n-FFT COMPRESSED SENSING ALGORITHM OF SMART DIMENSIONALITY REDUCTION METHOD AND ITS APPLICATION IN FEATURE EXTRACTION AND CLASSIFICATION OF GEAR SYSTEM by CHEN Xiao, HUANG ChuanJin

“…Analysis shows that n-FFT algorithm is fast,with high feature accumulation,is beneficial to the classify and fault monitoring and diagnosis of gear operating state.…”
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Parish Clergy and Secular Authorities in the Tobolsk North in 18^th - Early 20th Centuries: Features of Relationships by V. V. Tsys

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MS3D: A Multi-Scale Feature Fusion 3D Object Detection Method for Autonomous Driving Applications by Ying Li, Wupeng Zhuang, Guangsong Yang

“…It integrates a Second Feature Pyramid Network to enhance multi-scale feature representation and contextual integration. …”
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OM-VST: A video action recognition model based on optimized downsampling module combined with multi-scale feature fusion. by Xiaozhong Geng, Cheng Chen, Ping Yu, Baijin Liu, Weixin Hu, Qipeng Liang, Xintong Zhang

“…This model adds a multi-scale feature fusion module with an optimized downsampling module based on a Video Swin Transformer (VST) to improve the model's ability to perceive and characterize feature information. …”
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YOLOP-MVF: A Multi-Task Autonomous Driving Perception Detection Method Based on Multi Scale Feature Weighted Fusion by Yanqiu Niu, Jing Zhang

“…To address challenges such as large-scale variations, background interference, and occlusions in multi-task autonomous driving perception, this paper proposes YOLOP-MVF, a multi-task detection framework based on multi-scale feature weighting fusion. …”
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Features of Recognizing Images of Figures of Different Colors and Sizes by Children 3-4 Years Old Using a Noise Background by T.G. Kuznetsova, M.L. Struzhkin, I.Yu. Golubeva

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Fault Feature Extraction Based on Variational Modal Decomposition and Lifting Wavelet Transform: Application in Gear of Mine Scraper Conveyor Gearbox by Zhengxiong Lu, Linyue Li, Chuanwei Zhang, Shuanfeng Zhao, Lingxiao Gong

“…The minimum entropy value is used to set the sensitive parameters involved in lifting wavelet transform, and the power supply current frequency and noise interference information of a scraper conveyor are removed from the current signal. …”
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MFSE-TransUNet: A Thyroid Nodule Ultrasound Image Segmentation Network Integrated With Dynamic Feature Calibration and Edge Enhancement by Ye Lu, Jiaojiao Jing, Wenbo Zhang, Yali Kong

“…However, its low resolution, high noise interference, numerous artifacts, and blurred boundaries make manual annotation time-consuming and highly subjective. …”
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Micro-expression spotting based on multi-modal hierarchical semantic guided deep fusion and optical flow driven feature integration by Haolin Chang, Zhihua Xie, Fan Yang

“…By introducing an Optical Flow-Driven fusion feature Integration Module (OF-DIM), the correlation of non-scale fusion features is modeled in the channel dimension. …”
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A Yarn Quality Prediction Method Based on M-ESTIMATOR Robust Broad Learning System With Tightly Cascaded Feature Layers by Baowei Zhang, Zhilin Guo, Yonghua Wang

“…Aiming at the problem that multilayer neural networks rely on large datasets and broad learning system (BLS) cannot cope well with outliers in data of yarn production, which leads to low accuracy and stability when used for predicting yarn quality, we propose a robust broad learning system with the ability to resist the interference of outliers and optimize its ability to extract features. …”
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MF-ShipNet: a multi-feature weighted fusion and PCA-SVM model for ship detection in remote sensing images by Jianfeng Li, Yibing Yang, Liutong Yang, Yang Zhao, Qinghua Luo, Chenxu Wang

