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Visar resultat 1 - 5 av 70 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Planet-NeRF : Neural Radiance Fields for 3D Reconstruction on Satellite Imagery in Season Changing Environments

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Erica Ingerstad; Liv Kåreborn; [2024]
    Nyckelord :NeRF; Neural Radiance Field; Satellite Imagery; Machine Learning; Deep Learning;

    Sammanfattning : This thesis investigates the seasonal predictive capabilities of Neural Radiance Fields (NeRF) applied to satellite images. Focusing on the utilization of satellite data, the study explores how Sat-NeRF, a novel approach in computer vision, per- forms in predicting seasonal variations across different months. LÄS MER

  3. 2. Randomized Diagonal Estimation

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Niclas Joshua Popp; [2023]
    Nyckelord :Diagonal estimation; randomized numerical linear algebra; low-rank approximation; matrix functions; Diagonalestimering; randomiserad numerisk linjär algebra; lågrankad approximation; matrisfunktioner;

    Sammanfattning : Implicit diagonal estimation is a long-standing problem that is concerned with approximating the diagonal of a matrix that can only be accessed through matrix-vector products. It is of interest in various fields of application, such as network science, material science and machine learning. LÄS MER

  4. 3. Designing a Novel RPL Objective Function & Testing RPL Objective Functions Performance

    Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Khalil Mardini; Emad Abdulsamad; [2023]
    Nyckelord :Routing protocol for low-power and lossy networks RPL ; Wireless Sensor Networks WSN ; The Internet of Things IoT ; Objective Function OF ; Low-Power and Lossy Networks LLNs ; Expected Transmission Count ETX ; Min- imum Rank with Hysteresis Objective Function MRHOF ; Packet Delivery Ratio PDR ; Directed Acyclic Graph DODAG ;

    Sammanfattning : The use of Internet of Things systems has increased to meet the need for smart systems in various fields, such as smart homes, intelligent industries, medical systems, agriculture, and the military. IoT networks are expanding daily to include hundreds and thousands of IoT devices, which transmit information through other linked devices to reach the network sink or gateway. LÄS MER

  5. 4. EVALUATING PERFORMANCE OF GENERATIVE MODELS FOR TIME SERIES SYNTHESIS

    Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :Muhammad Junaid Haris; [2023]
    Nyckelord :GAN; Generative Adversarial Network; VQ-VAE; Vector Quantized Variational AutoEncoder; AutoEncoder; VAE; Time Series; Synthesizing; Data Synthesis;

    Sammanfattning : Motivated by successes in the image generation domain, this thesis presents a novel Hybrid VQ-VAE (H-VQ-VAE) approach for generating realistic synthetic time series data with categorical features. The primary motivation behind this work is to address the limitations of existing generative models in accurately capturing the underlying structure and patterns of time series data, especially when dealing with categorical features. LÄS MER

  7. 5. Multi-scale Bark Beetle Predictions Using Machine Learning

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

    Författare :Albert Øhrman Wellendorf; [2023]
    Nyckelord :Geography; GIS; Geographically weighted regression; bark beetle; machine learning; Earth and Environmental Sciences;

    Sammanfattning : Bark beetle attacks have led to widespread tree disturbance and deaths in many parts of the world, and thereby also economic and biodiversity losses. Forest-rich Sweden has experienced periodic attacks, latest in 2018. LÄS MER