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Showing 1 to 9 of 9 for “"temporal convolutional network"”.

  1. Sepsis Prediction Using Temporal Convolutional Network

    Zeng, Kaiyuan2021

    auckland-tech

  2. Predicting stock market volatility using neural network models : a comparative study on Bidirectional Temporal Convolutional Network (BiTCN), Neural Hierarchical Interpolation for Time Series (NHITS), Time-series Dense Encoder (TiDE), and Temporal Fusion Transformer (TFT) across 20 years of S&P 500 constituent stocks

    Mendoza Ortiz, J.A.2025

    tilburg Repository record

  3. Gaze-Aware Driver Maneuver Prediction Using Object Detection and Sequential Deep Learning Models for Advanced Driver Assistance Systems

    Sawane, RavindranathThe University of Western Ontario2025

    … (GRU), Long Short-Term Memory (LSTM), and the Temporal Convolutional Network (TCN). Results indicate that incorporating gaze-based object detection features slightly increased the time available to anticipate maneuvers but did not improve prediction accuracy. The Temporal Convolutional Network …

    uwo Repository record

  4. Predicting text features of social temporal point process

    Cui, DiUniversity of Delaware2021

    … the problem of predicting the text feature of temporal point processes. Temporal point process is common in our daily life - for example, the time sequence of multivariate discussions in online forums with features like text and user profile, and the coordinate sequence of human joint position …

    udel Repository record

  5. Real-time process monitoring of Spark-Assisted Chemical Engraving (SACE) machine with data-driven techniques

    Seyedi Sahebari, Seyed MahmoudUniversity of Ontario Institute of Technology2025

    … for this segmentation using two architectures—Temporal Convolutional Network (TCN) and Long Short-Term Memory (LSTM)—achieving classification accuracies of 97.18% and 96.44%, respectively. The second step establishes a correlation between extracted process signatures and SACE machining quality …

    uoit Repository record

  6. Fast head profile estimation using curvature, derivatives and deep learning methods

    Dickers, GordonUniversity of Wales Trinity Saint David2022

    … train a long short-term memory recurrent neural network and produced a significant speedup in execution time where pre-filtering of a sampled dataset was required. Following on from this, a new dataset of head profile contours was generated and annotated with anthropometric cranio-facial …

    uwtsd Repository record

  7. Automatic baleen whale detection and 2D localization using a network of unsynchonized passive acoustic sensors

    Goldwater, Mark H.Massachusetts Institute of Technology and Woods Hole Oceanographic Institution2024

    … the results, an appropriately trained neural network can quickly process data with no human supervision. Both low-cost passive acoustic monitoring (PAM) sensing platforms and algorithms that can analyze massive amounts of raw data are critical to accessible and scalable approaches in ocean …

    woods-hole Repository record

  8. Automatic Baleen Whale Detection and 2D Localization Using a Network of Unsynchronized Passive Acoustic Sensors

    Goldwater, Mark HarryMassachusetts Institute of Technology2024

    … the results, an appropriately trained neural network can quickly process data with no human supervision. Both low-cost passive acoustic monitoring (PAM) sensing platforms and algorithms that can analyze massive amounts of raw data are critical to accessible and scalable approaches in ocean …

    mit Repository record

  9. Improving the Maximum Power Point Tracking Efficiency of Photovoltaic Arrays via Machine Learning and Deep Learning

    Inamdar, Sumedha2025

    <p>Under partial shading conditions, photovoltaic (PV) modules in a solar array experience varying irradiance. A Global Maximum (GM) and multiple Local Maximums (LMs) can originate on the Power-Voltage (P-V) curve under nonuniform irradiance conditions. There are many maximum power point tracking …

    kennesaw Repository record