Sökning: "aktivitetsigenkänning"

Visar resultat 1 - 5 av 15 uppsatser innehållade ordet aktivitetsigenkänning.

  1. 1. 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. 2. Human Activity Recognition Models and Step Counter With Smartphone Sensor Data

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

    Författare :Josef Afreim; Simon Bossér; [2023]
    Nyckelord :;

    Sammanfattning : In this time of technology, with the availability of wearable sensors and copiousamounts of cheap data, new uses of machine learning emerge. Tasks that were previouslyheld-back by a lack of data and computation power are today more feasible and useful thanever. Human activity recognition (HAR) is one such task. LÄS MER

  4. 3. Human Activity Recognition and Step Counter Using Smartphone Sensor Data

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

    Författare :Fredrik Jansson; Gustaf Sidén; [2022]
    Nyckelord :Human Activity Recognition; Step Counter; Smartphone Sensor Data; Accelerometer; Gyroscope; Random Forest.;

    Sammanfattning : Human Activity Recognition (HAR) is a growing field of research concerned with classifying human activities from sensor data. Modern smartphones contain numerous sensors that could be used to identify the physical activities of the smartphone wearer, which could have applications in sectors such as healthcare, eldercare, and fitness. LÄS MER

  5. 4. Classification Models for Activity Recognition using Smart Phone Accelerometers

    Magister-uppsats, Umeå universitet/Statistik

    Författare :Biswas Kumar; [2022]
    Nyckelord :;

    Sammanfattning : The huge amount of data generated by accelerometers in smartphones creates new opportunities for useful data mining applications. Machine Learning algorithms can be effectively used for tasks such as the classification and clustering of physical activity patterns. LÄS MER

  7. 5. Step Counter and Activity Recognition Using Smartphone IMUs

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

    Författare :Anton Israelsson; Max Strandell; [2022]
    Nyckelord :Step Counting; Human Activity Recognition; IMU; Smartphone;

    Sammanfattning : Fitness tracking is a rapidly growing market as more people desire to take better control over their lives. And the growing availability of smartphones with sensitive sensors makes it possible for anyone to take part. LÄS MER