Sökning: "Faltningsnät"

Visar resultat 1 - 5 av 8 uppsatser innehållade ordet Faltningsnät.

1. 1. Meta-Pseudo Labelled Multi-View 3D Shape Recognition

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

   Författare :Fehmi Ayberk Uçkun; [2023]
   Nyckelord :3D shape recognition; 3D object classification; 3D shape retrieval; 3D object retrieval; Automatic labelling; Semi-supervised learning; Pseudo labelling; Meta Pseudo Labelling; Multi-View Convolutional Neural Networks; Shape descriptors; Multi-view representations; Deeplearning; 3D-formigenkänning; 3D-objektklassificering; 3D-formhämtning; Hämtning av 3D-objekt; Automatisk märkning; Halv-vägledd lärning; Pseudomärkning; Meta Pseudo-märkning; Multi-View Faltningsnät; Formbeskrivningar; Multi-view representation; Djupinlärning;

   Sammanfattning : The field of computer vision has long pursued the challenge of understanding the three-dimensional world. This endeavour is further fuelled by the increasing demand for technologies that rely on accurate perception of the 3D environment such as autonomous driving and augmented reality. LÄS MER

3. 2. Estimation of Height, Weight, Sex and Age from Magnetic Resonance Images using 3D Convolutional Neural Networks

   Master-uppsats, Linköpings universitet/Institutionen för medicinsk teknik

   Författare :Carl Nimhed; [2022]
   Nyckelord :mr; magnetic resonance; machine learning; deep learning;

   Sammanfattning : Magnetic resonance imagining is a non-invasive 3D imaging technology widely used in the medical field for partial and full body scans. AMRA Medical AB is a medical company which combines MRI images with additional patient attributes such as height, weight, sex and age to perform analysis such as body composition profiling. LÄS MER

4. 3. Real-time Human Detection using Convolutional Neural Networks with FMCW RADAR RGB data

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Anna Phan; Rogelio Medina; [2022]
   Nyckelord :Human Detection; Machine Learning; Convolutional Neural Networks; YOLO; FMCW Radar; Human Detection Evaluation; Människodetektering; Maskininlärning; Neurala faltningsnät; Djupa faltningsnät; YOLO; FMCW Radar; Utvärdering;

   Sammanfattning : Machine learning has been employed in the automotive industry together with cameras to detect objects in surround sensing technology. You Only Look Once is a state-of-the-art object detection algorithm especially suitable for real-time applications due to its speed and relatively high accuracy compared to competing methods. LÄS MER

5. 4. Funktionell PCA mot Artificiella Neuronnät

   Kandidat-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

   Författare :Freja Nordh; Mattis Hallberg; Shayan Mollahosseini; Jack Sandberg; Erik Jansson; Philip Gard; [2021-07-01]
   Nyckelord :;

   Sammanfattning : Denna rapport fokuserar på jämförelsen av några olika klassificeringsmetoder applicerade på bilddatan Fashion-MNIST. De olika metoderna är artificiella neurala nätverk och funktionell principalkomponentanalys och principalkomponentanalys. För de neurala nätverken har vi två typer: CNN och FNN. LÄS MER

7. 5. Evaluating deep learning models for electricity spot price forecasting

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

   Författare :Mia Zdybek; [2021]
   Nyckelord :Time series forecasting; Electricity price forecasting; Machine Learning; Deep learning; Multi-layer perceptron; Long short-term memory; Convolutional neural network; Tidsserieprediktion; Prognostisering av elspotpriser; Maskininlärning; Djupinlärning; Flerskikts-perceptron; Lågt korttidsminne; Neurala faltningsnät;

   Sammanfattning : Electricity spot prices are difficult to predict since they depend on different unstable and erratic parameters, and also due to the fact that electricity is a commodity that cannot be stored efficiently. This results in a volatile, highly fluctuating behavior of the prices, with many peaks. LÄS MER