Partial Discharge Data Augmentation and Pattern Recognition Method Based on DAE-GAN by Xin Du, Jun Qi, Jiyi Kang, Zezhong Sun, Chunxin Wang, Jun Xie

“…Lastly, the model’s discriminator is fine-tuned with augmented and balanced training data to enable PD pattern recognition. The DAE-GAN method is used to augment data and recognize patterns in experimental PD signals. …”
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Pattern Recognition of Signals for the Fault-Slip Type of Rock Burst in Coal Mines by X. S. Liu, J. Tan, Y. L. Tan, S. C. Hu

“…Results showed that the signals patterns proposed are in good agreement with the process of the fault-slip type of rock burst. The pattern recognition can provide a basis for the early warning and the implementation of relief measures of the fault-slip type of rock burst.…”
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Human Motion Representation and Motion Pattern Recognition Based on Complex Fuzzy Theory by Xiangkun Li, Guoqing Sun, Yifei Li

“…For the error monitoring of key gait events, the screen window is used to filter the repeated recognition events in a certain period of time, which greatly improves the recognition accuracy and provides important gait information for motion pattern recognition. The similarity matching is performed on each template, the correct rate of motion feature extraction is 90.2%, and the correct rate of motion pattern recognition is 96.3%, which verifies the feasibility and effectiveness of human motion recognition based on fuzzy theory. …”
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Entropy-Based Ensemble of Convolutional Neural Networks for Clothes Texture Pattern Recognition by Reham Al-Majed, Muhammad Hussain

“…Automatic clothes pattern recognition is important to assist visually impaired people and for real-world applications such as e-commerce or personal fashion recommendation systems, and it has attracted increased interest from researchers. …”
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Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition by Wenjia Liu, Bo Chen, R. Andrew Swartz

“…This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. …”
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Advanced Feature Selection for Simplified Pattern Recognition within the Damage Identification Framework by G. Manson, R.J. Barthorpe

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Intelligent Pattern Recognition Using Distributed Fiber Optic Sensors for Smart Environment by Brian Pamukti, Shofuro Afifah, Shien-Kuei Liaw, Jiun-Yu Sung, Daping Chu

Subjects: “…pattern recognition…”
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Visualized pattern recognition optimization for apple mechanical damage by laser relaxation spectroscopy by Junbo Lian, Ling Ma, Xincan Wu, Ting Zhu, Quan Liu, Yuqi Sun, Zhenghao Mei, Jingyuan Ning, Haifen Ye, Guohua Hui, Xiongwei Lou

“…The data was pretreated using the Min-Max standardization algorithm and analyzed using pattern recognition models including the depth extreme learning machine (DELM), SSA-DELM (optimized by the sparrow search algorithm), and backpropagation (BP) neural networks. …”
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Medical Pattern Recognition: Applying an Improved Intuitionistic Fuzzy Cross-Entropy Approach by Kuo-Chen Hung

“…An illustrative example for medical pattern recognition demonstrates the usefulness of this study. …”
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Inhibition SNN: unveiling the efficacy of various lateral inhibition learning in image pattern recognition by Xin Liu

“…Abstract This study presents an enhanced spiking neural network (SNN) with inhibition, referred to as Inhibition SNN, which advances the field of pattern recognition through efficient event-driven computation. …”
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Pattern Recognition Receptors in Periodontal Disease: Molecular Mechanisms, Signaling Pathways, and Therapeutic Implications by Elisabetta Ferrara, Francesco Mastrocola

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The Double-Layer Clustering Based on K-Line Pattern Recognition Based on Similarity Matching by Xinglong Li, Qingyang Liu, Yanrong Hu, Hongjiu Liu

“…The research presented in this paper aims to overcome the limitations of traditional candlestick pattern analysis, which is constrained by fixed pattern definitions, quantity limitations, and subjectivity in pattern recognition, thus improving its effectiveness in dynamic market environments. …”
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Pattern Recognition via the Toll-Like Receptor System in the Human Female Genital Tract by Kaei Nasu, Hisashi Narahara

“…Rapid innate immune defenses against microbial infection usually involve the recognition of invading pathogens by specific pattern-recognition receptors recently attributed to the family of Toll-like receptors (TLRs). …”
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Near infrared spectroscopy discrimination and pattern recognition of Chinese Pogostemon cablin and Agastache rugosa by Songping Lan, Jialiang Cai, Hongning Zhao, Dong Wang, Shengguo Ji

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An IMU-based machine learning approach for daily behavior pattern recognition in dairy cows by Hua-Ta Liang, Shu-Wen Hsu, Jih-Tay Hsu, Chia-Jui Tu, Yi-Chu Chang, Chua Teck Jian, Ta-Te Lin

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Probabilistic Prediction of Mine Dynamic Disaster Risk Based on Multiple Factor Pattern Recognition by Tianwei Lan, Chaojun Fan, Sheng Li, Hongwei Zhang, Adrian Sergaevich Batujin

“…Application of the prediction method of mine dynamic disaster factors based on pattern recognition, to improve the implementation of mine dynamic disaster prediction and controlling measures, guarantees the safe production of the coal mine.…”
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THE BRAIN AS A MULTI-LAYERED MAP. SCALES AND REFERENCE POINTS FOR PATTERN RECOGNITION IN NEUROIMAGING by Margarita Zaleshina, Alexander Zaleshin

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THE BRAIN AS A MULTI-LAYERED MAP. SCALES AND REFERENCE POINTS FOR PATTERN RECOGNITION IN NEUROIMAGING by Margarita Zaleshina, Alexander Zaleshin

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An approach for traffic pattern recognition integration of ship AIS data and port geospatial features by Gaocai Li, Xinyu Zhang, Lingling Jiang, Chengbo Wang, Ruining Huang, Zhensheng Liu

“…However, the current research focuses on the spatiotemporal behavioral feature clustering of ship trajectory points or segments while lacking consideration for multiple factors that influence ship behavior, such as ship static and maritime geospatial features, resulting in insufficient precision in ship traffic pattern recognition. This study proposes a ship traffic pattern recognition method that considers multi-attribute trajectory similarity (STPMTS), which considers ship static feature, dynamic feature, port geospatial feature, as well as semantic relationships between these features. …”
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Detecting respiratory diseases using machine learning-based pattern recognition on spirometry data by Ahmed I. Taloba, R.T. Matoog

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