Research Progress
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12/07 -2017-PCA-based denoising method for division of focal plane polarimeters
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12/07 -2017-Fabrication and photoelectrochemical properties of silicon nanowires/g-C3N4core/shell arrays
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12/07 -2017-Phase switching mechanism for wifi-based long distance networks in industrial real-time applications
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12/07 -2017-A novel approach for extracting viscoelastic parameters of living cells through combination of inverse finite element simulation and Atomic Force Microscopy
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12/07 -2017-High-Throughput Fabrication and Modular Assembly of 3D Heterogeneous Microscale Tissues
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12/07 -2017-Performance Investigation of Multilayer MoS2Thin-Film Transistors Fabricated via Mask-free Optically Induced Electrodeposition
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12/07 -2017-Robustness Analysis of License Plate Visual Positioning Method in Vehicle Collision Warning System
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12/07 -2017-Combining sequence and Gene Ontology for protein module detection in the Weighted Network
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12/07 -2017-Mask-free fabrication of a versatile microwell chip for multidimensional cellular analysis and drug screeningCells are frequently studied because they are basic structural, functional, and biological units of living organisms. Extracting features from cellular behaviors can facilitate decision making in medical diagnoses and represents an important aspect in the development of biomedical engineering. Previous studies have just focused on either the individual cell or cell clusters separately
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12/01 -2017-User attribute discovery with missing labelsIn this paper, we focus on user attribute analysis by recasting such a problem as a multi-task learning issue, where each attribute is considered as an independent task. In comparison with traditional data analysis, the missing labels problem broadly presents for smart sensor data due to some objective / subjective factors, where the label incompleteness increases the difficulty significantly.
