Sökning: "Classification Algorithms"

Visar resultat 1 - 5 av 504 uppsatser innehållade orden Classification Algorithms.

  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. 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

  4. 3. Optimization of Speed vs. Accuracy Trade-off in State-of-the-Art Object Detectors for Traffic Light Detection

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

    Författare :Vikash Lal Dodani; [2023]
    Nyckelord :Machine Learning; Computer Vision; Traffic Lights Detection; Self-Driving Cars; BOSCH; BSTLD; LISA;

    Sammanfattning : Traffic lights detection systems are an important area of research, aimed towards improving the accuracy and response time of self-driving vehicles when faced with traffic signals. This project attempted to find a solution for the speed-accuracy trade-off faced by traffic light detection systems. LÄS MER

  5. 4. Automatic event detection oncontinuous glucose datausing neural networks

    Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :David Borghäll; [2023]
    Nyckelord :Automatic Event Detection; Continuous Glucose Monitor; Deep Learning; Diabetes Mellitus; Automatisk Eventdetektion; Kontinuerlig Glukosmätare; Djupinlärning; Diabetes;

    Sammanfattning : Automatically detecting events for people with diabetes mellitus using continuousglucose monitors is an important step in allowing insulin pumps to automaticallycorrect the blood glucose levels and for a more hands-off approach to thedisease. The automatic detection of events could also aid physicians whenassisting their patients when referring to their continuous glucose monitordata. LÄS MER

  7. 5. Identification of Fibers in Micro-CT Images of Paperboard Using Deep Learning

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Hållfasthetslära; Lunds universitet/Institutionen för byggvetenskaper

    Författare :David Rydgård; [2023]
    Nyckelord :Fiber networks; Paperboard mechanics; Deep learning; Tomography; Image analysis; Technology and Engineering;

    Sammanfattning : This master thesis project explores the possibility of using deep learning to segment individual fibers in three-dimensional tomography images of paperboard fiber networks. We test a method which has previously been used to segment fibers in images of glass fiber reinforced polymers. LÄS MER