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Showing 1 to 6 of 6 for “"Deep Autoencoder"”.

  1. A FEDERATED DEEP AUTOENCODER FOR DETECTING IOT CYBER ATTACKS

    … for traditional detection systems. However, deep learning-based solutions have been utilized in recent years, and many challenges have yet to be addressed. In this thesis, we propose a federated-based approach, this will employ a deep autoencoder to detect botnet attacks using on-device …

    kennesaw Repository record for A FEDERATED DEEP AUTOENCODER FOR DETECTING IOT CYBER ATTACKS (opens in a new tab)

  2. Deep Generative Models for Unsupervised Scale-Based and Position-Based Disentanglement of Concepts from Face Images.

    … recent advances of artificial intelligence using deep neural networks, computers are still struggling at achieving a rich and flexible understanding of face images comparable to humans' face perception abilities. This thesis aims at finding fully unsupervised ways for learning a transformation …

    carleton Repository record for Deep Generative Models for Unsupervised Scale-Based and Position-Based Disentanglement of Concepts from Face Images. (opens in a new tab)

  3. Lightweight intrusion detection of attacks on the Internet of Things (IoT) in critical infrastructures.

    … Traditional Machine Learning (ML) and Deep Learning (DL) approaches have proven to offer promising results in detecting intrusions; however, their computational demands make them impractical for resource-constrained IoT devices. This study proposes an Optimized Common Features Selection …

    rgu Repository record for Lightweight intrusion detection of attacks on the Internet of Things (IoT) in critical infrastructures. (opens in a new tab)

  4. Clustering and dimensionality reduction for time-series service monitoring data

    … as the initial dataset) produced with Deep and Convolutional AutoEncoders. The experiments disclose that the reconstructed dataset with Deep AutoEncoder is the most performing. Later, we propose an ensemble-based DR approach to effectively handle the high-dimensionality of the E2E …

    regina Repository record for Clustering and dimensionality reduction for time-series service monitoring data (opens in a new tab)

  5. Learning Clinical Body Composition Metrics from 2D and 3D Optical Imaging

    … learning. 4. Performs a systematic review of deep 3D shape autoencoders for total human body geometry with the goal of identifying the current state of the art methods and architectures in reconstruction accuracy while also suggesting standards and best practices for future work in this …

    washington Repository record for Learning Clinical Body Composition Metrics from 2D and 3D Optical Imaging (opens in a new tab)

  6. High-dimensional MR spectroscopic imaging integrating physics-based modeling and machine learning

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-12-01

    uiuc Repository record for High-dimensional MR spectroscopic imaging integrating physics-based modeling and machine learning (opens in a new tab)