Sökning: "pixel art"

Visar resultat 1 - 5 av 40 uppsatser innehållade orden pixel art.

  1. 1. Svensk Satir i Flux: En Tidsresa från Papper till Pixel. En semiotisk analys om hur satiren i Sverige har ändrats över tid

    Kandidat-uppsats, Göteborgs universitet/Institutionen för journalistik, medier och kommunikation

    Författare :Sara Tervonen; Hanna Steringer; [2024-03-06]
    Nyckelord :Satir; satirteckningar; digitalt; medier; tidningar; politik;

    Sammanfattning : The purpose of this bachelor thesis is to examine the satire climate in Sweden. In the 1970’s, satire art was frequently published in Swedish newspapers in contrast to today where satire art is barely existent in newspapers. LÄS MER

  3. 2. Developing a Neural Network Model for Semantic Segmentation

    M1-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :Ronny Westphal; [2023]
    Nyckelord :Semantic segmentation; neural network; Unity Barracuda; PyTorch; augmented reality; Semantisk segmentering; neurala nätverk; Unity Barracuda; PyTorch; augmenterad verklighet;

    Sammanfattning : This study details the development of a neural network model designed for real-time semantic segmentation, specifically to distinguish sky pixels from other elements within an image. The model is incorporated into a feature for an Augmented Reality application in Unity, leveraging Unity Barracuda—a versatile neural network inference library. LÄS MER

  4. 3. Segmentation of Neuronal Cells Using Simplistic Methods : A Comparison of the Mean Shift Algorithm and Otsu’s Method

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

    Författare :Alex Gunnarsson; Filip Karlsson; [2023]
    Nyckelord :;

    Sammanfattning : Information regarding specific neuronal characteristics, such as shape and distribution, is essential for quantifying the brain structure and modelling accurate computer simulations. To this end, it is important to perform cell segmentation; to isolate the cells in a given image from the surrounding tissue, so it can be further analysed. LÄS MER

  5. 4. Cell Identification from Microscopy Images using Deep Learning on Automatically Labeled Data

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Fredrik Salomon-Sörensen; [2023]
    Nyckelord :Deep Learning; Cell Identification; Image Segmentation; Nuclei Segmentation; Convolutional Neural Networks; UNet; Image Analysis; Microscopy; Noisy Labels; Phase-Contrast; Automatic Labeling; Technology and Engineering;

    Sammanfattning : In biology, cell counting provides a fundamental metric for live-cell experiments. Unfortunately, most researchers are constrained to using tedious and invasive methods for counting cells. Automatic identification of cells in microscopy images would therefore be a valuable tool for such researchers. LÄS MER

  7. 5. A real-time Multi-modal fusion model for visible and infrared images : A light-weight and real-time CNN-based fusion model for visible and infrared images in surveillance

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

    Författare :Jin Wanqi; [2023]
    Nyckelord :Image fusion; deep learning; surveillance; CNN; real time; Bildfusion; djupinlärning; övervakning; CNN; realtid;

    Sammanfattning : Infrared images could highlight the semantic areas like pedestrians and be robust to luminance changes, while visible images provide abundant background details and good visual effects. Multi-modal image fusion for surveillance application aims to generate an informative fused images from two source images real-time, so as to facilitate surveillance observatory or object detection tasks. LÄS MER