Sökning: "Classification Algorithms"

Visar resultat 16 - 20 av 576 uppsatser innehållade orden Classification Algorithms.

  1. 16. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

    Master-uppsats, KTH/Mekatronik och inbyggda styrsystem

    Författare :Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Nyckelord :Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

    Sammanfattning : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. LÄS MER

  3. 17. Exploring Advanced Clustering Techniques for Business Descriptions : A Comparative Study and Analysis of DBSCAN, K-Means, and Hierarchical Clustering

    Uppsats för yrkesexamina på avancerad nivå, Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)

    Författare :Wisam Orabi Alkhen; [2023]
    Nyckelord :Machine learning; Business descriptions; Search scope reduction; Relevant business terminology; Data analysis.;

    Sammanfattning : In this study, we introduce several approaches to analyze large volumes of business descriptions by applying machine learning clustering and classification algorithms. The goal is to efficiently classify these descriptions, reducing the search scope and allowing for better business insights and decision-making processes. LÄS MER

  4. 18. Comparing dropout regularization algorithms for convolutional neural networks identifying malignant cells for diagnosis of leukemia

    Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Hampus Engström; Alexander Koutakis; [2023]
    Nyckelord :classification; Bernoulli; Gaussian; spatial; machine learning; cancer; myeloid; myeloproliferative neoplasms;

    Sammanfattning : Fast and high quality classifications of cells inflicted with malignant mutations is essential for diagnosing patients with different forms of leukemia, to quickly be able give patients the crucial care they need. Convolutional neural networks (CNNs) can be trained and used for this purpose. LÄS MER

  5. 19. IMPROVING NONDISCRIMINATIVE CLASSIFIERS WITH THE HELP OF CLUSTERING : Enhancing Text Classification: Using Clustering For Improved Classifier Performance

    Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Martin Mickels; [2023]
    Nyckelord :classification; waste; Avfallsloggen; clustering; nondiscriminative;

    Sammanfattning : A common classification task of today is classifying resources that consist of words. Nondiscriminative classifiers are a popular type of classifiers for such classification. This paper presents a study that determines whether a method of using clusters of words found in training data can be utilized for improved classifier performance. LÄS MER

  7. 20. Song Popularity Prediction with Deep Learning : Investigating predictive power of low level audio features

    Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Gustaf Holst; Jan Niia; [2023]
    Nyckelord :machine learning; deep learning; audio;

    Sammanfattning : Today streaming services are the most popular way to consume music, and with this the field of Music Information Retrieval (MIR) has exploded. Tangy market is a music investment platform and they want to use MIR techniques to estimate the value of not yet released songs. LÄS MER