Sensor Fault Detection and Classification Using Multi-Step-Ahead Prediction with an Long Short-Term Memoery (LSTM) Autoencoder 由 Md. Nazmul Hasan, Sana Ullah Jan, Insoo Koo

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Deep Learning Autoencoder Study on ECG Signals 由 Dandi Mochamad Reza, Satria Mandala, Salim M. Zaki, Eileen Su Lee Ming

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Seismic Reflection Analysis of AETA Electromagnetic Signals 由 Zhenyu Bao, Shanshan Yong, Xin’an Wang, Chao Yang, Jinhan Xie, Chunjiu He

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The Prediction of the Remaining Useful Life of Rotating Machinery Based on an Adaptive Maximum Second-Order Cyclostationarity Blind Deconvolution and a Convolutional LSTM Autoencod... 由 Yangde Gao, Zahoor Ahmad, Jong-Myon Kim

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LSTM-Autoencoder-Based Incremental Learning for Industrial Internet of Things 由 Atallo Kassaw Takele, Balazs Villanyi

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Multistep Forecasting of Power Flow Based on LSTM Autoencoder: A Study Case in Regional Grid Cluster Proposal 由 Fachrizal Aksan, Yang Li, Vishnu Suresh, Przemysław Janik

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Klasifikasi Nyeri pada Video Ekspresi Wajah Bayi Menggunakan DCNN Autoencoder dan LSTM 由 Yosi Kristian, I Ketut Eddy Purnama, Effendy Hadi Sutanto, Lukman Zaman, Esther Irawati Setiawan, Mauridhi Hery Purnomo

主題: “...neural network, dcnn, lstm, autoencoder, klasifikasi nyeri, ekspresi wajah bayi...”
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Anomaly Detection in Fractal Time Series with LSTM Autoencoders 由 Lyudmyla Kirichenko, Yulia Koval, Sergiy Yakovlev, Dmytro Chumachenko

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Sensor and Component Fault Detection and Diagnosis for Hydraulic Machinery Integrating LSTM Autoencoder Detector and Diagnostic Classifiers 由 Ahlam Mallak, Madjid Fathi

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LSTM-Autoencoder Based Anomaly Detection Using Vibration Data of Wind Turbines 由 Younjeong Lee, Chanho Park, Namji Kim, Jisu Ahn, Jongpil Jeong

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TimeTector: A Twin-Branch Approach for Unsupervised Anomaly Detection in Livestock Sensor Noisy Data (TT-TBAD) 由 Junaid Khan Kakar, Shahid Hussain, Sang Cheol Kim, Hyongsuk Kim

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Objective Falls Risk Assessment Using Markerless Motion Capture and Representational Machine Learning 由 Sean Maudsley-Barton, Moi Hoon Yap

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Estimation of Frequency-Dependent Impedances in Power Grids by Deep LSTM Autoencoder and Random Forest 由 Azam Bagheri, Massimo Bongiorno, Irene Y. H. Gu, Jan R. Svensson

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GCN-Based LSTM Autoencoder with Self-Attention for Bearing Fault Diagnosis 由 Daehee Lee, Hyunseung Choo, Jongpil Jeong

主題: “...long short-term memory (LSTM) autoencoder...”
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Design of an improved model using federated learning and LSTM autoencoders for secure and transparent blockchain network transactions 由 R. Vijay Anand, G. Magesh, I. Alagiri, Madala Guru Brahmam, Balamurugan Balusamy, Chithirai Pon Selvan, Haya Mesfer Alshahrani, Masresha Getahun, Ben Othman Soufiene

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RSSI-Based MAC-Layer Spoofing Detection: Deep Learning Approach 由 Pooria Madani, Natalija Vlajic

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A Combined Semi-Supervised Deep Learning Method for Oil Leak Detection in Pipelines Using IIoT at the Edge 由 Christos Spandonidis, Panayiotis Theodoropoulos, Fotis Giannopoulos

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