Harbin Engineering University

About: Harbin Engineering University is a education organization based out in Harbin, Heilongjiang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 31149 authors who have published 27940 publications receiving 276787 citations. The organization is also known as: HEU.

Semi-supervised classification for hyperspectral imagery based on spatial-spectral Label Propagation

Abstract: Graph-based classification algorithms have gained increasing attention in semi-supervised classification. Nevertheless, the graph cannot fully represent the inherent spatial distribution of the data. In this paper, a new classification methodology based on the spatial-spectral Label Propagation is proposed for semi-supervised classification of hyperspectral imagery. The spatial information was used in two aspects: on the one hand, the spatial features extracted by a 2-D Gabor filter were stacked with spectral features; on the other hand, the width of the Gaussian function, which was used to construct graph, was determined with an adaptive method. Subsequently, the unlabeled samples from the spatial neighbors of the labeled samples were selected and the spatial graph was constructed based on spatial smoothness. Finally, labels were propagated from labeled samples to unlabeled samples with spatial-spectral graph to update the training set for a basic classifier (e.g., Support Vector Machine, SVM). Experiments on four hyperspectral datasets show that the proposed Spatial-Spectral Label Propagation based on the SVM (SS-LPSVM) can effectively represent the spatial information in the framework of semi-supervised learning and consistently produces greater classification accuracy than the standard SVM, the Laplacian Support Vector Machine (LapSVM), Transductive Support Vector Machine (TSVM) and the Spatial-Contextual Semi-Supervised Support Vector Machine (SCS 3 VM).

Growth of CoFe2O4 hollow nanoparticles on graphene sheets for high-performance electromagnetic wave absorbers

Abstract: CoFe2O4 hollow nanoparticles with an average diameter and shell thickness of about 9.0 nm and 3.0 nm, respectively, were grown on graphene sheets. The hybrid exhibited excellent electromagnetic wave absorption properties with all of the minimal reflection losses below −10 dB at a thickness of 1.5–5.0 mm, superior to the hybrid based on CoFe2O4 solid nanoparticles and recently reported absorbers. Our results open a novel way for fabrication of hollow nanoparticles on graphene sheets for high-performance electromagnetic wave absorbers.

Honeycomb-Satellite Structured pH/H2O2-Responsive Degradable Nanoplatform for Efficient Photodynamic Therapy and Multimodal Imaging

Abstract: The oxygen-deprived environment of a solid tumor is still great restriction in achieving an efficient photodynamic therapy (PDT). In this work, we developed a smart pH-controllable and H2O2-responsive nanoplatform with degradable property, which was based on honeycomb manganese oxide (hMnO2) nanospheres loaded with Ce6-sensitized core–shell–shell structured up-conversion nanoparticles (NaGdF4:Yb/Er,Tm@NaGdF4:Yb@NaNdF4:Yb) (abbreviated as hMUC). In the system, the speedy breakup of the as-prepared hMnO2 nanostructures results in release of loaded Ce6-sensitized UCNPs under the condition of H2O2 in acid solution. When exposed to tissue-penetrable 808 nm laser, up-conversion nanoparticles (UCNPs) emit higher-energy visible photons which would be absorbed by Ce6 to yield cytotoxic reactive oxygen species (ROS), thus triggering PDT treatment naturally. Moreover, the in vitro and in vivo experiments demonstrate that hMUC sample with the honeycomb-satellite structure can serve as multimodal bioimaging contrast a...