Sökning: "Neural conversion"

Visar resultat 1 - 5 av 16 uppsatser innehållade orden Neural conversion.

1. 1. Performance analysis: CNN model on smartphones versus on cloud : With focus on accuracy and execution time

   Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Författare :Stegmayr Klas; Johansson Edwin; [2023]
   Nyckelord :CNN; Deep learning; iOS; Core ML; CIFAR-10;

   Sammanfattning : In the modern digital landscape, mobile devices serve as crucial data generators.Their usage spans from simple communication to various applications such as userbehavior analysis and intelligent applications. However, privacy concerns associatedwith data collection are persistent. LÄS MER

3. 2. Image Colorization Based on Deep Learning

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

   Författare :Tao Deng; [2023]
   Nyckelord :Image colorization; Deep Learning; Convolutional Neural Network; Generative Adversarial Network; Färgläggning av bilder; djupinlärning; Konvolutionella Neurala Nätverk; Generativa Adversariella Nätverk;

   Sammanfattning : With the development of artificial intelligence, there is a clear trend to combine computer technology with traditional industries. In recent years, with the development of digital media technology, many methods for coloring gray-scale images have been proposed. LÄS MER

4. 3. Minimizing the expected opportunity loss by optimizing the ordering of shipping methods in e-Commerce using Machine Learning

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Jonatan Ay; Jamil Azrak; [2022]
   Nyckelord :statistics; machine learning; applied mathematics; e-commerce; statistik; maskininlärning; tillämpad matematisk statistik; e-handel;

   Sammanfattning : The shopping industry is rapidly changing as the technology is advancing. This is especially true for the online industry where consumers are nowadays able to to shop much of what the need over the internet. LÄS MER

5. 4. Spiking Reinforcement Learning for Robust Robot Control Under Varying Operating Conditions

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

   Författare :Philipp Mondorf; [2022]
   Nyckelord :;

   Sammanfattning : Over the last few years, deep reinforcement learning (RL) has gained increasing popularity for its successful application to a variety of complex control and decision-making tasks. As the demand for deep RL algorithms deployed in challenging real-world environments grows, their robustness towards uncertainty, disturbances and perturbations of the environment becomes more and more important. LÄS MER

7. 5. LaMOSNet: Latent Mean-Opinion-Score Network for Non-intrusive Speech Quality Assessment : Deep Neural Network for MOS Prediction

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

   Författare :Fredrik Cumlin; [2022]
   Nyckelord :Speech naturalness assessment; Speech quality assessment; Mean opinion score; Voice conversion challenge; Semi-supervised learning; Noisy labels.; Naturligt tal bedömning; Ljudkvalitetsbedömning; Medel bedömningsvärdet; Talkonverteringsutmaningen; Semi-övervakad inlärning; Varierande märkningar.;

   Sammanfattning : Objective non-intrusive speech quality assessment aimed to emulate and correlate with human judgement has received more attention over the years. It is a difficult problem due to three reasons: data scarcity, noisy human judgement, and a potential uneven distribution of bias of mean opinion scores (MOS). LÄS MER