Search Results - Bidirectional LSTM autoencoder

Improved network intrusion classification with attention-assisted bidirectional LSTM and optimized sparse contractive autoencoders by Bi, Jing, Guan, Ziyue, Yuan, Haitao, Zhang, Jia

“… SABD integrates Stacked sparse contractive autoencoders (SSCA), Attention-based Bidirectional long-term and short-term memory (LSTM…”
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Prediction model of sparse autoencoder-based bidirectional LSTM for wastewater flow rate by Huang, Jianying, Yang, Seunghyeok, Li, Jinhui, Oh, Jeill, Kang, Hoon

“… In this paper, we present the design of the Sparse Autoencoder-based Bidirectional long short-term memory (SAE-BLSTM…”
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An Attention-Driven and Autoencoder-Based Bidirectional LSTM for Long Interval Gap-Filling of a Water Treatment Process Data Set by Gudla, Rohan, Cheng, Jinxiang, Chang, Ni-Bin

“… a Bidirectional Long Short-Term Memory Autoencoder with multi-head Attention Mechanism (BiLSTM-AAM). The multi-head attention mechanism allows the model to focus…”
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A novel approach for automatic acoustic novelty detection using a denoising autoencoder with bidirectional LSTM neural networks by Marchi, Erik, Vesperini, Fabio, Eyben, Florian, Squartini, Stefano, Schuller, Bjorn

“… In our approach auditory spectral features are processed by a denoising autoencoder with bidirectional Long Short-Term Memory recurrent neural networks…”
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Optimizing dotted Arabic expiration date recognition with ARABEX: a convolutional autoencoder with bidirectional LSTM and CRNN approach by Zaki, Hozaifa, Soliman, Ghada

“…In this study, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using an Optimized Convolutional Autoencoder with a bidirectional LSTM…”
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Correlating the Ambient Conditions and Performance Indicators of the LoRaWAN via Surrogate Gaussian Process-Based Bidirectional LSTM Stacked Autoencoder by Bhat, Showkat Ahmad, Huang, Nen-Fu, Hussain, Imtiyaz, Sajjad, Uzair

“… In this research, a Bayesian surrogate Gaussian process-based bidirectional LSTM stacked autoencoder model (BSGP-BLSTM_SAE…”
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Tool wear monitoring for robotic milling based on multi-dimensional stacked sparse autoencoders and bidirectional LSTM networks with singularity features by Zhou, Chang’an, Zhang, Kaixing, Xu, Jiawei, Guo, Kai, Liu, Xin, Hu, Bingyin, Wang, Gang

“… The proposed tool wear monitoring method (TWM) relies on a sophisticated framework that integrates a multi-dimensional stacked sparse autoencoders (MD-SSAEs…”
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Correlating the Ambient Conditions and Performance Indicators of the LoRaWAN via Surrogate Gaussian Process based Bidirectional LSTM Stacked Autoencoder Showkat by Bhat, Showkat Ahmad, Huang, Nen Fu, Hussain, Imtiyaz, Sajjad, Uzair

“… In this research, a Bayesian surrogate Gaussian pr ocess based bidirectional LSTM stacked autoencoder model (BSGP BLSTMSAE…”
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Hybrid Cyber Defense Mechanism with PINN for Resilient and Reliable Control against Replay / FDI Attacks in DC Microgrid Systems by Machina, Venkata Siva Prasad, Koduru, Sriranga Suprabhath, Madichetty, Sreedhar, Mishra, Sukumar

“…) and replay attacks through a combination of bidirectional LSTM (Bi-LSTM) autoencoders for anomaly detection, cross-correlation analysis for replay attack identification, and a physics-informed neural network (PINN…”
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Video Anomaly Detection Based on 3D-CNN Autoencoder with Bidirectional LSTM by Sankaran, Mohan, Jooluri, Nagaraju, Subbusundaram, Balasundaram, Oggu, Vijaya Bhaskar, Meghana, A

