detection Inspired by the Human Visual System by Xiaoge Wang, Yunlong Sheng, Qun Hao, Haiyuan Hou, Suzhen Nie

“…To address challenges of background interference and limited multi-scale feature extraction in infrared small target detection, this paper proposes a YOLO-HVS detection algorithm inspired by the human visual system. …”
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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. …”
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MR-FuSN: A Multi-Resolution Selective Fusion Approach for Bearing Fault Diagnosis by Lin Sha, Shikai Tang, Min Wang, Sibo Qiao, Shihang Yu, Weixia Liu, Jiaqi Li

“…However, when collected in complex industrial environments, these signals are often contaminated by noise interference, posing significant challenges to fault feature extraction and diagnostic accuracy. …”
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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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License Plate Recognition for Smart Construction Sites Based on GMH-YOLO by Ming Li, Ze-Quan Wang, Yu-Hang Zhao, Qiang Li

“…This lightweight gating unit adaptively allocates feature channel resources, effectively enhancing key information while suppressing background interference, making it particularly suitable for detecting multiple license plate types and partially occluded plates in complex construction site environments. …”
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Rolling bearing fault diagnosis under small sample conditions based on WDCNN-BiLSTM Siamese network by Chenxu Bian, Chunni Jia, Jibo Li, Xiangjun Chen, Pei Wang

“…This model constructs a feature extraction system that combines WDCNN and BiLSTM to extract local spatial features and global temporal dependencies from vibration signals. …”
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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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Research on UAV Jamming Signal Generation Based on Intelligent Jamming by Haonan Xue, Zhihai Zhuo, Weihao Yan, Yuexia Zhang

“…The model leverages advanced convolutional networks to integrate the real and imaginary components of the signal for feature extraction, while the residual modules further refine signal processing and enhance feature learning. …”
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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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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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Supramodal and cross-modal representations of working memory in higher-order cortex by Doyoung Park, Seong-Hwan Hwang, Keonwoo Lee, Yeeun Ryoo, Hyoung F. Kim, Sue-Hyun Lee

“…While numerous studies have shown the involvement of sensory areas in maintaining working memory in a feature-specific manner, the challenge of utilizing retained sensory representations without interference from incoming stimuli of the same feature remains unresolved. …”
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Few-Shot Incremental Learning With Context-Aware Spatial Enhancement for Image Recognition by Heng Wu, Ze Yang, Zijun Zheng, Haiyang Wang, Wansong Wang

“…This comprehensive design not only reduces background interference and highlights salient features but also improves generalization and stability in few-shot learning scenarios. …”
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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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Swin Attention Augmented Residual Network: a fine-grained pest image recognition method by Xiang Wang, Zhiyong Xiao, Zhaohong Deng

“…On the one hand, Swin-AARNet enhances local key features and establishes a feature complementation mechanism, thereby improving the extraction capability of local features. …”
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Ship Plate Detection Algorithm Based on Improved RT-DETR by Lei Zhang, Liuyi Huang

“…The proposed model integrates three core components: an improved High-Frequency Enhanced Residual Block (HFERB) embedded in the backbone to strengthen multi-scale high-frequency feature fusion, with deformable convolution added to handle occlusion and deformation; a Pinwheel-shaped Convolution (PConv) module employing multi-directional convolution kernels to achieve rotation-adaptive local detail extraction and accurately capture plate edges and character features; and an Adaptive Sparse Self-Attention (ASSA) mechanism incorporated into the encoder to automatically focus on key regions while suppressing complex background interference, thereby enhancing feature discriminability. …”
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A lightweight multi scale fusion network for IGBT ultrasonic tomography image segmentation by Meng Song, Zhaoba Wang, Youxing Chen, Ya Li, Yong Jin, Bei Jia

“…Additionally, we introduce two flexible, plug-and-play modules: the Context Feature Fusion (CFF) module, which effectively integrates multi-scale contextual information at skip connection layers, and the Multi-Scale Perception Aggregation (MPA) module, which focuses on extracting and fusing multi-scale features at bottleneck layers. …”
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A Robust Cross-Band Network for Blind Source Separation of Underwater Acoustic Mixed Signals by Xingmei Wang, Peiran Wu, Haisu Wei, Yuezhu Xu, Siyu Wang

“…To address insufficient feature discrimination, we decompose mixed signals into sub-bands aligned with ship noise harmonics. …”
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Enhancing, Refining, and Fusing: Towards Robust Multiscale and Dense Ship Detection by Congxia Zhao, Xiongjun Fu, Jian Dong, Shen Cao, Chunyan Zhang

“…CASS-Det integrates three key innovations: 1) a center enhancement module (CEM) that employs rotational convolution to emphasize ship centers, improving localization while suppressing background interference; 2) a neighbor attention module that leverages cross-layer dependencies to refine ship boundaries in densely populated scenes; and 3) a cross-connected feature pyramid network (CC-FPN) that enhances multiscale feature fusion by integrating shallow and deep features. …”
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