Search for dissertations about: "Deep level"

Showing result 1 - 5 of 336 swedish dissertations containing the words Deep level.

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

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

    Abstract : 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. READ MORE

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

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

    Abstract : 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. READ MORE

  3. 3. Deep levels in SiC

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

    Abstract : 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. READ MORE

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

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

    Abstract : 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. READ MORE

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

    Author : Pär Omling; Fasta tillståndets fysik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Fysicumarkivet A:1983:Omling;

    Abstract : [abstract missing].... READ MORE