Search Results - Stacked LSTM encoder-decoder model

Development and implementation of real-time anomaly detection on tool wear based on stacked LSTM encoder-decoder model by Oshida, Taisuke, Murakoshi, Tomohiro, Zhou, Libo, Ojima, Hirotaka, Kaneko, Kazuki, Onuki, Teppei, Shimizu, Jun

“… In this study, we proposed a stacked LSTM encoder-decoder model for tool wear anomaly detection…”
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Cycle-level traffic conflict prediction at signalized intersections with LiDAR data and Bayesian deep learning by Wu, Peijie, Wei, Wei, Zheng, Lai, Hu, Zhenlin, Essa, Mohamed

“…•Bayesian-Multi-head Stacked-LSTM Encoder-Decoder is suggested as the optimal model. Real-time safety prediction models are vital in proactive road safety management strategies…”
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State of Charge Estimation of Lithium-Ion Batteries Using Stacked Encoder–Decoder Bi-Directional LSTM for EV and HEV Applications by Terala, Pranaya K., Ogundana, Ayodeji S., Foo, Simon Y., Amarasinghe, Migara Y., Zang, Huanyu

“… This method consists of using combined stacked bi-directional LSTM and encoder–decoder bi-directional long short-term memory architecture…”
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Evaluation of Deep Learning Models for Predicting the Concentration of Air Pollutants in Urban Environments by Tello-Leal, Edgar, Ramirez-Alcocer, Ulises Manuel, Macías-Hernández, Bárbara A., Hernandez-Resendiz, Jaciel David

“… (in their fractions PM2.5 and PM10) and carbon monoxide (CO) in consecutive hours. The proposed prediction models are based on recurrent neural…”
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An encoder-decoder based framework for hindi image caption generation by Singh, Alok, Singh, Thoudam Doren, Bandyopadhyay, Sivaji

“… In this paper, an encoder-decoder based architecture is proposed where Convolutional Neural Network (CNN…”
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Analyzing Sequences of Airspace States to Detect Anomalous Traffic Conditions by Habler, Edan, Shabtai, Asaf

“…The ADS-B system serves as a replacement for the current radar-based air traffic control systems. Although much effort and resources have been invested in…”
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DSLSTM: a deep convolutional encoder–decoder architecture for abnormality detection in video surveillance by Roka, Sanjay, Diwakar, Manoj

“… This paper proposes a novel two-stream spatial and temporal architecture called Deep Stacked LSTM (DSLSTM…”
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Stacked LSTM Model for Contextual Correlation Detection Among Multiple Emotions by Younas, Aqsa, Riaz, Shazia, Ali, Saqib, Khan, Rafiullah, Ullah, Mohib, Kwak, Daehan

“…Emotions are closely tied to human behavior and play a critical role in daily life. With the widespread use of social media, individuals frequently express…”
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Granger Causality-Based Forecasting Model for Rainfall at Ratnapura Area, Sri Lanka: A Deep Learning Approach by Saubhagya, Shanthi, Tilakaratne, Chandima, Lakraj, Pemantha, Mammadov, Musa

“… The identification of the optimal set of features for the LSTM model was conducted using Random Forest and Granger Causality tests…”
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A novel Encoder-Decoder structure for Time Series analysis based on Bayesian Uncertainty reduction by Llugsi, Ricardo, Yacoubi, Samira El, Fontaine, Allyx, Lupera, Pablo

“…In the present work, a novel Convolutional LSTM Encoder-Decoder structure for the implementation of Weather Forecast for the Andean city of Quito is presented…”
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Sentic Computing for Aspect-Based Opinion Summarization Using Multi-Head Attention with Feature Pooled Pointer Generator Network by Kumar, Akshi, Seth, Simran, Gupta, Shivam, Maini, Shivam

“…Neural sequence to sequence models have achieved superlative performance in summarizing text…”
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An Encoder-Decoder Deep Learning Approach for Multistep Service Traffic Prediction by Theodoropoulos, Theodoros, Maroudis, Angelos-Christos, Violos, John, Tserpes, Konstantinos

“… We examined four encoder-decoder DL architectures i) Stacked LSTMs…”
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Internal Flow Prediction in Arbitrary Shaped Channel Using Stream-Wise Bidirectional LSTM by Ko, Jaekyun, Choi, Wanuk, Lee, Sanghwan

“… Recent studies have stacked numerous convolutional layers to extract high-level feature maps, which are then used for the analysis of various shapes under differing conditions…”
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A Hybrid Method With Adaptive Sub-Series Clustering and Attention-Based Stacked Residual LSTMs for Multivariate Time Series Forecasting by Liu, Fagui, Lu, Yunsheng, Cai, Muqing

“… This paper focuses on those two challenges and proposes a new prediction method based on decomposition-ensemble framework called adaptive sub-series clustering-stacked residual LSTMs-multi-level attention mechanism (ASC-SRLSTMs-MLAttn…”
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A novel approach for detecting error measurements in a network of automatic weather stations by Llugsi, R., El Yacoubi, S., Fontaine, A., Lupera, P.

“…), LSTM stacked and a convolutional LSTM model with uncertainty error reduction. The analysis carried out exhibits a significant success with the methodology for three stations reaching error values between 0.98 C…”
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Advanced Methods of Power Load Forecasting

“… Models of LSTM neural networks, LSTM networks with a SESDA architecture, in even LSTM-CNN are used…”
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T5LSTM-RNN based Text Summarization Model for Behavioral Biology Literature by Chaurasia, Shivangi, Dasgupta, Debalay, Regunathan, Rajeshkhannan

“… For proper training of the LSTM model, the lengthy video and journal datasets are pre-processed using the T5 transformer model to generate a uniform training dataset…”
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Advanced Intelligent Control in Robots

“…Advanced intelligent control is a rapidly developing, complex and challenging field with significant practical importance and potential applications. The…”
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A Deep Learning Model for Smart Manufacturing Using Convolutional LSTM Neural Network Autoencoders by Essien, Aniekan, Giannetti, Cinzia

“… However, making accurate data-driven machine speed forecasts is challenging. Given the complex nature of industrial manufacturing process data, predictive models…”
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Explainable heat demand forecasting for the novel control strategies of district heating systems by Zdravković, Milan, Ćirić, Ivan, Ignjatović, Marko

“…) approach, namely, stacked LSTM, bi-directional LSTM, encoder-decoder and attention models…”
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