Sökning: "seq2seq"

Visar resultat 1 - 5 av 9 uppsatser innehållade ordet seq2seq.

  1. 1. Sequential Anomaly Detection for Log Data Using Deep Learning

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Lina Hammargren; Wei Wu; [2021-06-14]
    Nyckelord :anomaly detection; recurrent neural network; long short-term memory; semi-supervised learning; seq2seq; transformer; unsupervised learning; log analysis;

    Sammanfattning : AbstractSoftware development with continuous integration changes needs frequent testing forassessment. Analyzing the test output manually is time-consuming and automatingthis process could be beneficial to an organization. LÄS MER

  2. 2. Encoder-Decoder Networks for Cloud Resource Consumption Forecasting

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

    Författare :Sami Mejdi; [2021]
    Nyckelord :Telecommunications; Cloud; Time Series; Forecasting; Encoder-Decoder; Deep Learning; Machine Learning; Telekommunikation; Moln; Tidsserie; Prognoser; Envoder-Decoder; Djupinlärning; Maskininlärning;

    Sammanfattning : Excessive resource allocation in telecommunications networks can be prevented by forecasting the resource demand when dimensioning the networks and the allocation the necessary resources accordingly, which is an ongoing effort to achieve a more sustainable development. In this work, traffic data from cloud environments that host deployed virtualized network functions (VNFs) of an IP Multimedia Subsystem (IMS) has been collected along with the computational resource consumption of the VNFs. LÄS MER

  3. 3. Deep learning prediction of Quantmap clusters

    Master-uppsats, Uppsala universitet/Institutionen för biologisk grundutbildning

    Författare :Akshai Parakkal Sreenivasan; [2021]
    Nyckelord :Deep Learning; Machine Learning; Deep Neural Network; Convolutional Neural Network; Recurrent Neural Network; Drug classification; Drug-biological function;

    Sammanfattning : The hypothesis that similar chemicals exert similar biological activities has been widely adopted in the field of drug discovery and development. Quantitative Structure-Activity Relationship (QSAR) models have been used ubiquitously in drug discovery to understand the function of chemicals in biological systems. LÄS MER

  4. 4. Using Attention-based Sequence-to-Sequence Neural Networks for Transcription of Historical Cipher Documents

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

    Författare :Han Renfei; [2020]
    Nyckelord :;

    Sammanfattning : Encrypted historical manuscripts (also called ciphers), containing encoded information, provides a useful resource for giving new insight into our history. Transcribing these manuscripts from image format to computer readable format is a necessary step for decrypting them. LÄS MER

  5. 5. Encoder-Decoder Networks for Cloud Resource Consumption Forecasting

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

    Författare :Sami Mejdi; [2020]
    Nyckelord :Telecommunications; Cloud; Time Series; Forecasting; Encoder-Decoder; Deep Learning; Machine Learning; Telekommunikation; Moln; Tidsserie; Prognoser; Encoder-Decoder; Djupinlärning; Maskininlärning;

    Sammanfattning : Excessive resource allocation in telecommunications networks can be prevented by forecasting the resource demand when dimensioning the networks and then allocating the necessary resources accordingly, which is an ongoing effort to achieve a more sustainable development. In this work, traffic data from cloud environments that host deployed virtualized network functions (VNFs) of an IP Multimedia Subsystem (IMS) has been collected along with the computational resource consumption of the VNFs. LÄS MER