Rotating Machinery Fault Detection Using Support Vector Machine via Feature Ranking by Harry Hoa Huynh, Cheol-Hong Min

“…Based on feature extraction and raking, eleven predictors were extracted leading to reduced training complexity, while achieving a high classification accuracy of 99.7% could be obtained in less than half of the training time.…”
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DRFW-TQC: Reinforcement Learning for Robotic Strawberry Picking with Dynamic Regularization and Feature Weighting by Anping Zheng, Zirui Fang, Zixuan Li, Hao Dong, Ke Li

“…Concurrently, deep learning-based pose control algorithms suffer from inherent training instability, slow convergence rates, and inefficient learning processes in complex environments characterized by high-density fruit clusters and occluded picking scenarios. …”
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Administrative legal means for the organization of getting higher education and the training of scientific and teaching staff by S. M. Rukavishnikov

“…Considering the mechanism of administrative legal regulation in the sphere of higher education and training of scientific and teaching staff it is necessary to study the main approaches to the definition, direction and specific features of the relevant administrative legal remedies. …”
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Strategies for upgrading the training of personnel at the Shanghai Municipal and district Centers for Disease Control and Prevention by HE Yongchao, SUI Mengyun, LI Yugang

“…ObjectiveTo investigate the current status of personnel training, barriers and bottlenecks at Shanghai Municipal and district Centers for Disease Control and Prevention (hereinafter referred to as" CDC"), so as to provide a reference basis for the formulation of training policies that are consistent with the CDC’s staff development path, characteristics of the era, and features of Shanghai mega⁃city.MethodsQuestionnaire survey and qualitative interview were used to collect the data, covering the basic information of the research subjects, as well as training status, needs, barriers and problems. …”
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A Lightweight Pavement Defect Detection Algorithm Integrating Perception Enhancement and Feature Optimization by Xiang Zhang, Xiaopeng Wang, Zhuorang Yang

“…To address the current issue of large computations and the difficulty in balancing model complexity and detection accuracy in pavement defect detection models, a lightweight pavement defect detection algorithm, PGS-YOLO, is proposed based on YOLOv8, which integrates perception enhancement and feature optimization. …”
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Dynamic Bidirectional Feature Enhancement Network for Thin Cloud Removal in Remote Sensing Images by Yu Wang, Hao Chen, Ye Zhang, Guozheng Li

“…Then, we present a dynamic enhancement-based bidirectional information flow module to model the dynamic interaction between multitask features, guiding detail recovery and feedback for optimized cloud removal features. …”
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FADLEC: feature extraction and arrhythmia classification using deep learning from electrocardiograph signals by Sumita Lamba, Satender Kumar, Manoj Diwakar

“…Next, training, validation, and testing sets are created from the extracted feature set. …”
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GUIDE: a prospective cohort study for blood-based early detection of gastrointestinal cancers using targeted DNA methylation and fragmentomics sequencing by Ao Huang, De-Zhen Guo, Zhi-Xi Su, Yun-Shi Zhong, Liang Liu, Zhi-Guo Xiong, Dong-Li He, Bin Yan, Quan-Lin Li, Zhen Feng, Wen-Quan Wang, Pin-Xiang Lu, Meng-Jiang He, Zhi-Peng Qi, Qi Guo, Jian-Wen Cheng, Shi-Yu Zhang, Wei Guo, Qing Li, Guo-Yong Lin, Hui-Chuan Sun, Shuang-Jian Qiu, Qi-Ye He, Jia Fan, Ajay Goel, Rui Liu, Gang Jin, Xin-Rong Yang, Jian Zhou

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Adaptive weights learning in CNN feature fusion for crime scene investigation image classification by Liu Ying, Zhang Qian Nan, Wang Fu Ping, Chiew Tuan Kiang, Lim Keng Pang, Zhang Heng Chang, Chao Lu, Lu Guo Jun, Ling Nam

“…However, in existing work, as the weights in feature fusion do not change after the training phase, it may produce inaccurate image features which affect classification results. …”
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Multiple model visual feature embedding and selection method for an efficient ocular disease classification by Isha Kansal, Vikas Khullar, Preeti Sharma, Supreet Singh, Junainah Abd Hamid, A. Johnson Santhosh

