An Incremental Learning Ensemble Strategy for Industrial Process Soft Sensors by Huixin Tian, Minwei Shuai, Kun Li, Xiao Peng

“…The ability to handle large amounts of data incrementally and efficiently is indispensable for modern machine learning (ML) algorithms. According to the characteristics of industrial production process, we address an ILES (incremental learning ensemble strategy) that incorporates incremental learning to extract information efficiently from constantly incoming data. …”
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Explainable Machine Learning-Based Prediction Model for Diabetic Nephropathy by Jing-Mei Yin, Yang Li, Jun-Tang Xue, Guo-Wei Zong, Zhong-Ze Fang, Lang Zou

“…We compare four machine learning algorithms, including extreme gradient boosting (XGB), random forest, decision tree, and logistic regression, by AUC-ROC curves, decision curves, and calibration curves. …”
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Research on the Application of Deep Learning Methods in the Field of Image Classification by Peng Yuhui

“…The application of deep learning methods such as Convolutional Neural Network, Recurrent Neural Networks and Long Short-Term Memory in image classification is also discussed. …”
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Review on Deep Learning and Neural Network Implementation for Emotions Recognition by Renas Rajab Asaad

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The Influence of Power Relations on Teenagers’ Learning Process in an EFL Class by Yolima Forero-Rocha, Luis Fernando Gómez-Rodríguez

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A review of deep learning for brain tumor analysis in MRI by Felix J. Dorfner, Jay B. Patel, Jayashree Kalpathy-Cramer, Elizabeth R. Gerstner, Christopher P. Bridge

“…Abstract Recent progress in deep learning (DL) is producing a new generation of tools across numerous clinical applications. …”
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(EFL) Learners’ Perspectives on Vocabulary Learning through Reading and Listening by Sara Jamal Mohammed Faraj

“…It was also found that there is no significant difference between both genders and age groups in vocabulary learning.…”
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Methodological Aspects of Learning of Work with a Multi-user Database by V. Oskerko, Z. Punchik

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Optical fiber eavesdropping detection method based on machine learning by Xiaolian CHEN, Yi QIN, Jie ZHANG, Yajie LI, Haokun SONG, Huibin ZHANG

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Architectural planning robot driven by unsupervised learning for space optimization by Zhe Zhang, Yuchun Zheng

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Psychometrics of an Elo-based large-scale online learning system by Hanke Vermeiren, Joost Kruis, Maria Bolsinova, Han L.J. van der Maas, Abe D. Hofman

“…This method proves to be highly advantageous in online learning environments. Computerized adaptive practice (CAP) endeavors to present learners with items that are well-suited to their individual ability levels, with the ultimate goal of enhancing motivation and optimizing learning outcomes. …”
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The Impact of Online Learning System on Students Affected with Stroke Disease by Sobia Wassan, Chen Xi, Tian Shen, Kamal Gulati, Kinza Ibraheem, Rana M. Amir Latif Rajpoot

“…Neuroimaging investigates SD’s impact on attention, working memory, mood, and hippocampal learning. We analyzed how this data enriches our mechanistic understanding of these alterations and the clinical illnesses linked with sleep disruption. …”
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Research and development of hash retrieval technology based on deep learning by Mingwen YUAN, Jiangbo QIAN, Yihong DONG, Huahui CHEN

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Driver Lane-Changing Behavior Prediction Based on Deep Learning by Cheng Wei, Fei Hui, Asad J. Khattak

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Sharing Worldviews: Learning in Encounter for Common Values in Diversity (WEL) by Vahdeddin Şimşek

“…Son olarak birkaç profesör, uzman ve eğitimci, Avrupa çapında öğretmenlerin hizmet içi eğitiminde ve öğretmen adaylarının eğitiminde sadece teorik olarak değil, aynı zamanda Farklılıklar İçerisinde Ortak Değerler için Karşılaşma Yoluyla Öğrenme kavramları içerisinde okullarda ve sınıflarda nasıl uygulanacağı noktasında uygulama eğitimlerini kapsayan SHARING WORLDVIEWS: LEARNING IN ENCOUNTER FOR COMMON VALUES IN DIVERSITY (WEL) (Erasmus+ KA220-HED- Yükseköğretim Alanında İşbirliği ve Ortaklık Projesi) başlıklı projede bir araya gelmiştir.…”
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Application of Rotating Machinery Fault Diagnosis Based on Deep Learning by Wei Cui, Guoying Meng, Aiming Wang, Xinge Zhang, Jun Ding

“…After a brief review of early fault diagnosis methods, this paper focuses on the method models that are widely used in deep learning: deep belief networks (DBN), autoencoders (AE), convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), and transfer learning methods are summarized from the two aspects of principle and application in the field of fault diagnosis of rotating machinery. …”
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Feature Extraction and Classification of Music Content Based on Deep Learning by Qianqiu Shi, Young Chun Ko

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Analysis of the Application of Deep Learning in Model Reconstruction of Ancient Buildings by Zhihong Wang, Hao Xiong

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A Deep Learning Model for the Thermospheric Nitric Oxide Emission by Xuetao Chen, Jiuhou Lei, Dexin Ren, Wenbin Wang

Subjects: “…deep learning…”
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Construction of a mobile game for learning Libras - Guess teaching by João A. F. Furquim, Flávia B. Blum Haddad, Débora G. Ribeiro Dias

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