CD4C: Change Detection for Remote Sensing Image Change Captioning by Xiliang Li, Bin Sun, Zhenhua Wu, Shutao Li, Hu Guo

“…The C-Stream leverages the visual change information provided by the mask to enhance the ability of CD4C to capture foreground visual change features at both the image and feature levels. The N-Stream incorporates a pseudofeature generation module designed to mitigate the interference caused by poor change detection results. …”
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DMSA-Net: a deformable multiscale adaptive classroom behavior recognition network by Chunyu Dong, Jing Liu, Shenglong Xie

“…Moreover, there are occlusions and scale differences in the front and back rankings, which can easily cause confusion and interference with target features in the detection process, greatly limiting the accurate recognition ability of existing visual algorithms for classroom behavior. …”
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CA-STIM: an interpolation model with spatio-temporal evolution characteristics and cross-attention mechanism for 2D island morphology sequences by Peng Zhang, Wenzhou Wu, Shaochen Shi, Fengyu Li, Fenzhen Su

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RFAG-YOLO: A Receptive Field Attention-Guided YOLO Network for Small-Object Detection in UAV Images by Chengmeng Wei, Wenhong Wang

“…However, detecting small objects in UAV images remains a formidable challenge due to factors such as a low resolution, complex background interference, and significant scale variations, which collectively degrade the quality of feature extraction and limit detection performance. …”
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Rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention by ZHANG Changfan, XU Yifu, HE Jing, YANG Haonan

“…In respect of large noise interference of wheel tread and insufficient feature fusion of traditional detection algorithms, in order to achieve fast and accurate detection of wheel tread defects, a method for rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention was proposed. …”
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A Novel Low-Rank Embedded Latent Multi-View Subspace Clustering Approach by Sen Wang, Lian Chen, Zhijian Liang, Qingyang Liu

“…To alleviate these issues, we present a latent multi-view representation learning model based on low-rank embedding by implicitly uncovering the latent consistency structure of data, which allows us to achieve robust and efficient multi-view feature fusion. In particular, we utilize low-rank constraints to construct a unified latent subspace representation and introduce an adaptive noise suppression mechanism that significantly enhances robustness against outliers and noise interference. …”
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HGCS-Det: A Deep Learning-Based Solution for Localizing and Recognizing Household Garbage in Complex Scenarios by Houkui Zhou, Chang Chen, Zhongyi Xia, Qifeng Ding, Qinqin Liao, Qun Wang, Huimin Yu, Haoji Hu, Guangqun Zhang, Junguo Hu, Tao He

“…However, due to the interference of complex environments, coupled with the influence of the irregular features of garbage, garbage detection in complex scenarios still faces significant challenges. …”
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Research on Detection Technology of Wind Turbine Blade AnomalyBased on Audio Data by HU Kaikai, CHEN Yanan, CHEN Gang, SHU Hui, LI Ziyuan

“…By installing a pickup on the wind turbine, analyzing and mining the collected wind turbine audio data, and based on the multi classification machine learning model, it explores a set of audio data feature analysis and pattern recognition methods. …”
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Occlusion Vehicle Target Recognition Method Based on Component Model by Haorui Han, Hanshan Li

“…Therefore, based on the distribution features of vehicle components, this paper proposes a two-stage VSRS-VCFM net occlusion vehicle target recognition method. …”
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Semi-Supervised Atmospheric Turbulence Mitigation Based on Hybrid Models by Wenhao Chu, Zhi Cheng, Lixin He

“…Secondly, a simple convolutional neural network containing a lightweight feature extraction residual module was used for deblurring. …”
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Hierarchical Convolution-Transformer Framework for Gear Fault Diagnosis Under Severe Noise by Qiushi He, Bo Kang, Shanshan Fan, Xueyi Li

“…In addition, a dual-stage squeeze-and-excitation mechanism recalibrates feature channels to suppress noise interference and enhance robustness. …”
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Image Matching Algorithm for Transmission Towers Based on CLAHE and Improved RANSAC by Ruihua Chen, Pan Yao, Shuo Wang, Chuanlong Lyu, Yuge Xu

“…First, the improved AKAZE enhances image contrast using Contrast-Limited Adaptive Histogram Equalization (CLAHE), which highlights target features and improves robustness against environmental interference. …”
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A Novel Pseudo-Siamese Fusion Network for Enhancing Semantic Segmentation of Building Areas in Synthetic Aperture Radar Images by Mengguang Liao, Longcheng Huang, Shaoning Li

“…Next, the encoded features were reconstructed through skip connections and transposed convolution operations to obtain discriminative features of the building areas. …”
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HiDRA-DCDNet: Dynamic Hierarchical Attention and Multi-Scale Context Fusion for Real-Time Remote Sensing Small-Target Detection by Jiale Wang, Zhe Bai, Ximing Zhang, Yuehong Qiu, Fan Bu, Yuancheng Shao

“…The HiDRA mechanism implements a dual-phase feature enhancement process: channel competition through bottleneck compression for discriminative feature selection, followed by spatial-semantic reweighting for foreground–background decoupling. …”
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Research on SPAD Inversion of Rice Leaves at a Field Scale Based on Machine Vision and Leaf Segmentation Techniques by Bailin Yue, Yong Jin, Shangrong Wu, Jieyang Tan, Youxing Chen, Hu Zhong, Guipeng Chen, Yingbin Deng

“…Then, the color features of leaf images were extracted. Seven color features highly correlated with SPAD were selected via the Pearson correlation coefficient and recursive feature elimination optimization. …”
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HFEF²-YOLO: Hierarchical Dynamic Attention for High-Precision Multi-Scale Small Target Detection in Complex Remote Sensing by Yao Lu, Biyun Zhang, Chunmin Zhang, Yifan He, Yanqiang Wang

“…However, achieving high-precision detection of small objects against complex backgrounds remains challenging due to insufficient feature representation and background interference. …”
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Multipath and Deep Learning-Based Detection of Ultra-Low Moving Targets Above the Sea by Zhaolong Wang, Xiaokuan Zhang, Weike Feng, Binfeng Zong, Tong Wang, Cheng Qi, Xixi Chen

“…Without suppressing interferences, the proposed method uses both target and multipath information for detection based on their distinguishable image features and deep learning (DL) techniques. …”
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Research on Improved YOLO11 for Detecting Small Targets in Sonar Images Based on Data Enhancement by Xiaochuan Wang, Zhiqiang Zhang, Xiaodong Shang

“…Existing sonar target detection methods suffer from low efficiency and accuracy due to sparse target features and significant noise interference in sonar images. …”
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Lithology classification integrating multi-source remote sensing data after vegetation suppression: a case study from Inner Mongolia Autonomous Region, China by Jiaxin Lu, Ling Han, Junfeng Wang, Liangzhi Li, Zhaode Xia

“…A vegetation coverage-based image filtering method was introduced to minimize vegetation interference in multispectral images, while an improved water cloud model mitigated interference in SAR backscattering images. …”
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A PEDESTRIAN STEP COUNTING PARAMETER DETECTION METHOD AIDED WITH ANGULAR VELOCITY INFORMAITON by WANG Ping, ZHANG GuangPeng, ZHANG YanShun, HUANG ShuFeng, YAO Juan

“…In 27 experiments,which pedestrian walked certain steps and interference of activities ups and downs in-situ were brought in,the average accuracy rate of peak detection method and this method was 85. 8%,98. 84% respectively. …”
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