Sökning: "Deep level"

Visar resultat 1 - 5 av 358 avhandlingar innehållade orden Deep level.

  1. 1. Deep Learning on the Edge : A Flexible Multi-level Optimization Approach

    Författare :Nesma Rezk; Magnus Jonsson; Mahdi Fazeli; Antonio Carlos Schneider Beck; Högskolan i Halmstad; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

    Sammanfattning : Recent advances in Deep Learning (DL) research have been adopted in a wide variety of applications, including autonomous driving, AI in health care, and smart homes. In parallel, research in high-performance embedded computing has resulted in advanced hardware platforms that offer enhanced performance and energy efficiency for demanding computations. LÄS MER

  2. 2. Optical Characterization of Deep Level Defects in SiC

    Författare :Andreas Gällström; Erik Janzén; Ivan Ivanov; Jörg Weber; Linköpings universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : Silicon Carbide (SiC) has long been considered a promising semiconductor material for high power devices, and has also recently found to be one of the emergent materials for quantum computing. Important for these applications are both the quality and purity of the crystal. LÄS MER

  3. 3. Deep levels in SiC

    Författare :Franziska C. Beyer; Erik Janzén; Carl Hemmingsson; Jörg Weber; Linköpings universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP;

    Sammanfattning : Silicon carbide (SiC) has been discussed as a promising material for high power bipolar devices for almost twenty years. Advances in SiC crystal growth especially the development of chemical vapor deposition (CVD) have enabled the fabrication of high quality material. LÄS MER

  4. 4. Self-supervised deep learning and EEG categorization

    Författare :Mats Svantesson; Magnus Thordstein; Håkan Olausson; Anders Eklund; Gerald Cooray; Linköpings universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; EEG; Deep Learning; Self-supervised; Interrater Agreement; T- SNE;

    Sammanfattning : Deep learning has the potential to be used to improve and streamline EEG analysis. At the present, classifiers and supervised learning dominate the field. Supervised learning depends on target labels which most often are created by human experts manually classifying data. LÄS MER

  5. 5. Epitaxial growth and deep level characterization of GaAs₁₋xPx

    Författare :Pär Omling; Fasta tillståndets fysik; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Fysicumarkivet A:1983:Omling;

    Sammanfattning : [abstract missing].... LÄS MER