Sökning: "Plasticitet"

Visar resultat 1 - 5 av 45 uppsatser innehållade ordet Plasticitet.

  1. 1. Adversarial robustness of STDP-trained spiking neural networks

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

    Författare :Karl Lindblad; Axel Nilsson; [2023]
    Nyckelord :;

    Sammanfattning : Adversarial attacks on machine learning models are designed to elicit the wrong behavior from the model. One such attack on image classifiers are maliciously crafted inputs that, to the human eye, look untampered with but have been carefully altered to cause misclassification. LÄS MER

  3. 2. Regression with Bayesian Confidence Propagating Neural Networks

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

    Författare :Raghav Rajendran Bongole; [2023]
    Nyckelord :Machine Learning; Neural Networks; Brain-like computing; Bayesian Confidence Propagating Neural Networks; Maskininlärning; neurala nätverk; hjärnliknande datorer; Bayesian Förtroendespridande neurala nätverk;

    Sammanfattning : Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivity, and Hebbian learning. LÄS MER

  4. 3. Influence from temperature variations in stacking fault energy on the mechanical properties of stainless steels

    Kandidat-uppsats, KTH/Materialvetenskap

    Författare :Christopher Hallén; Marcus Johansson Storne; [2023]
    Nyckelord :;

    Sammanfattning : This paper investigates the mechanical properties and deformation mechanisms of austenitic stainless steels and how they relate to the material property of stacking fault energy (SFE) and its relation to temperature and nickel content. Austenitic stainless steels are commonly used and well known for good mechanical properties and deformation characteristics. LÄS MER

  5. 4. Volumetric Image Segmentation of Lizard Brains

    Master-uppsats, KTH/Tillämpad fysik

    Författare :Yulia Dragunova; [2023]
    Nyckelord :image segmentation; deep learning; atlas; lizard brain; micro-CT; image augmentation; bild segmentering; djupinlärning; atlas; ödelhjärna; mikro-datortomagrofi; datautökning;

    Sammanfattning : Accurate measurement brain region volumes are important in studying brain plasticity, which brings insight into the fundamental mechanisms in animal, memory, cognitive, and behavior research. The traditional methods of brain volume measurements are ellipsoid or histology. LÄS MER

  7. 5. Modelling synaptic rewiring in brain-like neural networks for representation learning

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

    Författare :Kunal Bhatnagar; [2023]
    Nyckelord :Adaptive Sparsity; Computational Neuroscience; Rewiring; Structural Plasticity; Brain-like Computing; Neural Networks; Hebbian Learning; Adaptiv gleshet; beräkningsneurovetenskap; omkoppling; strukturell plasticitet; Hjärnliknande beräkning; Neurala Nätverk; Hebbskt lärande;

    Sammanfattning : This research investigated the concept of a sparsity method inspired by the principles of structural plasticity in the brain in order to create a sparse model of the Bayesian Confidence Propagation Neural Networks (BCPNN) during the training phase. This was done by extending the structural plasticity in the implementation of the BCPNN. LÄS MER