Football sports video tracking and detection technology based on YOLOv5 and DeepSORT by Bin Wang

“…First, the model is improved with lightweight network architecture and attention mechanism is introduced to improve feature extraction capability and target detection accuracy. …”
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High-Voltage CVT Fault Diagnosis Based on Effective Data Recognition and Multi-dimensional Information Fusion by Huishan ZHANG

“…Subsequently, fuzzy theory is utilized for feature-level information fusion, and the variance contribution values of common factors are taken as input parameters for the membership function to identify the fault types of CVT, thus achieving the accurate diagnosis of high-voltage CVT faults. …”
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A bearing fault diagnosis method based on hybrid artificial intelligence models. by Lijie Sun, Xin Tao, Yanping Lu

“…Addressing the issue of that the difficulty of incipient weak signals feature extraction influences the rolling bearing diagnosis accuracy, an efficient bearing fault diagnostic technique, a proposition is forwarded for hybrid artificial intelligence models, which integrates Improved Harris Hawks Optimization (IHHO) into the optimization of Deep Belief Networks and Extreme Learning Machines (DBN-ELM). …”
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Rolling Bearing Fault Diagnosis Based on VMD-DWT and HADS-CNN-BiLSTM Hybrid Model by Luchuan Shao, Bing Zhao, Xutao Kang

“…Subsequently, the denoised signals undergo multimodal feature fusion through depthwise separable convolution, triple attention mechanisms, and BiLSTM temporal modeling. …”
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An Effective Strategy of Object Instance Segmentation in Sonar Images by Pengfei Shi, Huanru Sun, Qi He, Hanren Wang, Xinnan Fan, Yuanxue Xin

“…However, the noise interference, low resolution, and blurred edges bring more significant challenges for sonar image instance segmentation. …”
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Small target detection of bearing surface defects based on improved YOLOv5s. by Haisong Xu, Xiaolin Shi, Han Zhang, Fan Yang, Yun Chen

“…However, traditional detection methods have problems such as insufficient feature extraction for small targets and sensitivity to background interference. …”
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DM-YOLO: improved YOLOv9 model for tomato leaf disease detection by Abudukelimu Abulizi, Junxiang Ye, Halidanmu Abudukelimu, Wenqiang Guo

“…Specifically, firstly, lightweight dynamic up-sampling DySample is incorporated into the feature fusion backbone network to enhance the ability to extract features of small lesions and suppress the interference from the background environment; secondly, the MPDIoU loss function is used to enhance the learning of the details of overlapping lesion margins in order to improve the accuracy of localizing overlapping lesion margins. …”
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Weighted Filter Bank and Regularization Common Spatial Pattern-Based Decoding Algorithm for Brain-Computer Interfaces by Jincai Ye, Jiajie Zhu, Shoulin Huang

“…This study provides a new approach to addressing the issues of individual differences and noise interference in EEG signals.…”
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Optimized decomposition and identification method for multiple power quality disturbances by Wang Zhaoqing, Chang Yanzhao, Chen Jianlei, Bao Weiyu

“…The OSVM strategically employs distinct kernel functions to augment the discriminability of the feature set. The synergy of IVMD and OSVM enables the detection of multiple PQDs, remarkably even with a minimal amount of training data. …”
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Hybrid Self-Attention Transformer U-Net for Fourier Single-Pixel Imaging Reconstruction at Low Sampling Rates by Haozhen Chen, Hancui Zhang, Bo Zou, Long Wu

“…Fourier Single-Pixel Imaging exhibits significant advantages over conventional imaging techniques, including high interference resistance, broad spectral adaptability, nonlocal imaging capability, and long-range detection. …”
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A Noise-Robust Deep-Learning Framework for Weld-Defect Detection in Magnetic Flux Leakage Systems by Junlin Yang, Senxiang Lu

“…However, the acquired MFL signals are affected by field noise, such as electromagnetic interference and mechanical vibrations, which degrade the performance of the developed models. …”
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Assessing distortion in carbon fiber woven fabrics based on machine vision by Shiyue Li, Quanzhou Yao, Lin Ye

“…A back-lighting imaging system was designed to minimize surface reflection interference, enabling high-quality fabric image acquisition. …”
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The siRNA Non-seed Region and Its Target Sequences Are Auxiliary Determinants of Off-Target Effects. by Piotr J Kamola, Yuko Nakano, Tomoko Takahashi, Paul A Wilson, Kumiko Ui-Tei

“…RNA interference (RNAi) is a powerful tool for post-transcriptional gene silencing. …”
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Improving Multisensor Positioning of Land Vehicles with Integrated Visual Odometry for Next-Generation Self-Driving Cars by Muhammed Tahsin Rahman, Tashfeen Karamat, Sidney Givigi, Aboelmagd Noureldin

“…However, in area such as urban cores, parking lots, and under dense foliage, which are all commonly frequented by AVs, GNSS signals suffer from blockage, interference, and multipath. These effects cause high levels of errors and long durations of service discontinuity that mar the performance of current systems. …”
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ISLRWR: A network diffusion algorithm for drug-target interactions prediction. by Lu Sun, Zhixiang Yin, Lin Lu

“…Moreover, after excluding the interference of homologous proteins (popular drugs or targets may lead to inflated prediction results), the ISLRWR algorithm still showed a significant performance improvement.…”
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Observation of a Fano Resonance at 92 meV (13.5 µm) in Al_0.2Ga_0.8N/GaN-Based Quantum Cascade Emitters by Daniel Hofstetter, Andreas D. Wieck, Hans Beck, David P. Bour

“…In order to observe this type of resonance in electro-luminescence, a spectrally narrow feature must interact with a broad, quasi-continuous emission. …”
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Apvit: ViT with adaptive patches for scene text recognition by Ning Zhang, Ce Li, Zongshun Wang, Jialin Ma, Zhiqiang Feng

“…Abstract Scene texts in nature exhibit varied colors, which serve as a significant distinguishing feature that effectively suppresses background interference. …”
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CFAR-DP-FW: A CFAR-Guided Dual-Polarization Fusion Framework for Large-Scene SAR Ship Detection by Tianjiao Zeng, Tianwen Zhang, Zikang Shao, Xiaowo Xu, Wensi Zhang, Jun Shi, Shunjun Wei, Xiaoling Zhang

“…These challenges are twofold: the detection of extremely small ships is often hindered by inadequate feature extraction, and the presence of inshore ships is obscured by pronounced land-based interference, both of which lead to reduced detection accuracy. …”
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Cloud Removal in Full-disk Solar Images Using Deep Learning by Zhenhong Shang, Peng Du, Zhenping Qiang, Runxin Li

“…Quantitative and qualitative experimental results demonstrate that the proposed method effectively removes complex cloud interference while preserving solar features, significantly improving the quality of observed data and outperforming existing solar image cloud removal methods. …”
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Robust audio authenticity detection based on One-Class learning by LIANG Ziqi, ZHANG Xulong, WANG Jianzong, XIAO Jing

“…In addition, to address the scarcity of fake voice data, the more versatile and robust self-supervised model Wav2vec2 was introduced for feature extraction, further improving the recognition accuracy of the model when faced with unknown attacks. …”
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