The abnormal traffic detection scheme based on PCA and SSH by Zhenhui Wang, Dezhi Han, Ming Li, Han Liu, Mingming Cui

“…PCSS applies the PCA algorithm to the data preprocessing to eliminate the interference of redundant data. At the same time, PCSS also combines feature fusion and SSH to enhance the feature extraction of unclear features data, and effectively improve the detection speed and accuracy. …”
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A High-Precision Method for Warehouse Material Level Monitoring Using Millimeter-Wave Radar and 3D Surface Reconstruction by Wenxin Zhang, Yi Gu

“…To improve grain surface identification, an anomalous signal correction method based on angle–range feature fusion is introduced, mitigating errors caused by weak reflections and multipath effects. …”
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Low-Voltage Alternating Current Series Arc Fault Detection Using Periodic Background Subtraction and Linear Dividing Lines by Xiaofei Zhang, Jinjie Li, Bangzheng Han, Wei Wang, Guofeng Zou

“…This approach effectively suppresses interference from normal current variations and environmental noise, enabling a more robust expression of arc fault characteristics. …”
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Recognition of Cordyceps Based on Machine Vision and Deep Learning by Zihao Xia, Aimin Sun, Hangdong Hou, Qingfeng Song, Hongli Yang, Liyong Ma, Fang Dong

“…MRFPN is used to solve the problem of weak features. In N-CSPDarknet53, the Da-Conv module is proposed to address the background and color interference problems in shallow feature maps. …”
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Advanced Dense Text Detection in Graded Examinations Leveraging Chinese Character Components by Renyuan Liu, Yunyu Shi, Xian Tang, Xiang Liu

“…In the field of education, the detection of handwritten Chinese characters is affected by background noise, texture interference, etc. Especially in low-quality handwritten text, character overlap or occlusion makes the character boundaries blurred, which increases the difficulty of detection and segmentation; In this paper, an improved EAST network CEE (Components-ECA-EAST Network), which fuses the attention mechanism with the feature pyramid structure, is proposed based on the analysis of the structure of Chinese character mini-components. …”
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Curvature Scale Space Corner Detection-Based Registration Algorithm for Infrared and Visible Light Images of Power Equipment by HongYan Han, ZhengGuang Wang, Peng Ding, Nan Liu, ZhenYao Li, ZhanQiang Ru, WenQing Zhu, HeLun Song

“…First, a Modal Perception-Based Canny Edge Detection Strategy (MP-Canny) is developed to resolve feature sparsity in low-contrast infrared images and noise interference in visible-light images. …”
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ATT-CR: Adaptive Triangular Transformer for Cloud Removal by Yang Wu, Ye Deng, Pengna Li, Wenli Huang, Kangyi Wu, Xiaomeng Xin, Jinjun Wang

“…To address these challenges, we propose the adaptive triangular transformer for cloud removal (ATT-CR), a model that effectively reduces computational costs and mitigates interference from cloudy pixels. Specifically, it consists of two core components: Triangular attention (TAN) and feature selected gating module (FSGM). …”
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HFC-YOLO11: A Lightweight Model for the Accurate Recognition of Tiny Remote Sensing Targets by Jinyin Bai, Wei Zhu, Zongzhe Nie, Xin Yang, Qinglin Xu, Dong Li

“…To address critical challenges in tiny object detection within remote sensing imagery, including resolution–semantic imbalance, inefficient feature fusion, and insufficient localization accuracy, this study proposes Hierarchical Feature Compensation You Only Look Once 11 (HFC-YOLO11), a lightweight detection model based on hierarchical feature compensation. …”
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MSLI-Net: retinal disease detection network based on multi-segment localization and multi-scale interaction by Zhenjia Qi, Jin Hong, Jilan Cheng, Guoli Long, Hanyu Wang, Siyue Li, Shuangliang Cao

“…Additionally, a multi-segmented lesion localization module (LLM) is integrated within each branch of a modified feature pyramid network (FPN) to effectively extract critical features while suppressing background noise through parallel branch refinement, and a wavelet subband spatial attention module (WSSA) is designed to significantly improve the model’s overall performance in noise suppression by collaboratively processing and exchanging information between the low- and high-frequency subbands extracted through wavelet decomposition.ResultsExperimental evaluation on the OCT-C8 dataset demonstrates that MSLI-Net achieves 96.72% accuracy in retinopathy classification, underscoring its strong discriminative performance and promising potential for clinical application.ConclusionThis model provides new research ideas for the early diagnosis of retinal diseases and helps drive the development of future high-precision medical imaging-assisted diagnostic systems.…”
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A Distributed Detection Method for Quality-related Faults in Complex Non-stationary Industrial Processes by Jie DONG, Daye LI, Yanmei WEI, Kaixiang PENG, Hui YANG

