Sökning: "Semantisk Segmentering"

Visar resultat 1 - 5 av 58 uppsatser innehållade orden Semantisk Segmentering.

  1. 1. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks

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

    Författare :Xinchen Wang; [2024]
    Nyckelord :Deep Learning; Semantic segmentation; Network optimization; Network pruning; Torch Pruning; YOLOv8; Network Depth; Djup lärning; Semantisk segmentering; Nätverksoptimering; Nätverksbeskärning; Fackelbeskärning; YOLOv8; Nätverksdjup;

    Sammanfattning : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. LÄS MER

  3. 2. Enhancement of a Power Line Information System by Combining BIM and LiDAR Data

    Master-uppsats, KTH/Lantmäteri – fastighetsvetenskap och geodesi

    Författare :Daniel Wollberg; [2024]
    Nyckelord :GIS; BIM; FME; CloudCompare; GIS; BIM; FME; CloudCompare;

    Sammanfattning : With the great ongoing energy transition in Sweden, Svenska Kraftnät (SVK) sees a huge need for investment in the Swedish transmission network and supporting IT- systems.  SVK has a great amount of collected laser data over the electric power transmission network however this data does not contain any semantic attribution that can be analyzed on broader information systems. LÄS MER

  4. 3. 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

  5. 4. Aggregating predictions of a yeast semantic segmentation model : Reducing a pixel classifier into a binary image classifier

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

    Författare :Ali Muquri; [2023]
    Nyckelord :;

    Sammanfattning : The introduction of machine learning in clinical microbiology is important for aiding clinical laboratories with highly repetitive tasks that are fatiguing, error-prone, and require long employee training time due to the complex nature of the task. A challenging task that belongs to the subareas that need assistance is yeast detection in fluorescence microscopy where various yeast morphologies exist. LÄS MER

  7. 5. Optic nerve sheath diameter semantic segmentation and feature extraction

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

    Författare :Simone Bonato; [2023]
    Nyckelord :Machine Learning; Computer Vision; Image Segmentation; Medical Imaging; Optic Nerve Sheath Diameter; nnU-Net; Maskininlärning; datorseende; bildsegmentering; medicinsk bildbehandling; optisk nervslidsdiameter; nnU-Net;

    Sammanfattning : Traumatic brain injury (TBI) affects millions of people worldwide, leading to significant mortality and disability rates. Elevated intracranial pressure (ICP) resulting from TBI can cause severe complications and requires early detection to improve patient outcomes. LÄS MER