Sökning: "Multiclass Segmentation"

Hittade 3 uppsatser innehållade orden Multiclass Segmentation.

  1. 1. 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

  3. 2. Instance Segmentation of Multiclass Litter and Imbalanced Dataset Handling : A Deep Learning Model Comparison

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Rolf Sievert; [2021]
    Nyckelord :Machine learning; Multiclass; Deep learning; Instance segmentation; Object segmentation; Iterative stratification; Mask R-CNN; DetectoRS; Imbalanced dataset; Classification; Detection; Segmentation; Litter; Trash; TACO; COCO; MMDetection; Multinomial; Cybercom; AI; Artificial intelligence; Land-based litter; Computer vision; Maskininlärning; Djupinlärning; Instanssegmentering; Objektsegmentering; Mask R-CNN; DetectoRS; Obalanserat dataset; Klassificering; Detektion; Segmentering; Skräp; TACO; COCO; MMDetection; Multinomial; Cybercom; AI; Artificiell intelligens; Datorseende;

    Sammanfattning : Instance segmentation has a great potential for improving the current state of littering by autonomously detecting and segmenting different categories of litter. With this information, litter could, for example, be geotagged to aid litter pickers or to give precise locational information to unmanned vehicles for autonomous litter collection. LÄS MER

  4. 3. Exploring Deep Learning Frameworks for Multiclass Segmentation of 4D Cardiac Computed Tomography

    Master-uppsats, Linköpings universitet/Institutionen för hälsa, medicin och vård

    Författare :Norman Janurberg; Christian Luksitch; [2021]
    Nyckelord :Computed Tomography; Multiclass Segmentation; Image Segmentation; 4D; Deep Learning; MONAI; Unet; Cropping network; Multiaxis Segmentation;

    Sammanfattning : By combining computed tomography data with computational fluid dynamics, the cardiac hemodynamics of a patient can be assessed for diagnosis and treatment of cardiac disease. The advantage of computed tomography over other medical imaging modalities is its capability of producing detailed high resolution images containing geometric measurements relevant to the simulation of cardiac blood flow. LÄS MER