“…This classical method identifies a feature subset that maximizes the correlation between features and targets and minimizes redundancy between features based on mutual information. …”
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Building Surface Defect Detection Based on Improved YOLOv8 by Xiaoxia Lin, Yingzhou Meng, Lin Sun, Xiaodong Yang, Chunwei Leng, Yan Li, Zhenyu Niu, Weihao Gong, Xinyue Xiao

“…Traditional methods face three challenges in complex scenarios: locating defect features accurately due to multi-scale texture and background interference, missing fine cracks because of their tiny size and low contrast, and the insufficient generalization of irregular defects due to complex geometric deformation. …”
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A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

“…Despite advancements in satellite-based radiometry such as NASA’s Soil Moisture Active Passive (SMAP), significant challenges persist in coastal SSS retrieval due to radio frequency interference (RFI), land-sea contamination, and complex interactions of nearshore dynamic processes.MethodThis study proposes a deep neural network (DNN) framework that integrates SMAP L-band brightness temperature data with ancillary oceanographic and geographic parameters such as sea surface temperature, the shortest distance to the coastline (dis) to enhance SSS estimation accuracy in the Yellow and East China Seas. …”
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YOLO-SRSA: An Improved YOLOv7 Network for the Abnormal Detection of Power Equipment by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…In the network structure improvements, first, the ACmix module is introduced to reconstruct the SPPCSPC network, effectively suppressing background noise and irrelevant feature interference to enhance feature extraction capability; second, the BiFormer module is integrated into the efficient aggregation network to strengthen focus on critical features and improve the flexible recognition of multi-scale feature images; finally, the original loss function is replaced with the MPDIoU function, optimizing detection accuracy through a comprehensive bounding box evaluation strategy. …”
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A New Signal Separation and Sampling Duration Estimation Method for ISRJ Based on FRFT and Hybrid Modality Fusion Network by Siyu Wang, Chang Zhu, Zhiyong Song, Zhanling Wang, Fulai Wang

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MFFSNet: A Lightweight Multi-Scale Shuffle CNN Network for Wheat Disease Identification in Complex Contexts by Mingjin Xie, Jiening Wu, Jie Sun, Lei Xiao, Zhenqi Liu, Rui Yuan, Shukai Duan, Lidan Wang

“…A dual-branch shuffle attention mechanism (DSA) is also integrated to enhance the model’s focus on critical features, reducing interference from complex backgrounds. …”
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GAT-Enhanced YOLOv8_L with Dilated Encoder for Multi-Scale Space Object Detection by Haifeng Zhang, Han Ai, Donglin Xue, Zeyu He, Haoran Zhu, Delian Liu, Jianzhong Cao, Chao Mei

“…Traditional YOLO-series algorithms encounter challenges such as poor robustness in small object detection and significant interference from complex backgrounds. In this paper, a multi-scale feature fusion framework based on an improved version of YOLOv8_L is proposed. …”
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Spatiotemporal Interactive Learning for Cloud Removal Based on Multi-Temporal SAR–Optical Images by Chenrui Xu, Zhenfei Wang, Liang Chen, Xiangchao Meng

“…To address these challenges, a spatiotemporal feature interaction-based cloud removal method is proposed to effectively fuse SAR and optical images. …”
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Hierarchical Sampling Representation Detector for Ship Detection in SAR Images by Ming Tong, Shenghua Fan, Jiu Jiang, Chu He

“…However, distinguishing ship targets precisely from the interference of multiplicative non-Gaussian coherent speckle is still a challenging task due to the discreteness, variability, and nonlinearity of ship scattering features. …”
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LAAVOS: A DeAOT-Based Approach for Medaka Larval Ventricular Video Segmentation by Kai Rao, Minghao Wang, Shutan Xu

“…And the video frames contain multiple complex interfering factors, including optical interference from the filming environment, dynamic color changes caused by blood flow, significant diversity in ventricular scales, image blurring in certain video frames, high similarity in organ structures, and indistinct boundaries between the ventricles and atria. …”
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CSSA-YOLO: Cross-Scale Spatiotemporal Attention Network for Fine-Grained Behavior Recognition in Classroom Environments by Liuchen Zhou, Xiangpeng Liu, Xiqiang Guan, Yuhua Cheng

“…Second, a Shuffle Attention mechanism is then integrated into the neck to suppress interference from complex backgrounds, thereby enhancing the model’s ability to focus on relevant features. …”
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