Sökning: "pixel"

Visar resultat 16 - 20 av 431 uppsatser innehållade ordet pixel.

  1. 16. Anomaly Detection with Machine Learning using CLIP in a Video Surveillance Context

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Christoffer Gärdin; [2023]
    Nyckelord :Datorseende; maskininlärning; CLIP; anomalidetektion; videoövervakning;

    Sammanfattning : This thesis explores the application of Contrastive Language-Image Pre-Training (CLIP), a vision-language model, in an automated video surveillance system for anomaly detection. The ability of CLIP to perform zero-shot learning, coupled with its robustness against minor image alterations due to its lack of reliance on pixel-level image analysis, makes it a suitable candidate for this application. LÄS MER

  3. 17. Using the James Webb Space Telescope to Find Carbon Dioxide on Ganymede

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

    Författare :Olof Helgesson; Oscar Lundin; [2023]
    Nyckelord :;

    Sammanfattning : The aim of this bachelor's thesis is to search for CO₂ on Ganymede by studyingobservations taken by the James Webb Space Telescope and in doing so, create aprocessing pipeline for JWST data. The data is collected by JWST's Near InfraredSpectrograph instrument which is used for spectroscopy in the near infrared spectrum. LÄS MER

  4. 18. Applying Machine Learning Techniques for Anomaly Detection in Wooden Plank Images

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen Vi3

    Författare :Iza Smedberg; [2023]
    Nyckelord :Anomaly Detection; Machine Vision; Machine Learning; Neural Network;

    Sammanfattning : Anomaly detection is an important first step of quality control in manufacturing processes. In wooden planks, anomalies such as broken knots and resin pockets can lower the quality of the final product. With the help of machine vision, inspections can be made faster, at higher accuracy, and at a lower cost. LÄS MER

  5. 19. 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. 20. Structure from Motion with a Neural Network

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Jiarong Gong; [2023]
    Nyckelord :Technology and Engineering;

    Sammanfattning : This project delves into the 3D reconstruction of both single and multiple rigid motions, examining the potential of deep learning methods, such as that proposed by Moran et al., to supplant traditional geometry-based approaches. The project is structured into two main parts. LÄS MER