Retracted: Construction of Personalized Learning Platform Based on Intelligent Algorithm in the Context of Industry Education Integration by Advances in Multimedia

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Robust Malware identification via deep temporal convolutional network with symmetric cross entropy learning by Jiankun Sun, Xiong Luo, Weiping Wang, Yang Gao, Wenbing Zhao

Subjects: “…learning (artificial intelligence)…”
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Retracted: Design and Construction of an Interactive Intelligent Learning System for English Learners in Higher Education Institutions by Advances in Multimedia

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Comparative Analysis of Federated and Centralized Learning Systems in Predicting Cellular Downlink Throughput Using CNN by Kukuh Nugroho, Hendrawan, Iskandar

Subjects: “…Federated learning…”
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Learning through mistakes in crisis management as a strategy of low losses in conditions of continuous uncertainty by T. V. Mokeeva

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Low-Shot Wall Defect Detection for Autonomous Decoration Robots Using Deep Reinforcement Learning by Fanyu Zeng, Xi Cai, Shuzhi Sam Ge

“…Finally, we train our method with deep reinforcement learning to learn the optimal detection policy. The experiments are implemented on a low-shot dataset in which images are collected from real decoration environments, and the experimental results show the proposed method can achieve fast convergence and learn the optimal detection policy for wall defect images.…”
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Examining the Impact of Self-concept on Adolescents’ Self-regulated Learning: A Predictive Modeling Approach by Patricia Ayllón-Salas, José L. Arco-Tirado, Francisco D. Fernández-Martín

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Deep Learning Based Dual Channel Banana Grading System Using Convolution Neural Network by Raghavendra S, Souvik Ganguli, P. Thirumarai Selvan, Mitali Madhusmita Nayak, Sushovan Chaudhury, Randell U. Espina, Isaac Ofori

“…Deep learning has recently been hailed as the most advanced computer vision technology for image classification. …”
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Learning model combined with data clustering and dimensionality reduction for short-term electricity load forecasting by Hyun-Jung Bae, Jong-Seong Park, Ji-hyeok Choi, Hyuk-Yoon Kwon

“…It has evolved from statistical methods to artificial intelligence-based techniques that use machine learning models. In this study, we investigate short-term load forecasting (STLF) for large-scale electricity usage datasets. …”
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Swarm learning with weak supervision enables automatic breast cancer detection in magnetic resonance imaging by Oliver Lester Saldanha, Jiefu Zhu, Gustav Müller-Franzes, Zunamys I. Carrero, Nicholas R. Payne, Lorena Escudero Sánchez, Paul Christophe Varoutas, Sreenath Kyathanahally, Narmin Ghaffari Laleh, Kevin Pfeiffer, Marta Ligero, Jakob Behner, Kamarul A. Abdullah, Georgios Apostolakos, Chrysafoula Kolofousi, Antri Kleanthous, Michail Kalogeropoulos, Cristina Rossi, Sylwia Nowakowska, Alexandra Athanasiou, Raquel Perez-Lopez, Ritse Mann, Wouter Veldhuis, Julia Camps, Volkmar Schulz, Markus Wenzel, Sergey Morozov, Alexander Ciritsis, Christiane Kuhl, Fiona J. Gilbert, Daniel Truhn, Jakob Nikolas Kather

“…Methods In this study, we present an integrated pipeline combining weakly supervised learning—reducing the need for detailed annotations—with local AI model training via swarm learning (SL), which circumvents centralized data sharing. …”
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Multi-Modal Social Robot Behavioural Alignment and Learning Outcomes in Mediated Child–Robot Interactions by Paul Baxter

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Multimedia development to improve character analysis thinking skills through value-based learning approaches by Arifin Arifin

“…The instruments used in this study were in-depth interviews, observation, and documentation of the learning process using the developed multimedia. The results showed that students, in general, can use this multimedia in the learning process. …”
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Path Optimization of Enterprise Network Innovation Performance Management Based on Deep Learning and Internet of Things by Peiran Xiong

“…This paper will explore the measurement scale of technology learning cost, and from the basic perspective of technology learning cost, deeply explore and analyze how enterprise technology innovation performance is affected by the strength of enterprise network relationship. …”
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Research on the Initial Fault Prediction Method of Rolling Bearings Based on DCAE-TCN Transfer Learning by Huaitao Shi, Yajun Shang, Xiaochen Zhang, Yinghan Tang

“…In this paper, a rolling bearing initial fault prediction model that is based on transfer learning and the DCAE-TCN is presented. Firstly, a deep autoencoder (DAE as the first two hidden layers and CAE as the last hidden layer) is used to extract fault features from the rolling bearing vibration signal data. …”
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New Media Marketing Strategy Optimization in the Catering Industry Based on Deep Machine Learning Algorithms by Zikang Peng

“…The communication module is connected with a deep machine learning algorithm system; that is, deep machine learning algorithm system is connected with a sales platform in communication. …”
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Intentionally-underestimated value function at terminal state for temporal-difference learning with mis-designed reward by Taisuke Kobayashi

Subjects: “…Temporal-difference learning…”
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Presentation of Machine Learning Approaches for Predicting the Severity of Accidents to Propose the Safety Solutions on Rural Roads by Mohammad Habibzadeh, Mahmoud Ameri, Hassan Ziari, Neda Kamboozia, Seyede Mojde Sadat Haghighi

“…In addition, both machine learning and statistical methods can be served as guidance for safety authorities to provide safety solutions, thereby leading to reducing accidents. …”
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Novel PCA-driven extreme machine learning for comprehensive modelling of metropolitan wastewater treatment systems by Vini Antony Grace N, Ghadah Aldehim, Nuha Alruwais, Prabakar T.N.

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Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models by Hongkun Fu, Jian Lu, Jian Li, Wenlong Zou, Xuhui Tang, Xiangyu Ning, Yue Sun

“…This study proposes a method for predicting yields in China’s major winter wheat-producing regions using MOD13A1 data and a deep learning model which incorporates an Improved Gray Wolf Optimization (IGWO) algorithm. …”
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Automatic skull segmentation of MRI volume, a deep learning model trained on synthetic data by Romain Valabregue, Mélanie Didier, Mathieu Santin, Éric Bardinet, Victor Giolland, Antoine Balzeau

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