Sökning: "perceptron"

Visar resultat 1 - 5 av 171 uppsatser innehållade ordet perceptron.

  1. 1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Nikolaos Staikos; [2024]
    Nyckelord :Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

    Sammanfattning : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. LÄS MER

  2. 2. 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. 3. 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. 4. A Machine Learning Approach to Skin Cancer Delineation on Photoacoustic Imaging

    Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation

    Författare :Alice Fracchia; [2023]
    Nyckelord :Skin cancer; carcinoma; photoacoustic imaging; ultrasound imaging; machine learning; dimensionality reduction; sandpiles algorithm; active contour; multilayer perception MLP ; convolutional neural networks CNN ; autoencoder; Physics and Astronomy;

    Sammanfattning : Skin cancer is a growing public health concern due to its prevalence among the population. Current clinical procedures require high invasiveness and multiple surgeries, which are responsible for patient discomfort and high medical expenses. LÄS MER

  5. 5. Recommending digital books to children : Acomparative study of different state-of-the-art recommendation system techniques

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

    Författare :Malvin Lundqvist; [2023]
    Nyckelord :Recommendation Systems; Collaborative Filtering; Matrix Factorization; Multi-Layer Perceptron; Neural Network-based Collaborative Filtering; Implicit Feedback; Deep Learning; Term Frequency-Inverse Document Frequency; Rekommendationssystem; Kollaborativ filtrering; Matrisfaktorisering; Flerlagersperceptron; Neurala nätverksbaserad kollaborativ filtrering; Implicit data; Djupinlärning; Termfrekvens med omvänd dokumentfrekvens;

    Sammanfattning : Collaborative filtering is a popular technique to use behavior data in the form of user’s interactions with, or ratings of, items in a system to provide personalized recommendations of items to the user. This study compares three different state-of-the-art Recommendation System models that implement this technique, Matrix Factorization, Multi-layer Perceptron and Neural Matrix Factorization, using behavior data from a digital book platform for children. LÄS MER