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Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.

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Showing 1 to 5 of 5 for “"Convolutional LSTM"”.

  1. Learning from videos with deep convolutional LSTM networks

    Courtney, LoganUniversity of Illinois at Urbana-Champaign2021

    … This research explores the use of convolution LSTMs to simultaneously learn spatial- and temporal-information in videos. A deep network of convolutional LSTMs allows the model to access the entire range of temporal information at all spatial scales of the data. This work first constructs an …

    uiuc Repository record

  2. Machine Learning Application in Energy Storage System’s State Estimation: State of Health (SOH)

    Nazari, AshkanVirginia Tech2021

    … developed DL models with long short-term memory (LSTM), convolutional LSTM (ConvLSTM), and deep convolutional neural network (DCNN) architecture are acceptable by industry standards, with mean absolute percentage error (MAPE) less than 3%. The promising results obtained in this study indicate that …

    vt Repository record

  3. An Attention LSTM U-Net Model for Drosophila Melanogaster Heart Tube Segmentation

    Ouyang, Xiangping2024

    … segmentation model, FlyNet 2.0+, is a fully convolutional LSTM U-Net model. However, the performance of the model diminishes in the presence of artifacts, such as image reflection and heart movement, resulting in time-consuming manual intervention for mask correction. Therefore, we developed …

    wustl Repository record

  4. Advanced space-time integration for knowledge discovery in human mobility studies

    Xu, LiUniversity of Illinois at Urbana-Champaign2020

    … activity at the individual level. Last, a deep convolutional LSTM networks model is proposed to capture the spatial and temporal dependencies in an integrated way to predict real-time taxi demand. All proposed models are proven to be more effective or robust in various real-world experiments as …

    uiuc Repository record

  5. Graph neural network approaches and real-time unsupervised learning for anomaly detection in vehicular networks

    Razzazi, HarirUniversity of Missouri--Kansas City2025

    … Graph Neural Network (GNN) architectures: Graph Convolutional Network (GCN), Graph Attention Network (GAT), GraphSAGE, Temporal GCN (T-GCN), Gated Convolutional LSTM (GConvLSTM), and Gated Convolutional GRU (GConvGRU). The GConvLSTM and GConvGRU models achieved the highest precision, recall, and …

    umkc Repository record