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Showing 1 to 9 of 9 for “"Capsule Networks"”.

  1. HIERARCHICAL OBJECT-CENTRIC LEARNING WITH CAPSULE NETWORKS

    Grangetto, Marco, Renzulli, RiccardoUniversità degli Studi di Torino2023

    unito Repository record

  2. Application of capsule networks for image classification on complex datasets

    Goswami, DeborshiUniversity of Illinois at Urbana-Champaign2019

    Capsule Network, introduced in 2017 by Sabour, Hinton, and Frost, has sparked great interest in the computer vision and deep learning community and offers a paradigm shift in neural computation. In CapsNet, Sabour et. al. replace classical notions of scalar neural computation with a vectorised …

    uiuc Repository record

  3. Capsule Networks: Framework and Application to Disentanglement for Generative Models

    Moghimi, ZahraVirginia Tech2021

    … generative models such as generative adversarial networks. Thus, we attempt to increase the disentanglement of latent variables in variational autoencoders without compromising the generated image quality. In this thesis, a novel generative model based on capsule networks and a variational …

    vt Repository record

  4. The effectiveness of convolutional neural networks and capsule networks for medical waste classification

    Broek, B. van den2025

    tilburg Repository record

  5. AUTOMATIC IDENTIFICATION OF ANIMALS IN THE WILD: A COMPARATIVE STUDY BETWEEN C-CAPSULE NETWORKS AND DEEP CONVOLUTIONAL NEURAL NETWORKS.

    Kamdem Teto, Joel, Xie, Ying2018

    … is also an opportunity to present some custom Capsule Networks architectures to the deep learning community while solving the above-mentioned critical problem. Incidentally, we are going to take advantage of these data to make a comparative study on multiple deep learning models, specifically, …

    kennesaw Repository record

  6. DERMAI – A DEEP LEARNING-BASED WEB PLATFORM FOR DERMATOLOGIC DIAGNOSIS

    LYU SHAOBO2024

    … and a Convolutional Block Attention Module for capsule networks, achieved 99.25% accuracy on the HAM10000 dataset. DermAI enables patients to receive preliminary skin disease diagnoses via internet, potentially improving primary care diagnostic efficiency, reducing unnecessary specialist …

    nus Repository record

  7. Deep learning models for defect and anomaly detection on industrial surfaces

    Saberironaghi, AlirezaUniversity of Ontario Institute of Technology2023

    … For textiles, a novel system merges capsule networks with convolutional neural networks and a spatial attention module, achieving a 99.42% accuracy on the TILDA dataset. In civil engineering, the DepthCrackNet model, optimized for pavement crack detection, attains mIoU scores of 77.0% …

    uoit Repository record

  8. An evaluation of the robustness of the natural-adversarial mutual information-based defense and malware classification against adversarial attacks for deep learning

    Schwab, David2023

    … researchers have shown that even deep neural networks (DNNs) can be “fooled” into misclassifying an input sample that has been minimally modified in a specific way. These modified samples are known as adversarial examples and have been crafted with the goal of causing the target DNN to modify …

    utc Repository record

  9. Automated Teeth Extraction and Dental Caries Detection in Panoramic X-ray

    Haghanifar, ArmanUniversity of Saskatchewan2022

    … are used for feature extraction, followed by capsule networks to perform classification. The dataset of Panoramic x-rays is prepared by the authors, with help from an expert radiologist to provide labels. The proposed model has demonstrated an acceptable detection rate of 86.05%, and an …

    sask Repository record