Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting by Wensheng Dai, Jui-Yu Wu, Chi-Jie Lu

“…Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. …”
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FB-YOLOv8s: A fire detection algorithm based on YOLOv8s by Yuhang Liu, Chunjuan Bo, Chong Feng

“…Second, the Bi-directional Feature Pyramid Network (BiFPN) is incorporated to replace the Path Aggregation Network (PANet) in the neck network to enhance the model’s feature fusion capability. …”
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Discriminative graph regularized representation learning for recognition. by Jinshan Qi, Rui Xu

“…Feature extraction has been extensively studied in the machine learning field as it plays a critical role in the success of various practical applications. …”
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Expression Recognition Method Based on CBAM-DSC Network by SONG Wen bo, GAO Lu, MIAO Zhuang, LIN Ke zheng

“…Finally, the convolutional block attention module is added, which can make the network focus on the key information when extracting features, so that the extracted feature expression information is more accurate and more conducive to classification. …”
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Closure state measurement of final joint of the immersed tunnel of the Hong Kong-Zhuhai-Macao Bridge by SUO Xuhong, LIU Guohui, ZHANG Dejin, GUAN Minglei

“…Firstly, the measurement feature points are arranged on the end faces of the two pipe joints that form the closure, and the coordinates of the feature points in the pipe joint coordinate system are obtained by measurement. …”
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A novel pedestrian detection algorithm based on data fusion of face images by Jianhu Zheng, Jinshuan Peng

“…During the face recognition process, feature classification ability and reliability are determined by the feature extraction methods. …”
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Development of parameters for an industry-specific methodology for calculating the electric energy storage system for gas industry facilities by Ivan S. Tokarev

“…The methodology was tested at a typical gas industry facility – the Yarynskaya compressor station of OOO Gazprom Transgaz Ukhta, a characteristic feature of which is an autonomous power supply system. …”
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Analog Circuits Fault Diagnosis Using ISM Technique and a GA-SVM Classifier Approach by Sabah Kouachi, Nacerdine Bourouba, Kamel Mebarkia, Imad Laidani

“… This present work aims to contribute to the solution of the problems encountered in electronic circuits fault diagnosis. …”
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Fast Spectral Correlation Based on Sparse Representation Self-Learning Dictionary and Its Application in Fault Diagnosis of Rotating Machinery by Hongchao Wang, Wenliao Du

“…To address the above problems, an impulsive feature-enhanced method which combines fast spectral correlation (FSC) with sparse representation self-learning dictionary is proposed in the paper. …”
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Implementation of Random Forest Method with Information Gain Selection and Hyperparameter Tuning for Alzheimer’s Disease Classification by Riska Nuril Fadhila, Nurissaidah Ulinnuha, Dian Yuliati, Nurissaidah Ulinnuha, Dian Yuliati

“…Using the Random Forest method with information gain feature selection and hyperparameter tuning optimization, this study aims to determine the results of optimization with feature selection and hyperparameter tuning using Random Search and Grid Search to classify Alzheimer's medical record data consisting of 32 variables, including lifestyle factors, clinical measurements, cognitive and functional assessments, as well as symptoms that indicate Alzheimer's. …”
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A New Bearing Fault Diagnosis Method Based on Deep Transfer Network and Supervised Joint Matching by Chengyao Liu, Fei Dong, Kunpeng Ge, Yuanyuan Tian

“…In practical industrial environment, variable working condition can result in shifts in data distributions, and the labeled fault data in various working conditions is difficult to collect because rotating machines often works in normal status, and the insufficient labeled fault data brings data samples imbalance and performance degradation of intelligent fault diagnosis model. To overcome these problems, by integrating the superiority of deep learning method and feature-based transfer learning method, this work proposes an innovative cross-domain fault diagnosis framework based on deep transfer convolutional neural network and supervised joint matching. …”
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Fault diagnosis method for rolling bearings based on CWT-IDenseNet by Guangfei JIA, Hanwen LIANG, Jinqiu YANG, Zhe WU, Yuxin HAN

“…The SRM focused on the weight of feature channels, while CBAM enhanced the feature expression ability from the two dimensions of channel and space. …”
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A Hierarchical ViT With Dynamic Window Shift Unit and Curriculum Learning for Remote Sensing Image Scene Classification by Yi Liu, Xiang Wu, Jihuan Ren, Jiacun Wang, Yuming Bo, Yuanhao Wang

“…This method has better multiscale feature representation ability due to the improved hierarchical vision transformer structure, in which a feature map fusion layer produces feature maps of different sizes, and a window transformer block with dynamic window shift unit actively shifts to the local region with dense information, flexibly extracting and associating key features with multiscale in different input regions. …”
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Lightweight defect detection algorithm of tunnel lining based on knowledge distillation by Anfu Zhu, Jiaxiao Xie, Bin Wang, Heng Guo, Zilong Guo, Jie Wang, Lei Xu, SiXin Zhu, Zhanping Yang

“…Secondly, in the distillation process, the feature and output dimension results are fused to improve the detection accuracy, and the mask feature relationship is learned in the space and channel dimension to improve the real-time detection. …”
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Multitask semantic change detection guided by spatiotemporal semantic interaction by Yinqing Wang, Liangjun Zhao, Yueming Hu, Hui Dai, Yuanyang Zhang

“…STGNet enhances the ability to capture spatial details by introducing a Detail-Aware Path (DAP) and designs a Bidirectional Guidance Module for Spatial Detail and Semantic Information for adaptive feature selection, improving feature extraction capabilities in complex scenes. …”
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Delta-Adjust: Minimum Distance Interpolation by Ziad F. Doughan, Sari S. Itani

“…We present Delta-Adjust, a novel interpolation method that extends local neighborhood interpolation techniques by introducing per-feature neighbor selection and feature-vector difference bias adjustment. …”
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Data-Driven Battery Remaining Life Prediction Based on ResNet with GA Optimization by Jixiang Zhou, Weijian Huang, Haiyan Dai, Chuang Wang, Yuhua Zhong

“…Although data-driven methods show good prediction potential without the need to understand the reaction mechanism inside the battery, they face the problems of high data demand and feature redundancy that may reduce the model learning accuracy in practical applications. …”
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Real-time monitoring and optimization of machine learning intelligent control system in power data modeling technology by Qiong Wang, Zuohu Chen, Yongbo Zhou, Zhiyuan Liu, Zhenguo Peng

“…Recursive feature elimination method can be used for feature selection in the model, and multi-model integration method can be used for feature fusion. …”
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Cross-Domain Person Re-Identification Based on Multi-Branch Pose-Guided Occlusion Generation by Pengnan Liu, Yanchen Wang, Yunlong Li, Deqiang Cheng, Feixiang Xu

“…Aiming at the problems caused by a lack of feature matching due to occlusion and fixed model parameters in cross-domain person re-identification, a method based on multi-branch pose-guided occlusion generation is proposed. …”
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Advancing Ton-Bag Detection in Seaport Logistics with an Enhanced YOLOv8 Algorithm by Xiulin Qiu, Haozhi Zhang, Chang Yuan, Qinghua Liu, Hongzhi Yao

“…Finally, the C2f-ORECZ block based on a linear scaling layer is designed for the neck, which reduces the training overhead and strengthens the feature learning of the feature extraction network for the targets in the complex background of the harbor and adds the 160 × 160 scale detection head to strengthen small target detection abilities. …”
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