Výsledky vyhledávání - "Convolutional LSTM autoencoder"

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 Autor Gao, Yangde, Ahmad, Zahoor, Kim, Jong-Myon

“…) and a convolutional LSTM autoencoder to achieve the feature extraction, health index analysis, and RUL prediction for rotating machinery…”
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A deep learning approach for error detection and quantification in extrusion-based bioprinting Autor Bonatti, Amedeo Franco, Vozzi, Giovanni, Kai Chua, Chee, De Maria, Carmelo

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

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

“… In this paper, we present StepEncog, a convolutional LSTM autoencoder model trained on fMRI voxels…”
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A Robust Deep Learning Model to Predict Epileptic Seizures based on Electroencephalographic (EEG) Signals Autor Prasad, Himayavardhini Jagath, Ramkumar, G.

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

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

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

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

“…Video anomalies detection is the intersection of anomaly detection and visual intelligence. It has commercial applications in surveillance, security,…”
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A Preliminary Study on Pattern Reconstruction for Optimal Storage of Wearable Sensor Data Autor Mahfuz, Sazia, Zulkernine, Farhana

“…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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Deep Learning Interference Cancellation in Wireless Networks Autor Zhou, Yiming, Samiee, Ashkan, Zhou, Tingyi, Jalali, Bahram

“…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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Unsupervised Feature Learning for Audio Analysis Autor Meyer, Matthias, Beutel, Jan, Thiele, Lothar

“… 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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