Sökning: "performance for mobile applications"

Visar resultat 1 - 5 av 304 uppsatser innehållade orden performance for mobile applications.

  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. Digitally Controlled Oscillator Topologies for mm-Wave Pulsed Coherent Radar

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Klas Junskog; [2023]
    Nyckelord :oscillators; mm-wave; radar; Technology and Engineering;

    Sammanfattning : The advancement of future generations of wireless communication and radar sensing warrants the need for mm-wave digitally controlled oscillators (DCOs) with high-frequency trade-offs in consideration. The purpose of this project is to investigate DCO topologies inspired from scientific literature. LÄS MER

  4. 3. Optimizing Realistic 3D Facial Models for VR Avatars through Mesh Simplification

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

    Författare :Beiqian Liu; [2023]
    Nyckelord :Mesh Simplification; Virtual Reality; Realistic Avatars; 3D Face Reconstruction;

    Sammanfattning : The use of realistic 3D avatars in Virtual Reality (VR) has gained significant traction in applications such as telecommunication and gaming, offering immersive experiences and face-to-face interactions. However, standalone VR devices often face limitations in computational resources and real-time rendering requirements, necessitating the optimization of 3D models through mesh simplification to enhance performance and ensure a smooth user experience. LÄS MER

  5. 4. Comparative Study of the Inference of an Image Quality Assessment Algorithm : Inference Benchmarking of an Image Quality Assessment Algorithm hosted on Cloud Architectures

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

    Författare :Jesper Petersson; [2023]
    Nyckelord :Machine learning; Cloud Computing; Benchmark; Image Quality Assessment; Maskininlärning; Molntjänster; Jämförelse; Bildkvalitetsbedömning;

    Sammanfattning : an instance has become exceedingly more time and resource consuming. To solve this issue, cloud computing is being used to train and serve the models. However, there’s a gap in research where these cloud computing platforms have been evaluated for these tasks. LÄS MER

  7. 5. Smart Tracking for Edge-assisted Object Detection : Deep Reinforcement Learning for Multi-objective Optimization of Tracking-based Detection Process

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

    Författare :Shihang Zhou; [2023]
    Nyckelord :Tracking-By-Detection; Deep Reinforcement Learning; Multi-Objective Optimization; Spårning genom detektion; Djup förstärkningsinlärning; Multiobjektiv optimering;

    Sammanfattning : Detecting generic objects is one important sensing task for applications that need to understand the environment, for example eXtended Reality (XR), drone navigation etc. However, Object Detection algorithms are particularly computationally heavy for real-time video analysis on resource-constrained mobile devices. LÄS MER