Sökning: "Satellite Image Classification"

Visar resultat 1 - 5 av 55 uppsatser innehållade orden Satellite Image Classification.

  1. 1. Using GIS and satellite data to assess access of green area for children living in growing cities

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

    Författare :Rebecca Borg; [2024]
    Nyckelord :Geography; GIS; Geographical Information System; Urban green space; children; schools; Malmö; Earth and Environmental Sciences;

    Sammanfattning : Urban green space (UGS) refers to open spaces within an urban context that are filled with greenery and nature. These can range from very small vegetation to expansive park areas. The common denominator is that they have proven to be beneficial for human health and well-being. Access to green spaces is also important for children. LÄS MER

  2. 2. Object Recognition in Satellite imagesusing improved ConvolutionalRecurrent Neural Network

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :TARUN NATTALA; [2023]
    Nyckelord :CRNN; CNN; RNN; Machine Learning and Satellite Image Recognition.;

    Sammanfattning : Background:The background of this research lies in detecting the images from satellites. The recognition of images from satellites has become increasingly importantdue to the vast amount of data that can be obtained from satellites. This thesisaims to develop a method for the recognition of images from satellites using machinelearning techniques. LÄS MER

  3. 3. Use of Satellite Remote Sensing for Detecting Archaeological Features: An Example from Ancient Corinth, Greece

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

    Författare :Emmanouil Papadakis; [2023]
    Nyckelord :Geography; GIS; Satellite Remote Sensing; Vegetation Indices; Classification; Archaeology; Earth and Environmental Sciences;

    Sammanfattning : During the last few decades, satellite remote sensing has proven to be an important non-invasive method for archaeological research in order to detect ancient sites and manage existing ones. Archaeologists have tried in the recent past to embed Geographic Information Systems (GIS) and image processing techniques in their research as non-destructive approaches, which can allow a wider perception of archaeological landscapes and predict past behaviors. LÄS MER

  4. 4. Land Use/Land Cover Classification From Satellite Remote Sensing Images Over Urban Areas in Sweden : An Investigative Multiclass, Multimodal and Spectral Transformation, Deep Learning Semantic Image Segmentation Study

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Oskar Aidantausta; Patrick Asman; [2023]
    Nyckelord :data fusion; deep learning; land use land cover classification; multiclass; multimodal; remote sensing; semantic segmentation; Sentinel satellite; spectral index; U-Net; Urban Atlas;

    Sammanfattning : Remote Sensing (RS) technology provides valuable information about Earth by enabling an overview of the planet from above, making it a much-needed resource for many applications. Given the abundance of RS data and continued urbanisation, there is a need for efficient approaches to leverage RS data and its unique characteristics for the assessment and management of urban areas. LÄS MER

  5. 5. Locating power lines in satellite images with semantic segmentation

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Erik Lundman; [2022]
    Nyckelord :AI; Machine learning; Semantic segmentation; Power lines; Satellite images;

    Sammanfattning : The inspection of power lines is an important process to maintain a stable electrical infrastructure. Simultaneously it is very time consuming task considering there are 164 000 km of power lines in Sweden alone. A cheaper and more sustainable approach is an automatic inspection with drones. LÄS MER