“… To address these limitations, we propose an unsupervised deep learning-based foundation for anomaly detection, utilizing a hybrid model with 3D Convolutions and a Bidirectional Long Short-Term Memory (Bi-LSTM) model…”
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Hybrid Network Intrusion Detection with Stacked Sparse Contractive Autoencoders and Attention-based Bidirectional LSTM by Bi, Jing, Guan, Ziyue, Yuan, Haitao

“… SABD integrates Stacked sparse contractive autoencoders, Attention-based Bidirectional long-term and short-term memory (LSTM…”
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Anomaly Detection in Commercial Load Data Using Bidirectional LSTM and Autoencoders by Zhu, Feng, Li, Meng, Liu, Yijuan, Liu, Jiyan, Wang, Zhelong, Chen, Yunlong, Zhang, Xuemei

“…This study proposes an anomaly detection algorithm, employing Bidirectional Long Short-Term Memory (LSTM…”
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Transparent EEG Analysis: Leveraging Autoencoders, Bi-LSTMs, and SHAP for Improved Neurodegenerative Diseases Detection by Mouazen, Badr, Bendaouia, Ahmed, Bellakhdar, Omaima, Laghdaf, Khaoula, Ennair, Aya, Abdelwahed, El Hassan, De Marco, Giovanni

“…) and frontotemporal dementia (FTD). We propose a novel classification pipeline that combines autoencoders for feature extraction and bidirectional long short-term memory (Bi-LSTM…”
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Anomaly Detection for Sensor Signals Utilizing Deep Learning Autoencoder-Based Neural Networks by Esmaeili, Fatemeh, Cassie, Erica, Nguyen, Hong Phan T., Plank, Natalie O. V., Unsworth, Charles P., Wang, Alan

“… We developed autoencoder-based prediction models to automatically detect anomalous data recorded by three electrochemical aptasensors, with variations in the signals…”
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A Bidirectional Long Short-Term Memory Autoencoder Transformer for Remaining Useful Life Estimation by Fan, Zhengyang, Li, Wanru, Chang, Kuo-Chu

“…, such as natural languages. We adopt the encoder part of the full Transformer as the backbone of our framework, integrating it with a self-supervised denoising autoencoder that utilizes bidirectional LSTM for improved feature extraction…”
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Outfit Generation and Style Extraction via Bidirectional LSTM and Autoencoder by Nakamura, Takuma, Goto, Ryosuke

“…When creating an outfit, style is a criterion in selecting each fashion item. This means that style can be regarded as a feature of the overall outfit…”
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Predicting process quality in multi-stage manufacturing using AE-BilA: an autoencoder-BiLSTM with attention mechanism by Hady, Haider N, Hadi, Russul H, Hassoon, Omar Hashim, Hasan, Ahmed M, Humaidi, Amjad J

“…) has been proposed as a framework in which a stacked Long Short-Term Memory (LSTM) autoencoder is combined with a bidirectional LSTM enhanced by an Attention mechanism for predicting quality in multi-stage manufacturing processes (MMP…”
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Deep learning methods for forecasting COVID-19 time-Series data: A Comparative study by Zeroual, Abdelhafid, Harrou, Fouzi, Dairi, Abdelkader, Sun, Ying

“…•Results demonstrate the potential of deep learning models to forecast COVID19 data.•Results show the superior performance of the Variational AutoEncoder model…”
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Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach by Li, Rumeng, Hu, Baotian, Liu, Feifan, Liu, Weisong, Cunningham, Francesca, McManus, David D, Yu, Hong

“…Bleeding events are common and critical and may cause significant morbidity and mortality. High incidences of bleeding events are associated with…”
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Automatic Features Extraction from Time Series of Passive Microwave Images for Snowmelt Detection Using Deep-Learning–A Bidirectional Long-Short Term Memory Autoencoder (Bi-Lstm-Ae) Approach by Massamba, Bienvenu Sedin

“…The Antarctic surface snowmelt is prone to the polar climate and is common in its coastal regions. With about 90 percent of the planet's glaciers, if all of…”
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