Sökning: "deep space network"

Visar resultat 16 - 20 av 87 uppsatser innehållade orden deep space network.

  1. 16. An Application of LatentCF++ on Providing Counterfactual Explanations for Fraud Detection

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Maria-Sofia Giannopoulou; [2023]
    Nyckelord :counterfactuals; fraud detection; LatentCF ; autoencoder; one-dimensional convolutional neural network;

    Sammanfattning : The aim of explainable machine learning is to aid humans in understanding how exactly complex machine learning models work. Machine learning models have offered great performance in various areas. However, the mechanisms behind how the model works and how decisions are being made remain unknown. LÄS MER

  3. 17. Fast Simulations of Radio Neutrino Detectors : Using Generative Adversarial Networks and Artificial Neural Networks

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Högenergifysik

    Författare :Anton Holmberg; [2022]
    Nyckelord :Askaryan emission; Radio detection of neutrinos; in-ice propagation; neutrino; Generative adversarial networks; GAN; WGAN; Neural networks; NN; surrogate model; IceCube; deep learning; generative model;

    Sammanfattning : Neutrino astronomy is expanding into the ultra-high energy (>1017eV) frontier with the use of in-ice detection of Askaryan radio emission from neutrino-induced particle showers. There are already pilot arrays for validating the technology and the next few years will see the planning and construction of IceCube-Gen2, an upgrade to the current neutrino telescope IceCube. LÄS MER

  4. 18. Artificial Neural Networks and Inductive Biases for Multi-Instance Multi-Modal Tabular Data : A Case Study for Default Probability Estimation in Small-to-Medium Enterprise Lending

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Gustav Röhss; [2022]
    Nyckelord :;

    Sammanfattning : The success of artificial neural networks in homogeneous data domains such as images, textual data, and audio and other signals has had considerable impact on Machine Learning and science in general. The domain of heterogeneous tabular data, while arguably much more common, remains much less explored with regards to artificial neural networks and deep learning. LÄS MER

  5. 19. Anomalous Behavior Detection in Aircraft based Automatic Dependent Surveillance–Broadcast (ADS-B) system using Deep Graph Convolution and Generative model (GA-GAN)

    Magister-uppsats, Linköpings universitet/Databas och informationsteknik

    Författare :Jayesh Kenaudekar; [2022]
    Nyckelord :Intrusion detection aircraft aviation security adsb protocol AI deep learning machine learning graph generative model surveillance broadcast;

    Sammanfattning : The Automatic Dependent Surveillance-Broadcast (ADS-B) is a key component of the Next Generation Air Transportation System (Next Gen) that manages the increasingly congested airspace and operation. From Jan 2020, the U.S. Federal Aviation Administration (FAA) mandated the use of (ADS-B) as a key component of Next Gen project. LÄS MER

  7. 20. Distance preserving Fermat VAE

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Miklovana Tuci; [2022]
    Nyckelord :;

    Sammanfattning : Deep neural networks takes their strength in the representations, or features, that they internally build. While these internal encodings help networks performing classification or regression tasks on specific data types, it exists a branch of machine learning that has for only purpose to build these representations. LÄS MER