“…Among the tested approaches, the “Combined Data” strategy utilizing features from all three models achieved the best results, with the BiLSTM classifier attaining 100% accuracy, precision, and recall on the training set, and over 98% performance on the validation set. …”
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Terrain and Atmosphere Classification Framework on Satellite Data Through Attentional Feature Fusion Network by Antoni Jaszcz, Dawid Połap

“…The proposed classifier architecture is the main element of the modeled framework for satellite data analysis, which is based on the possibility of training depending on the client’s desire. …”
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Transformers and large language models are efficient feature extractors for electronic health record studies by Kevin Yuan, Chang Ho Yoon, Qingze Gu, Henry Munby, A. Sarah Walker, Tingting Zhu, David W. Eyre

“…A zero-shot OpenAI GPT4 model matches the performance of traditional NLP models without the need for labelled training data (F1 = 0.71 and 0.86) and a fine-tuned GPT3.5 model achieves similar performance to the fine-tuned BERT-based model (F1 = 0.95 and 0.97). …”
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An XAI Approach to Melanoma Diagnosis: Explaining the Output of Convolutional Neural Networks with Feature Injection by Flavia Grignaffini, Enrico De Santis, Fabrizio Frezza, Antonello Rizzi

“…XAI has been successfully applied to DNNs for skin lesion image classification but never when additional information is incorporated during network training. This field is still unexplored; thus, in this paper, we aim to provide a method to explain, qualitatively and quantitatively, a convolutional neural network model with feature injection for melanoma diagnosis. …”
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Looming Detection in Complex Dynamic Visual Scenes by Interneuronal Coordination of Motion and Feature Pathways by Bo Gu, Jianfeng Feng, Zhuoyi Song

“…Existing insect‐inspired looming detection models typically rely on either motion‐pathway or feature‐pathway signals, yet both are susceptible to dynamic visual scene interference. …”
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A MODEL FOR ASSESSING SHIPPING SAFETY WITHIN PROJECT-ORIENTATED RISK MANAGEMENT BASED ON HUMAN ELEMENT by Svitlana ONYSHCHENKO, Yuriy BYCHKOVSKY, Oleksiy MELNYK, Oleg ONISHCHENKO, Martin JURKOVIČ, Viacheslav RUBSKYI, Kostiantyn LIASHENKO

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Effective Feature Selection on Transfer Deep Learning Algorithm for Thyroid Nodules Ultrasound Detection by Ghufran Basim Alghanimi, Hadeel Aljobouri, Khaleel Akeash Alshimmari, Rasha Massoud

“…Consequently, the addition of feature selection)FS) to the deep learning method enhances the results by reducing the high features and the time needed for training the dataset. …”
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Semi-Supervised Remote Sensing Building Change Detection with Joint Perturbation and Feature Complementation by Zhanlong Chen, Rui Wang, Yongyang Xu

“…To address this issue, we propose a feature multi-scale information interaction and complementation semi-supervised method based on consistency regularization (MSFG-SemiCD), which includes a multi-scale feature fusion-guided change detection network (MSFGNet) and a semi-supervised update method. …”
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Motion feature extraction using magnocellular-inspired spiking neural networks for drone detection by Jiayi Zheng, Jiayi Zheng, Yaping Wan, Xin Yang, Hua Zhong, Minghua Du, Gang Wang, Gang Wang

“…To design and train the MG-SNN, we propose a new backpropagation method called Dynamic Threshold Multi-frame Spike Time Sequence (DT-MSTS), and establish a dataset for the training and validation of MG-SNN, effectively extracting and updating visual motion features. …”
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Refined Anchor-Free Model With Feature Enhancement Mechanism for Ship Detection in Infrared Images by Yunlong Gao, Chuan Wu, Ming Ren, Yang Feng

“…Besides, for improving precision in multiscale ship detection task, we propose the refined feature alignment and label assignment redesign modules, the former is used during the feature fusion process to cope with the problem of contextual misalignment, and the latter is introduced to refrain from the disadvantageous effect of the fuzzy areas in the process of model training. …”
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Hierarchical Feature Fusion and Enhanced Attention Mechanism for Robust GAN-Generated Image Detection by Weinan Zhang, Sanshuai Cui, Qi Zhang, Biwei Chen, Hui Zeng, Qi Zhong

“…To address this issue, this paper proposes a deepfake image-detection network based on feature aggregation and enhancement. The key innovation of the proposed method lies in the integration of two modules: the Feature Aggregation Module (FAM) and the Attention Enhancement Module (AEM). …”
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