“…A weighted fusion method of Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG) was used to extract shape and texture features simultaneously. Principal Component Analysis (PCA) was used to reduce the dimension of fused features to reduce the false detection rate caused by redundant noise interference. …”
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TFF-Net: A Feature Fusion Graph Neural Network-Based Vehicle Type Recognition Approach for Low-Light Conditions by Huizhi Xu, Wenting Tan, Yamei Li, Yue Tian

“…To address the performance degradation caused by insufficient lighting, complex backgrounds, and light interference, this paper proposes a Twin-Stream Feature Fusion Graph Neural Network (TFF-Net) model. …”
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LGM-Net: Wheat Pest and Disease Detection Network Based on Local Global Information Interaction and Multi-Level Feature Fusion by Yimin Qu, Shaobo Yu, Jing Yang

“…Firstly, this paper designs a lightweight feature interactive network (LFI-Net) to fully extract the local and global features of wheat leaf diseases and improve the detection of wheat pest and disease targets under noise interference. …”
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Oil Spill Detection in PolSAR Imagery Using Composite Scattering Power Entropy and Multiscale Hybrid Feature Fusion Network by Deliang Xiang, Yu Lu, Dongdong Guan, Guannan Li, Jianda Cheng, Bangjie Li

“…To address the interference from look-alikes, we introduce a composite polarimetric feature, termed composite polarimetric scattering entropy, which effectively differentiates between oil spills and look-alikes. …”
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PCES-YOLO: High-Precision PCB Detection via Pre-Convolution Receptive Field Enhancement and Geometry-Perception Feature Fusion by Heqi Yang, Junming Dong, Cancan Wang, Zhida Lian, Hui Chang

“…Printed circuit board (PCB) defect detection faces challenges like small target feature loss and severe background interference. To address these issues, this paper proposes PCES-YOLO, an enhanced YOLOv11-based model. …”
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TBD-Y: Automatic tea bud detection with synergistic object-spatial attention and global-local attention guided feature fusion by Zhongyuan Liu, Li Zhuo, Chunwang Dong, Jiafeng Li, Yang Li

“…Firstly, a Synergistic Object-Spatial Attention (SOSA) mechanism is proposed, which incorporates the proposed Local Context Attention (LCA) mechanism to enhance the features in both spatial and regional dimensions. It enables the network to focus more on the tea bud regions, and suppress the interference from background noise. …”
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Leveraging 3GPP Features and Optimization Techniques for 5G NR-V2X Resource Allocation: A Survey by Chaeriah Bin Ali Wael, El Hadj Dogheche, Nasrullah Armi, Agus Subekti, Iyad Dayoub

“…Since its first introduction in rel-15 by 3GPP, 5G NR-V2X features have continued to evolve, aiming to support increasingly advanced V2X services. …”
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Robust scale fusion and edge-aware feature attention network for remote sensing UAV road detection under harsh weather by Jialang Liu, Jialei Zhan, Jiehua Zhang, Jiangming Chen, Yan Song, Lixing Tang, Le Zhou, Chengsi Du, Yingmei Wei, Yanming Guo

“…Accurate road detection from UAV imagery under adverse weather remains a significant challenge due to reduced visibility, motion blur, and environmental interference. To address these issues, we propose RSFC-EAFANet, a robust detection framework that integrates Robust Scale Fusion Convolution (RSFC) with an Edge-aware Adaptive Feature Aggregation (EAFA) module. …”
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HOMONYMY-RELATED ERRORS: A CASE STUDY AMONG ENGLISH MAJORED SOPHOMORES by Nguyen Phuong Lien, Nguyen Thi Kim Anh*, Vo Khanh Linh, Nguyen Thi Yen Vy

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A Complex Background SAR Ship Target Detection Method Based on Fusion Tensor and Cross-Domain Adversarial Learning by Haopeng Chan, Xiaolan Qiu, Xin Gao, Dongdong Lu

“…This improves the anti-interference and generalisation ability in complex backgrounds. …”
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