A Systematic Review of CNN Architectures, Databases, Performance Metrics, and Applications in Face Recognition by Andisani Nemavhola, Colin Chibaya, Serestina Viriri

“…This study provides a comparative evaluation of face recognition databases and Convolutional Neural Network (CNN) architectures used in training and testing face recognition systems. …”
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Addressing data imbalance in collision risk prediction with active generative oversampling by Li Li, Xiaoliang Zhang

“…We also propose a method for dynamically adjusting the training epochs of the generator and discriminator based on loss differences to achieve balance in model training. …”
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A Random Forest-Based Predictive Model for Student Academic Performance: A Case Study in Indonesian Public High Schools by Rifa Andriani Saputri, Asrianda Asrianda, Lidya Rosnita

“…The research methodology involved data preprocessing, training the Random Forest model using entropy and information gain to construct decision trees, and performance evaluation using metrics such as accuracy, precision, and recall. …”
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Image-Based Malware Detection Using Deep CNN Models by hawraa omran musa, Muhanad Tahrir Younis

“…The approach requires resizing malware images to a resolution of 64 x 64 pixels and normalizing these images for model training. The selection of a 64 × 64 size frame reduces network complexity while speeding up training without sacrificing important information. …”
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Introduction to the Special Thematic Issue "Virtual Reality and Eye Tracking" by Béatrice Hasler, Rudolf Groner

“…It addresses a variety of issues and topics, such as practical guidelines for VR-based eye tracking technologies, exploring new research avenues, evaluation of gaze-based assessments, and training interventions.  …”
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Applications of AI-Based Models for Online Fraud Detection and Analysis by Antonis Papasavva, Samantha Lundrigan, Ed Lowther, Shane Johnson, Enrico Mariconti, Anna Markovska, Nilufer Tuptuk

“…Results We discuss the state-of-the-art AI and NLP techniques used to analyse various online fraud categories; the data sources used for training the AI and NLP models; the AI and NLP algorithms and models built; and the performance metrics employed for model evaluation. …”
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Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost by Hualiang Fang, Jiaqi Liao, Shuo Huang, Maojie Zhang

“…Factors such as driving and charging habits, road traffic, and charging station equipment are taken into account. The training sample data are established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. …”
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DESIGNING OF INDIVIDUAL EDUCATIONAL TRAJECTORIES IN THE MASTER DEGREE PROGRAM FOR TEACHERS by Irina Igropulo, Alina Dunaenko

“…The characteristic of the algorithm for designing an individual educational trajectory is presented, including the diagnostic, target, content, technological, evaluation components. …”
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Surgical correction of hallux valgus deformity in children with cerebral palsy by Ilker Abdullah Sarikaya, Ali Seker, Ozan Ali Erdal, Mehmet Ali Talmac, Muharrem Inan

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Classification of Salmon Freshness In Situ Using Convolutional Neural Network by Juan Miguel L. Valeriano, Carlos C. Hortinela

“…Using the convolutional neural network (CNN) algorithm, we determined salmon fillet freshness in this study. …”
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Helicopter reconnaissance indicators sensitivity analysis based on machine learning by JIANG Xinyi, LOU Benchao, ZENG Weiping

“…Secondly, sensitivity analysis of helicopter reconnaissance mission effectiveness is achieved through task planning, constructing indicator systems, collecting relevant data, evaluating effectiveness, and using machine learning algorithms for modeling and training. …”
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Assessment of binary prediction of fraudulent advertisements in ATS candidate tracking cloud systems by V. V. Ligi-Goryaev, G. A. Mankaeva, T. B. Goldvarg, S. S. Muchkaeva, E. N. Dzhakhnaeva

“…The performance of the trained models can be evaluated using various metrics such as accuracy, precision, and recall. …”
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Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach by Doo-Seop Choi, Taeguen Kim, Boojoong Kang, Eul Gyu Im

“…As a result of the evaluation, our framework maintained high classification accuracy while improving model training speed by approximately 17.47% and testing speed by approximately 19.44%. …”
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The Enterprise School Readiness Prediction System (ESRPS) Uses Machine Learning to Assess Children's Readiness for Entering Elementary School by Muhammad Choerul Umam, Cicilia Dyah Sulistyaningrum I., Dydik Kurniawan, Priyono Tri Febrianto

“…This study aims to develop and evaluate the Enterprise School Readiness Prediction System (ESRPS) to predict children's readiness for elementary school using machine learning algorithms.  …”
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Development and validation of an interpretable risk prediction model for the early classification of thalassemia by Jin-Xin Lai, Jia-Wei Tang, Shan-Shan Gong, Ming-Xiong Qin, Yu-Lu Zhang, Quan-Fa Liang, Li-Yan Li, Zhen Cai, Liang Wang

“…Current diagnostic methods mainly rely on sophisticated equipment and specifically trained technicians. This study aims to identify and genotype thalassemia by applying machine learning (ML) algorithms to routine blood parameters. …”
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Geoinformation monitoring of the educational risk in educational institutions of higher education by Aleksandr N. Kolesenkov, Dmitry S. Zhuravlyov

“…Evaluation of the characteristics of training directions is carried out through the application of the classification method, the decision tree is used, which allows to order many specialties and training directions in a hierarchical, consistent structure according to the established rules. …”
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Lithology Identification of Buried Hill Reservoirs Based on Support Vector Machine by GAO Yongde, WU Jinbo, SUN Dianqiang

“…Compared with the conventional crossplot method and Random Forest algorithm, the SVM algorithm shows significant advantages in this area and effectively addresses the complex lithology identification challenges of the potential mountain reservoir.…”
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The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

“…Moreover, challenges such as algorithmic bias, generalizability across diverse populations, and the necessity for clinician training must be carefully considered. …”
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The assessment of sports performance by grip pressure using flexible piezoresistive pressure sensors in seven sports events by Kebao Zhang, Beilei Guo, Mingchuan Yang, Yi Jia, Kehu Zhang, Liu Wang

“…Finally, the K-Nearest Neighbor (KNN) of artificial intelligence algorithms is employed to identify differences for 400 strokes of tennis players in interval training session. …”
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Robust pose estimation for non-cooperative space objects based on multichannel matching method by Zhaoxiang Zhang, Yuelei Xu, Jianing Song

“…A space object dataset including nine different types of non-cooperative targets with 11,565 samples is developed for model training and evaluation. Extensive experimental results indicate that the proposed method demonstrates robust performance across various challenging conditions, including different object types, diverse illumination scenarios, varying rotation rates, and different image resolutions. …”
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