GDSN-CD: Graph-Guided Diffusion Synergistic Network for Remote Sensing Change Detection by Yunfei Zhu, Jintao Song, Jinjiang Li

“…Furthermore, we propose a hierarchical dynamic fusion module that adaptively fuses multilevel features to coordinate the complementary relationship between texture and semantics; and design a dual-feature dynamic selection module that optimizes the fusion of differential and additive features through adaptive weighting, accurately enhancing change signals while suppressing background interference. …”
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TPI-Net: Time-Phase Interaction Network Based on Learnable Wavelet Attention for Remote Sensing Change Detection by Yekai Cui, Jintao Song, Jinjiang Li

“…The model first employs ResNet50 for feature extraction, followed by the Deformable Local-Global Attention Interaction Module (DLGAM), which enhances feature consistency and suppresses nonchange area interference. …”
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A Small Target Pedestrian Detection Model Based on Autonomous Driving by Yang Zhang, Shuaifeng Zhang, Dongrong Xin, Dewang Chen

“…To improve the accuracy of small-target pedestrian detection and the anti-interference ability of the model, a small-target pedestrian detection model that fuses residual networks and feature pyramids is proposed. …”
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Study on evolution of NR duplex operation by Ting KE, Xinghua SONG, Fei WANG, Zhiheng GUO, Tuo YANG, Chunxia GUO, Chengcheng HAN, Yunfeng LIU, Zhenyu LI

“…Subband non-overlapping full duplex (SBFD) at gNB side within a conventional TDD band was considered as a key feature of 5G-Advanced to fulfill the challenging requirements of low latency and high uplink throughput emerging in vertical industry and industrial internet.Meanwhile, gNB-to-gNB cross-link interference handling needed to be enhanced to enable different TDD configurations for both public network (Macro) and vertical network (Micro) applied in the same frequency band.With a thorough analysis on the interference characteristic in the potential deployment scenarios for both different TDD configurations and subband non-overlapping full duplex, various feasible interference handling schemes to fulfill the challenging deployment requirements for vertical industry and industrial internet were presented, and the feasibility of above duplex enhancement schemes was checked via link budget, simulation and proof-of-concept prototype.…”
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Study on evolution of NR duplex operation by Ting KE, Xinghua SONG, Fei WANG, Zhiheng GUO, Tuo YANG, Chunxia GUO, Chengcheng HAN, Yunfeng LIU, Zhenyu LI

“…Subband non-overlapping full duplex (SBFD) at gNB side within a conventional TDD band was considered as a key feature of 5G-Advanced to fulfill the challenging requirements of low latency and high uplink throughput emerging in vertical industry and industrial internet.Meanwhile, gNB-to-gNB cross-link interference handling needed to be enhanced to enable different TDD configurations for both public network (Macro) and vertical network (Micro) applied in the same frequency band.With a thorough analysis on the interference characteristic in the potential deployment scenarios for both different TDD configurations and subband non-overlapping full duplex, various feasible interference handling schemes to fulfill the challenging deployment requirements for vertical industry and industrial internet were presented, and the feasibility of above duplex enhancement schemes was checked via link budget, simulation and proof-of-concept prototype.…”
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An Integrated Mechanical Fault Diagnosis Framework Using Improved GOOSE-VMD, RobustICA, and CYCBD by Jingzong Yang, Xuefeng Li

“…By employing an energy-feature-driven fitness function, this approach achieves synergistic optimization of the mode number and penalty factor. …”
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Detecting subsurface diseases on airport road surface based on an improved SSD algorithm. by Mengmeng Pan, Huiguang Chen, Lipeng Yang, XianRong Jiang

“…We analyze and propose an improved algorithm EFA-SSD (Enhanced Feature Aggregation SSD) for automatic detection of airport road subsurface diseases, which solves the problems of strong noise background conditions, severe interference of morphological features of different types of subsurface diseases, and low target recognition. …”
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Novel Deep Learning Framework for Evaporator Tube Leakage Estimation in Supercharged Boiler by Yulong Xue, Dongliang Li, Yu Song, Shaojun Xia, Jingxing Wu

“…However, leakage faults of evaporation tubes feature high time dependency, strong coupling among monitoring parameters, and interference from noise. …”
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Application of Prior-knowledge for Intelligent Gear Fault Diagnosis Under Variable Speed Condition by Pan Can, Li Weihua

“…Using the amplitude spectrum of the vibration response signal whose interference components are removed as input of the diagnosis model,it can reduce the feature difference between the samples of same class which correspond to different running speeds,and improve the generalization ability of the diagnosis model effectively,so that it can adapt to speed variation in a certain extent.…”
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DADNet: text detection of arbitrary shapes from drone perspective based on boundary adaptation by Jun Liu, Jianxun Zhang, Ting Tang, Shengyuan Wu

