Suche nach „[K.] [Zhu]“ hat 2 Publikationen gefunden
Suchergebnis als PDF
    NachhaltigElektrotechnik und MedientechnikIQMA


    Christoph Metzke, Werner Frammelsberger, Jonas Weber, Fabian Kühnel, K. Zhu, M. Lanza, Günther Benstetter

    On the Limits of Scanning Thermal Microscopy of Ultrathin Films

    Materials, vol. 13, no. 3


    DOI: 10.3390/ma13030518

    Abstract anzeigen

    Heat transfer processes in micro- and nanoscale devices have become more and more important during the last decades. Scanning thermal microscopy (SThM) is an atomic force microscopy (AFM) based method for analyzing local thermal conductivities of layers with thicknesses in the range of several nm to µm. In this work, we investigate ultrathin films of hexagonal boron nitride (h-BN), copper iodide in zincblende structure (γ-CuI) and some test sample structures fabricated of silicon (Si) and silicon dioxide (SiO2) using SThM. Specifically, we analyze and discuss the influence of the sample topography, the touching angle between probe tip and sample, and the probe tip temperature on the acquired results. In essence, our findings indicate that SThM measurements include artefacts that are not associated with the thermal properties of the film under investigation. We discuss possible ways of influence, as well as the magnitudes involved. Furthermore, we suggest necessary measuring conditions that make qualitative SThM measurements of ultrathin films of h-BN with thicknesses at or below 23 nm possible.

    DigitalAngewandte Informatik

    Beitrag (Sammelband oder Tagungsband)

    K. Zhu, Marcus Barkowsky, M. Shen, P. Callet, D. Saupe

    Optimizing feature pooling and prediction models of VQA algorithms

    2014 IEEE International Conference on Image Processing (ICIP)


    Abstract anzeigen

    In this paper, we propose a strategy to optimize feature pooling and prediction models of video quality assessment (VQA) algorithms with a much smaller number of parameters than methods based on machine learning, such as neural networks. Based on optimization, the proposed mapping strategy is composed of a global linear model for pooling extracted features, a simple linear model for local alignment in which local factors depend on source videos, and a non-linear model for quality calibration. Also, a reduced-reference VQA algorithm is proposed to predict the local factors from the source video. In the IRCCyN/IVC video database of content influence and the LIVE mobile video database, the performance of VQA algorithms is improved significantly by local alignment. The proposed mapping strategy with prediction of local factors outperforms one no-reference VQA metric and is comparable to one full-reference VQA metric. Thus predicting the local factors in local alignment based on video content will be a promising new approach for VQA.