Search Results - "convolutional LSTM autoencoder"

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  1. 1

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

    ISSN: 1424-8220, 1424-8220
    Published: Switzerland MDPI AG 09.04.2024
    Published in Sensors (Basel, Switzerland) (09.04.2024)
    “…) and a convolutional LSTM autoencoder to achieve the feature extraction, health index analysis, and RUL prediction for rotating machinery…”
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    Journal Article
  2. 2

    A deep learning approach for error detection and quantification in extrusion-based bioprinting by Bonatti, Amedeo Franco, Vozzi, Giovanni, Kai Chua, Chee, De Maria, Carmelo

    ISSN: 2214-7853, 2214-7853
    Published: Elsevier Ltd 2022
    Published in Materials today : proceedings (2022)
    “…Quality control in extrusion-based bioprinting (EBB) represents a crucial step to: i) reduce the trial-and-error process and associated material consumption,…”
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    Journal Article
  3. 3

    Video Anomaly Detection using Variational Convolutional LSTM Autoencoder by Sahoo, Sandhya Rani, Kokkiligadda, Jaideep, Dash, Ratnakar

    Published: IEEE 26.05.2023
    “…Unintentional, inadvertent, unanticipated, or unplanned events are referred to as anomalies or abnormal events. Anomaly detection in surveiiance video has been…”
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    Conference Proceeding
  4. 4

    StepEncog: A Convolutional LSTM Autoencoder for Near-Perfect fMRI Encoding by Oota, Subba Reddy, Rowtula, Vijay, Gupta, Manish, Bapi, Raju S.

    ISSN: 2161-4407
    Published: IEEE 01.07.2019
    “… In this paper, we present StepEncog, a convolutional LSTM autoencoder model trained on fMRI voxels…”
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    Conference Proceeding
  5. 5

    A Robust Deep Learning Model to Predict Epileptic Seizures based on Electroencephalographic (EEG) Signals by Prasad, Himayavardhini Jagath, Ramkumar, G.

    Published: IEEE 16.12.2024
    “… This paper presents a novel approach Deep Neural Optimum Transformation (DNOT) for epileptic seizure prediction based on EEG signals using a hybrid deep learning model, Convolutional LSTM AutoEncoder (CLSTM-AE…”
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    Conference Proceeding
  6. 6

    DAST-Net: Dense visual attention augmented spatio-temporal network for unsupervised video anomaly detection by Kommanduri, Rangachary, Ghorai, Mrinmoy

    ISSN: 0925-2312, 1872-8286
    Published: Elsevier B.V 28.04.2024
    Published in Neurocomputing (Amsterdam) (28.04.2024)
    “… For capturing temporal patterns, the framework employs a Convolutional LSTM Autoencoder (ConvLSTM-AE) module, enabling effective learning and representation of temporal dependencies in video data…”
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    Journal Article
  7. 7

    A deep learning approach for anomaly detection in large-scale Hajj crowds by Aldayri, Amnah, Albattah, Waleed

    ISSN: 0178-2789, 1432-2315
    Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2024
    Published in The Visual computer (01.08.2024)
    “…Hajj is an annual Islamic event attended by millions of pilgrims every year from around the globe. It is considered to be the biggest religious event that…”
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    Journal Article
  8. 8

    Enhanced Short-Term GHI Prediction using Cloud-Aware Deep Autoencoder Network by N, Kalpalathika, Salih, Jumin, P, Lakshmi, Siddiqi, Nihal, A, Bhuvaneswari

    Published: IEEE 04.08.2025
    “… Visible-band satellite imagery is used to generate spatiotemporal cloud mask cubes, which are encoded via a Convolutional LSTM Autoencoder to learn cloud evolution patterns…”
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    Conference Proceeding
  9. 9

    Visual anomaly detection in video by variational autoencoder by Waseem, Faraz, Rafael Perez Martinez, Wu, Chris

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 08.03.2022
    Published in arXiv.org (08.03.2022)
    “…Video anomalies detection is the intersection of anomaly detection and visual intelligence. It has commercial applications in surveillance, security,…”
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    Paper
  10. 10

    A Preliminary Study on Pattern Reconstruction for Optimal Storage of Wearable Sensor Data by Mahfuz, Sazia, Zulkernine, Farhana

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 25.02.2023
    Published in arXiv.org (25.02.2023)
    “…Efficient querying and retrieval of healthcare data is posing a critical challenge today with numerous connected devices continuously generating petabytes of…”
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    Paper
  11. 11

    Deep Learning Interference Cancellation in Wireless Networks by Zhou, Yiming, Samiee, Ashkan, Zhou, Tingyi, Jalali, Bahram

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 11.09.2020
    Published in arXiv.org (11.09.2020)
    “…With the crowding of the electromagnetic spectrum and the shrinking cell size in wireless networks, crosstalk between base stations and users is a major…”
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    Paper
  12. 12

    Unsupervised Feature Learning for Audio Analysis by Meyer, Matthias, Beutel, Jan, Thiele, Lothar

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 11.12.2017
    Published in arXiv.org (11.12.2017)
    “… It incorporates the two following novel contributions: First, an audio frame predictor based on a Convolutional LSTM autoencoder is demonstrated, which is used for unsupervised feature extraction…”
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    Paper