Student Engagement Recognition: Comprehensive Analysis Through EEG and Verification by Image Traits Using Deep Learning Techniques by Ajitha Sukumaran, Arun Manoharan

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Short‐Term Prediction of the Dst Index and Estimation of Efficient Uncertainty Using a Hybrid Deep Learning Network by Ruyao Wang, Jianhui Wang, Tuo Liang, Huixiong Zhang

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A deep learning ICDNET architecture for efficient classification of histopathological cancer cells using Gaussian noise images by Hui Zong, Wenlong An, Xin Chen, Zhanhui Yang, Heng Zhou, Xiangchao Liu, Jianchu Lin, Chuanyue Zong

“…The integration of deep learning technology has greatly improved diagnostic accuracy and efficiency. …”
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Deep learning of noncontrast CT for fast prediction of hemorrhagic transformation of acute ischemic stroke: a multicenter study by Huanhuan Ren, Haojie Song, Shaoguo Cui, Hua Xiong, Bangyuan Long, Yongmei Li

Subjects: “…Deep learning…”
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Archaeological Site Detection: Latest Results from a Deep Learning Based Europe Wide Hillfort Search by Jürgen Landauer, Simon Maddison, Giacomo Fontana, Axel G. Posluschny

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A Deep Learning-Based Approach for the Detection of Various Internet of Things Intrusion Attacks Through Optical Networks by Nouman Imtiaz, Abdul Wahid, Syed Zain Ul Abideen, Mian Muhammad Kamal, Nabila Sehito, Salahuddin Khan, Bal S. Virdee, Lida Kouhalvandi, Mohammad Alibakhshikenari

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Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study by Xin Xiong, Linghui Xiang, Litao Chang, Irene XY Wu, Shuzhen Deng

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A feature extraction method for hydrofoil attached cavitation based on deep learning image semantic segmentation algorithm by Yingyuan Liu, Yizhi Wang, Kang An

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The classification of absence seizures using power-to-power cross-frequency coupling analysis with a deep learning network by A.V. Medvedev, B. Lehmann

“…New artificial intelligence methods such as deep learning neural networks can provide powerful tools for automated analysis of EEG. …”
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Vehicle Turn Pattern Counting and Short Term Forecasting Using Deep Learning for Urban Traffic Management System by Sundarakrishnan Narayanan, Sohan Varier, Tarun Bhupathi, Manaswini Simhadri Kavali, Mohana, P. Ramakanth Kumar, K. Sreelakshmi

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Optimizing multi label student performance prediction with GNN-TINet: A contextual multidimensional deep learning framework. by Xiaoyi Zhang, Yakang Zhang, Angelina Lilac Chen, Manning Yu, Lihao Zhang

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Using a YOLO Deep Learning Algorithm to Improve the Accuracy of 3D Object Detection by Autonomous Vehicles by Ramavhale Murendeni, Alfred Mwanza, Ibidun Christiana Obagbuwa

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Advanced in Islanding Detection and Fault Classification for Grid-Connected Distributed Generation using Deep Learning Neural Network by Rusvaira Qatrunnada, Novizon Novizon, Mardini Hasanah, Tuti Angraini, Anton Anton

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Applying Deep Learning Methods on Time-Series Data for Forecasting COVID-19 in Egypt, Kuwait, and Saudi Arabia by Nahla F. Omran, Sara F. Abd-el Ghany, Hager Saleh, Abdelmgeid A. Ali, Abdu Gumaei, Mabrook Al-Rakhami

“…This paper presents a comparative study of two deep learning methods to forecast the confirmed cases and death cases of COVID-19. …”
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Exploration of the optimal deep learning model for english-Japanese machine translation of medical device adverse event terminology by Ayako Yagahara, Masahito Uesugi, Hideto Yokoi

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Precision Medicine Assessment of the Radiographic Defect Angle of the Intrabony Defect in Periodontal Lesions by Deep Learning of Bitewing Radiographs by Patricia Angela R. Abu, Yi-Cheng Mao, Yuan-Jin Lin, Chien-Kai Chao, Yi-He Lin, Bo-Siang Wang, Chiung-An Chen, Shih-Lun Chen, Tsung-Yi Chen, Kuo-Chen Li

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Application of deep learning for real-time detection, localization, and counting of the malignant invasive weed Solanum rostratum Dunal by Shifeng Du, Yashuai Yang, Hongbo Yuan, Man Cheng

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External Validation of Deep Learning Models for Classifying Etiology of Retinal Hemorrhage Using Diverse Fundus Photography Datasets by Pooya Khosravi, Nolan A. Huck, Kourosh Shahraki, Elina Ghafari, Reza Azimi, So Young Kim, Eric Crouch, Xiaohui Xie, Donny W. Suh

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Hybrid Deep-Learning Framework Based on Gaussian Fusion of Multiple Spatiotemporal Networks for Walking Gait Phase Recognition by Tao Zhen, Jian-lei Kong, Lei Yan

“…In this study, an effective hybrid deep-learning framework based on Gaussian probability fusion of multiple spatiotemporal networks (GFM-Net) is proposed to detect different gait phases from multisource IMU signals. …”
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Retracted: The Design of Critical Care Information System Supporting Clinical Decision Based on Deep Learning Recognition Method by International Transactions on Electrical Energy Systems

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