“…Using ResNet50 as the backbone network, we introduce the proposed Hybrid Text Attention Mechanism into the backbone network to enhance the perception of text regions in the feature extraction module. Additionally, we propose a Spatial Feature Fusion Module to adaptively fuse text features of different scales, thereby enhancing the model’s adaptability. …”
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基于EEMD与奇异熵增量谱的齿轮故障特征提取 by 杨望灿, 张培林, 吴定海, 陈彦龙

“…A method of feature extraction for gear fault based on Ensemble empirical mode decomposition（EEMD）and incremental spectrum of singularity entropy is put forward for the non-stationary and non-linear characteristics of gear vibration signal.Firstly,the gear vibration signal is decomposed into several smooth intrinsic mode functions（IMFs）by EEMD.The method of EEMD could take advantage of dyadic scale decomposition characteristics of the normal distribution white noise to suppress the problem of mode confusion in EMD.Because of the interference of background noise and residual assisted white noise,the gear fault feature is not extracted exactly from IMF.The method of singular value decomposition is used to remove the noise and reconstruct the IMF.The reconstruction order is determined according to the incremental spectrum of singularity entropy.Therefore the gear fault feature frequency could be extracted exactly.Results of simulation analysis and the gear fault test indicated that this method is accurate and effective for gear fault feature extraction.…”
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Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF by Yu Ding, Fei Wang, Zhen-ya Wang, Wen-jin Zhang

“…The proposed CRSR method is able to enhance the robustness of the feature information against interference while selecting the feature combination with balanced information expressing ability. …”
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Color image steganalysis based on embedding change probabilities in differential channels by Chunfang Yang, Yuhan Kang, Fenlin Liu, Xiaofeng Song, Jie Wang, Xiangyang Luo

“…Then, the embedding change probability of each element in the differential channels is added to the corresponding co-occurrence matrix bin to emphasize the interference of the residuals in textured regions to the improved co-occurrence matrix feature. …”
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A Fractal Curve-Inspired Framework for Enhanced Semantic Segmentation of Remote Sensing Images by Xinhua Wang, Botao Yuan, Zhuang Li, Heqi Wang

“…The classification and recognition of features play a vital role in production and daily life; however, the current semantic segmentation of remote sensing images is hampered by background interference and other factors, leading to issues such as fuzzy boundary segmentation. …”
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ROLLING BEARING FAULT DIAGNOSIS BASED ON LMD AND ICA by CHEN ChongYang, XIONG BangShu, HUANG JianPing, MO Yan, LI XinMin

“…For the problem of Local Mean Decomposition（ LMD） was easily affected by noise interference when in the extraction of fault features,a rolling bearing fault diagnosis method which based on LMD and Independent Component Analysis（ ICA） was proposed. …”
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An Analysis Method of Principal Components of Power Quality Based on Fast S-transform by MAN Weishi, ZHANG Zhiyu, XI Lei

“…The simulation results show that the feature components of the FST module coefficients for voltage disturbances are focused on low-frequency band, so that the algorithm has the advantages of high accuracy, short runtime and somewhat anti-interference ability. …”
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Application of MCKD-cyclic Domain Demodulation Method in Gearbox Fault Diagnosis by Wang Zhijian, Wang Junyuan, Zeng Zhiqiang, Zhang Jiping

“…The cross- term interference caused by multi- modulator and multi- carrier makes it limited the use of the cyclic autocorrelation demodulation. …”
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BCSM-YOLO: An Improved Product Package Recognition Algorithm for Automated Retail Stores Based on YOLOv11 by Pingqing Hou, Shaoze Huang

“…Firstly, introducing the Space-to-Depth Convolution (SPD-Conv) can maximize the preservation of detailed information such as commodity texture and shape in the downsampling stage, which provides a rich information base for the subsequent feature extraction. Then, the Convolutional Block Attention Module (CBAM) screens the processed data, adaptively focuses on the key regions, and suppresses the background interference. …”
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Research on Rolling Bearing Fault Diagnosis Using Improved Majorization-Minimization-Based Total Variation and Empirical Wavelet Transform by Yangli Ou, Shuilong He, Chaofan Hu, Jiading Bao, Wenjie Li

“…The majorization-minimization-based total variation (TV-MM) denoising algorithm effectively removes the noise interference from the signal and highlights the related feature information. …”
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Causal Intervention-Based Multimodal Class-Incremental Learning Network for 3D Model Classification and Retrieval by Qiang Li, Qiu-Yang Ma, Ning Zhang, Wei-Zhi Nie

“…It introduces an alternating modality freezing strategy to isolate parameter updates between geometric (point cloud) and visual (multi-view) modalities, thereby suppressing cross-modal gradient interference. Furthermore, a dynamic feature anchoring loss is utilized to constrain feature space drift and maintain cross-task consistency. …”
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