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Träfflista för sökning "WFRF:(Nguyen Tuan V) ;hsvcat:1"

Sökning: WFRF:(Nguyen Tuan V) > Naturvetenskap

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  • Nguyen, T. N. Anh, et al. (författare)
  • Depth-Dependent Magnetization Profiles of Hybrid Exchange Springs
  • 2014
  • Ingår i: Physical Review Applied. - 2331-7019. ; 2:4
  • Tidskriftsartikel (refereegranskat)abstract
    • We report on the magnetization depth profile of a hybrid exchange-spring system in which a Co/Pd multilayer with perpendicular anisotropy is coupled to a CoFeB thin film with in-plane anisotropy. The competition between these two orthogonal anisotropies promotes a strong depth dependence of the magnetization orientation. The angle of the magnetization vector is sensitive both to the strength of the individual anisotropies and to the local exchange constant and is thus tunable by changing the thickness of the CoFeB layer and by substituting Ni for Pd in one layer of the Co/Pd stack. The resulting magnetic depth profiles are directly probed by element-specific x-ray magnetic circular dichroism of the Fe and Ni layers located at different average depths. The experimental results are corroborated by micromagnetic simulations.
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3.
  • Do, Thanh Toan, et al. (författare)
  • Simultaneous feature aggregating and hashing for compact binary code learning
  • 2019
  • Ingår i: IEEE Transactions on Image Processing. - 1941-0042 .- 1057-7149. ; 28:10, s. 4954-4969
  • Tidskriftsartikel (refereegranskat)abstract
    • Representing images by compact hash codes is an attractive approach for large-scale content-based image retrieval. In most state-of-the-art hashing-based image retrieval systems, for each image, local descriptors are first aggregated as a global representation vector. This global vector is then subjected to a hashing function to generate a binary hash code. In previous works, the aggregating and the hashing processes are designed independently. Hence, these frameworks may generate suboptimal hash codes. In this paper, we first propose a novel unsupervised hashing framework in which feature aggregating and hashing are designed simultaneously and optimized jointly. Specifically, our joint optimization generates aggregated representations that can be better reconstructed by some binary codes. This leads to more discriminative binary hash codes and improved retrieval accuracy. In addition, the proposed method is flexible. It can be extended for supervised hashing. When the data label is available, the framework can be adapted to learn binary codes which minimize the reconstruction loss with respect to label vectors. Furthermore, we also propose a fast version of the state-of-the-art hashing method Binary Autoencoder to be used in our proposed frameworks. Extensive experiments on benchmark datasets under various settings show that the proposed methods outperform the state-of-the-art unsupervised and supervised hashing methods.
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  • Thang, Truong Cong, et al. (författare)
  • Design and implementation of an e-Health system for depression detection
  • 2015
  • Konferensbidrag (refereegranskat)abstract
    • We present the design and implementation of a cost-effective e-Health system for automatic depression detection. The system is based on a client-server architecture, where clients are popular mobile devices. For practical deployment, various factors that affect the accuracy and speed of depression detection are discussed and evaluated with extensive experiments.
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