Sökning: "Recurrent Neuralt Network"

Visar resultat 6 - 10 av 27 uppsatser innehållade orden Recurrent Neuralt Network.

1. 6. Data Trustworthiness Assessment for Traffic Condition Participatory Sensing Scenario

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

   Författare :Hairuo Gao; [2022]
   Nyckelord :Participatory sensing; Data trustworthiness assessment; Anomaly detection; Traffic prediction; Deep neural network; Deltagande avkänning; Bedömning av uppgifternas tillförlitlighet; Upptäckt av anomalier; Trafikprognoser; Djupt neuralt nätverk;

   Sammanfattning : Participatory Sensing (PS) is a common mode of data collection where valuable data is gathered from many contributors, each providing data from the user’s or the device’s surroundings via a mobile device, such as a smartphone. This has the advantage of cost-efficiency and wide-scale data collection. LÄS MER

3. 7. Transformer learning for traffic prediction in mobile networks

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

   Författare :Daniel Wass; [2021]
   Nyckelord :Transformer; Attention; LSTM; Mobile traffic prediction.; Transformer; Attention; LSTM; Prediktering av mobil nätverkstrafik.;

   Sammanfattning : The resources of mobile networks are expensive and limited, and as demand for mobile data continues to grow, improved resource utilisation is a prioritised issue. Traffic demand at base stations (BSs) vary throughout the day and week, but the capacity remains constant and utilisation could be significantly improved based on precise, robust, and efficient forecasting. LÄS MER

4. 8. FMCW mmWave Radar for Detection of Pulse, Breathing and Fall within Home Care

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

   Författare :Axel Trange; [2021]
   Nyckelord :;

   Sammanfattning : Countless of elderly people fall and get hurt within their homes, worldwide, every year, and as they can not always reach out for help themselves, they end up helplessly waiting for someone to notice what has occurred. Throughout this work, it is investigated if remote sensing of the mmWave FMCW radar IWR6843AOPEVM can be adopted to detect the incident of falls, and also detect the vital signs of the human subject. LÄS MER

5. 9. Experiments in speaker diarization using speaker vectors

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

   Författare :Ming Cui; [2021]
   Nyckelord :Speaker Diarization; Embedding Extraction Module; Deep Learning; Supervised method; Unsupervised method; Talardiarisering; inbäddning av extraktionsmodul; djupinlärning; övervakad metod; oövervakad metod;

   Sammanfattning : Speaker Diarization is the task of determining ‘who spoke when?’ in an audio or video recording that contains an unknown amount of speech and also an unknown number of speakers. It has emerged as an increasingly important and dedicated domain of speech research. LÄS MER

7. 10. Machinery Health Indicator Construction using Multi-objective Genetic Algorithm Optimization of a Feed-forward Neural Network based on Distance

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

   Författare :Jacob Nyman; [2021]
   Nyckelord :Prognostics; Health Indicator Construction; Remaining Useful Life Prediction; Multi-objective Optimization; Distance; Prognostik; Hälsoindikatorkonstruktion; Återstående Livslängd; Multiobjektiv Optimering; Avstånd;

   Sammanfattning : Assessment of machine health and prediction of future failures are critical for maintenance decisions. Many of the existing methods use unsupervised techniques to construct health indicators by measuring the disparity between the current state and either the healthy or the faulty states of the system. LÄS MER