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Visar resultat 1 - 5 av 6 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Topical Classification of Images in Wikipedia : Development of topical classification models followed by a study of the visual content of Wikipedia

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Matheus Vieira Bernat; [2023]
    Nyckelord :Wikipedia; Multilabel classification; Deep learning;

    Sammanfattning : With over 53 million articles and 11 million images, Wikipedia is the greatest encyclopedia in history. The number of users is equally significant, with daily views surpassing 1 billion. Such an enormous system needs automation of tasks to make it possible for the volunteers to maintain. LÄS MER

  3. 2. Multilabel text classification of public procurements using deep learning intent detection

    Master-uppsats, KTH/Matematisk statistik

    Författare :Adin Suta; [2019]
    Nyckelord :Natural language processing; text classification; deep learning; applied mathematics; recurrent neural network; word embedding; Maskininlärning; textklassificering; artificiella neruonnät; tillämpad matematik;

    Sammanfattning : Textual data is one of the most widespread forms of data and the amount of such data available in the world increases at a rapid rate. Text can be understood as either a sequence of characters or words, where the latter approach is the most common. LÄS MER

  4. 3. sEMG Classication with Convolutional Neural Networks: A Multi-Label Approach for Prosthetic Hand Control

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Alexander Olsson; [2018]
    Nyckelord :Electromyography; Machine Learning; Deep Learning; Gesture Recognition; Neural Networks; Technology and Engineering;

    Sammanfattning : In myoelectric prosthesis design, there is often a trade-off between control robustness and range of executable movements. As a low movement error rate is necessary in any real application, this often results in a quite severe limitation on the dexterity of the user. LÄS MER

  5. 4. Comparing Feature Extraction Methods and Effects of Pre-Processing Methods for Multi-Label Classification of Textual Data

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

    Författare :Martin Eklund; [2018]
    Nyckelord :Feature extraction multilabel classification glove tfidf;

    Sammanfattning :  This thesis aims to investigate how different feature extraction methods applied to textual data affect the results of multi-label classification. Two different Bag of Words extraction methods are used, specifically the Count Vector and the TF-IDF approaches. A word embedding method is also investigated, called the GloVe extraction method. LÄS MER

  7. 5. Utvärdering av Amazon Machine Learning för taggsystem

    Kandidat-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

    Författare :Farzana Madosh; Erik Lundsten; [2017]
    Nyckelord :amazon; maskininlärning; taggsystem;

    Sammanfattning : How companies deal with machine learning is currently a highly-discussed topic, as it can facilitate corporate manual work by training computers to recognize patterns and thus automate the working procedure. However, this requires resources and knowledge in the field. LÄS MER