Design of an Intelligent Driver-Passenger Monitoring System for Metro Trains Based on Device-Edge-Cloud Integration by FENG Jian, FANG Peng, ZHAO Haibo, ZHANG Mingshuai

“…Addressing the issue of insufficient monitoring of driver operations in violation of rules and abnormal passenger conditions in existing crew management systems, this paper proposes a smart driver-passenger monitoring system featuring device-edge-cloud integration for metro trains. …”
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Do Petanque Sports Athletes in Jawa Tengah Need Android-Based Applications for Training Program Implementation? by Taufiq Hidayah, Rivan Saghita Pratama, Nasuka Nasuka, Setya Rahayu, Irwan Budiono, Sugiharto Sugiharto, Ali MD Nadzalan, Abdul Hafidz, Septyaningrum Putri Purwoto, Limpad Nurrachmad

“… The purpose of this study was to analyze the needs of athletes regarding monitoring the implementation of training programs for Android-based athletes and trainers. …”
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Cross-modal learning with multi-modal model for video action recognition based on adaptive weight training by Qingguo Zhou, Yufeng Hou, Rui Zhou, Yan Li, JinQiang Wang, Zhen Wu, Hung-Wei Li, Tien-Hsiung Weng

“…In this study, an effective Vision-Language action recognition adaptation was implemented based on few-shot examples spanning different modalities. …”
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Effective feature selection based HOBS pruned- ELM model for tomato plant leaf disease classification. by M Amudha, K Brindha

“…Firstly, an Elephant Herding Optimization (EHO) algorithm selects pertinent features for classification tasks. The classification module integrates a Hessian-based Optimal Brain Surgeon (HOBS) approach with a pruned Extreme Learning Machine (ELM), optimizing network parameters while reducing computational complexity. …”
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Feature engineering for fault detection and diagnosis in Power Transmission Lines using a tree-based approach by Hassan N. Noura, Zaid Allal, Ola Salman, Khaled Chahine

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Optimization of EEG-based wheelchair control: machine learning, feature selection, outlier management, and explainable AI by Amr M. Hamed, Abdel-Fattah Attia, Heba El-Behery

“…This study proposes an optimized classification framework that evaluates ten machine learning (ML) models, emphasizing ensemble methods, feature selection (FS), and outlier utilization. The dataset, comprising 2869 samples and 141 features, was processed using Recursive Feature Elimination (RFE) and correlation thresholds (CTs), achieving a peak accuracy of 69% with Extra Trees after FS. …”
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The LETBP feature descriptor based fish species classification using Kepler optimization with Extreme Learning Machine by Annalakshmi GANESAN, Sakthivel Murugan SANTHANAM

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A Beam Hardening Artifact Correction Method for CT Images Based on VGG Feature Extraction Networks by Hong Zhang, Zhaoguang Ma, Da Kang, Min Yang

“…To mitigate beam hardening artifacts, this paper proposes a correction method based on the VGG16 feature extraction network. Continuous convolutional layers automatically extract relevant features of beam hardening artifacts, establish a nonlinear mapping between artifact-affected and artifact-free images, and progressively enhance the model’s ability to understand and represent complex image features through stacked layers. …”
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Complex Texture Contour Feature Extraction of Cracks in Timber Structures of Ancient Architecture Based on YOLO Algorithm by Jian Ma, Weidong Yan, Guoqi Liu, Shiyu Xing, Siqi Niu, Tong Wei

“…In the comparing process, we mainly have discussed the index performance of the three models in terms of training time, loss function, recall rate, and mAP value. …”
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PDAM-FAQ: Paraphrasing-Based Data Augmentation and Mixed-Feature Semantic Matching for Low-Resource FAQs by Dongsheng Wang, Liming Wang, Kun Tang, Qile Bo

“…Additionally, this paper presents a mixed-feature semantic matching model based on SimBERT. …”
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BBDetector: Intelligent border binary detection in IoT device firmware based on a multidimensional feature model. by Shudan Yue, Guimin Zhang, Qingbao Li, Wenbo Zhang, Xiaonan Li, Weihua Jiao

“…Finally, a border binary detection model (XLC-R) was obtained by training with feature vectors. We tested and evaluated BBDetector on two datasets. …”
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Abnormal Sound Detection of Wind Turbine Gearboxes Based on Improved MobileFaceNet and Feature Fusion by Yuelong Liang, Haorui Liu, Yayu Chen

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Ship crack detection method based on lightweight fast convolution and bidirectional weighted feature fusion network by Chong WANG, Yuhui ZHU

“…ObjectiveAs traditional ship crack detection methods based on artificial visual inspection and ultrasonic methods in ship repair and inspection processes have the characteristics of low efficiency, high cost and high danger, a ship crack detection method based on deep learning is proposed. …”
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A Drilling Debris Tracking and Velocity Measurement Method Based on Fine Target Feature Fusion Optimization by Jinteng Yang, Yu Bao, Zumao Xie, Haojie Zhang, Zhongnian Li, Yonggang Li

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Establishment of nomogram prediction model for patients with chronic obstructive pulmonary disease based on Lasso feature screening by Shuyi Zhang, Jiaojiao Sha, Tao Jiang, Zhou Lu, Yulin Shi, Jiatuo Xu

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Customized Spectro-Temporal CNN Feature Extraction and ELM-Based Classifier for Accurate Respiratory Obstruction Detection by M. Muthulakshmi, K. Venkatesan, Syarifah Bahiyah Rahayu, K. L. Nayana Sree

“…The proposed CNN-enhanced time-frequency features powered the ELM-based framework, yielding a test accuracy of 97.5% for the unseen test data considered. …”
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Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction by Diqing Fan, Chenjiang Yu, Ling Sha, Haifeng Zhang, Xintian Liu

“…Then, an image processing algorithm suitable for laser welding of automotive brake joints was studied, including pre-processing steps such as image smoothing, image enhancement, threshold segmentation, and morphological processing, to extract feature parameters of weld defects. On this basis, a welding seam defect detection and classification system based on the cascade classifier and AdaBoost algorithm was designed, and efficient recognition and classification of welding seam defects were achieved by training the cascade classifier. …”
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Multi-machine learning model based on radiomics features to predict prognosis of muscle-invasive bladder cancer by Bin Wang, Zijian Gong, Peide Su, Guanghao Zhen, Tao Zeng, Yinquan Ye

“…Abstract Objective This study aims to construct a survival prognosis prediction model for muscle-invasive bladder cancer based on CT imaging features. Materials and methods A total of 91 patients with muscle-invasive bladder cancer were sourced from the TCGA and TCIA dataset and were divided into a training group (64 cases) and a validation group (27 cases). …”
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Face recognition method based on convolutional neural network and distributed computing by Liu Yanyu, Zhang Liu, Zhang Dawei

“…Face attribute recognition is also widely used in human–computer interaction, train stations, and other fields because face attributes are rich in information. …”
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ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning by Raiyan Jahangir, Muhammad Nazrul Islam, Md. Shofiqul Islam, Md. Motaharul Islam

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