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Hittade 3 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Design Extractor: A ML-based Tool for CapturingSoftware Design Decisions

    Kandidat-uppsats, Mittuniversitetet/Institutionen för kommunikation, kvalitetsteknik och informationssystem (2023-)

    Författare :Petrus Söderström; [2023]
    Nyckelord :machine learning; natural language processing; design decisions; software design; voice recognition;

    Sammanfattning : Context: A software project’s success; involvinga larger group of individuals, relies on efficient teamcommunication. Part of efficient communication is avoidingmiscommunication, misunderstandings, and losingknowledge. These consequences of poor communication canlead to negative repercussions such as loss of time, money,and customer approval. LÄS MER

  3. 2. Examining Machine Learning as an alternative for scalable video analysis

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Niclas Ragnar; Zoran Tolic; [2019]
    Nyckelord :Machine Learning; MLaaS; Microsoft; Google; DeepAI; Aylien; video analysis; transcription; translation; summarisation; Word Error Rate; BLEU; Maskininlärning; MLaaS; Microsoft; Google; videoanalys; transkribering; översättning; sammanfattning; word error rate; BLEU;

    Sammanfattning : Video is a large part of today’s society where surveillance cameras represent the biggest source of big data, and real-time entertainment is the largest network traffic category. There is currently a large interest in analysing the contents of video where video analysis is mainly conducted by people. LÄS MER

  4. 3. The effect of noise in the training of convolutional neural networks for text summarisation

    Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

    Författare :Ailsa Meechan-Maddon; [2019]
    Nyckelord :text summarisation; text summarization; summarization; nlp; computational linguistics; cnn; neural networks; machine learning;

    Sammanfattning : In this thesis, we work towards bridging the gap between two distinct areas: noisy text handling and text summarisation. The overall goal of the paper is to examine the effects of noise in the training of convolutional neural networks for text summarisation, with a view to understanding how to effectively create a noise-robust text-summarisation system. LÄS MER