Sökning: "Automated Feature Extraction"

Visar resultat 16 - 20 av 32 uppsatser innehållade orden Automated Feature Extraction.

  1. 16. Separation and Extraction of Valuable Information From Digital Receipts Using Google Cloud Vision OCR.

    Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Elias Johansson; [2019]
    Nyckelord :optical character recognition; automatic text extraction; python; google cloud vision; string analysis; receipt;

    Sammanfattning : Automatization is a desirable feature in many business areas. Manually extracting information from a physical object such as a receipt is something that can be automated to save resources for a company or a private person. LÄS MER

  3. 17. Developing robust algorithms for feature extraction in images of polymer layers

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Anton Wemmenborn; [2019]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Automated manufacturing processes are an important component of today’s industries. Assuming the processes are properly maintained they allow for great efficiency when producing various goods. Image analysis can be used as a tool to monitor such processes and evaluate their results. LÄS MER

  4. 18. Towards a fully automated extraction and interpretation of tabular data using machine learning

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

    Författare :Per Hedbrant; [2019]
    Nyckelord :machine learning; unsupervised machine learning; spreadsheets;

    Sammanfattning : Motivation A challenge for researchers at CBCS is the ability to efficiently manage the different data formats that frequently are changed. This handling includes import of data into the same format, regardless of the output of the various instruments used. LÄS MER

  5. 19. Automatic Feature Extraction for Human Activity Recognitionon the Edge

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

    Författare :Oscar Cleve; Sara Gustafsson; [2019]
    Nyckelord :Human Activity Recognition; Automatic Feature Extraction; Automatic Feature Selection; Automated Machine Learning; Random Forest Classifier; Hypothesis Test;

    Sammanfattning : This thesis evaluates two methods for automatic feature extraction to classify the accelerometer data of periodic and sporadic human activities. The first method selects features using individual hypothesis tests and the second one is using a random forest classifier as an embedded feature selector. LÄS MER

  7. 20. Comparison of 2D and 3D investigations of non-metallic inclusions in metal samples by different analytical methods

    Kandidat-uppsats, KTH/Materialvetenskap

    Författare :Andreas Flyckt; [2019]
    Nyckelord :;

    Sammanfattning : The objective of this research is to make a comparison between 2D- and 3D-investigations of non-metallic inclusions (NMIs) in metal samples by different analytical methods. NMIs are undesired particles that degrade the quality of the steel through affecting the mechanical properties. LÄS MER