Sökning: "Perceptron Neurala Nätverk"

Visar resultat 1 - 5 av 20 uppsatser innehållade orden Perceptron Neurala Nätverk.

1. 1. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods

   Master-uppsats, KTH/Fysik

   Författare :Jeanette Marie Victoria Skeppland Hole; [2023]
   Nyckelord :ECG; ECG-analysis; QRS detector; Artificial Intelligence; Machine Learning; Deep neural networks; Long short-term memory; Convolutional neural network; Multilayer perceptron; EKG; EKG-analys; QRS detektor; Artificiell intelligens; Maskininlärning; Djupa neurala nätverk; Long short-term memory; Convolutional neural network; Multilayer perceptron;

   Sammanfattning : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). LÄS MER

3. 2. User authentication through behavioral biometrics using multi-class classification algorithms : A comprehensive study of machine learning algorithms for keystroke and mouse dynamics

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

   Författare :Emil Lantz; [2023]
   Nyckelord :Behavioral biometrics; keystroke dynamics; mouse dynamics; machine learning; neural networks; decision trees.; Beteendemässig biometri; maskininlärning; neurala nätverk; beslutsträd.;

   Sammanfattning : User authentication is vital in a secure system. Authentication is achieved through something a genuine user knows, has, or is. The latter is called biometrics, commonly attributed with fingerprint and face modalities. It is also possible to identify a user based on their behavior, called behavioral biometrics. LÄS MER

4. 3. Link Prediction Using Learnable Topology Augmentation

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Tori Leatherman; [2023]
   Nyckelord :Network Analysis; Inductive Link Prediction; Learnable Augmentation; Graph Neural Networks; Multilayer Perceptrons; Nätverksanalys; Induktiv Länkförutsägelse; Inlärningsbar Förstärkning; Grafiska Neurala Nätverk; Flerskiktsperceptroner;

   Sammanfattning : Link prediction is a crucial task in many downstream applications of graph machine learning. Graph Neural Networks (GNNs) are a prominent approach for transductive link prediction, where the aim is to predict missing links or connections only within the existing nodes of a given graph. LÄS MER

5. 4. Reverse Engineering of Deep Learning Models by Side-Channel Analysis

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

   Författare :Xuan Wang; [2023]
   Nyckelord :Side-Channel Attack; Deep Learning; Reverse Engineering; Perceptron Neural Network; Sidokanalattack; Djup lärning; Omvänd Konstruktion; Perceptron Neurala Nätverk;

   Sammanfattning : Side-Channel Analysis (SCA) aims to extract secrets from cryptographic systems by exploiting the physical leakage acquired from implementations of cryptographic algorithms. With the development of Deep Learning (DL), a new type of SCA called Deep Learning Side-Channel Analysis (DLSCA) utilizes the advantages of DL techniques in data features processing to break cryptographic systems more efficiently. LÄS MER

7. 5. Predicting Customer Satisfaction in the Context of Last-Mile Delivery using Supervised and Automatic Machine Learning

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

   Författare :Carl Höggren; [2022]
   Nyckelord :Last-mile Delivery; Customer Satisfaction; Supervised Machine Learning; Automatic Machine Learning; Imbalanced Datasets; Sista-milen Leveranser; Kundnöjdhet; Övervakad Maskininlärning; Automatiserad Maskininlärning; Obalanserade Dataset;

   Sammanfattning : The prevalence of online shopping has steadily risen in the last few years. In response to these changes, last-mile delivery services have emerged that enable goods to reach customers within a shorter timeframe compared to traditional logistics providers. LÄS MER