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您的检索式：作者名="LYU Xiaomeng"
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| 1 | Automatic texture exemplar extraction based on global and local textureness measures显示文摘Texture synthesis is widely used for modeling the appearance of virtual objects. However,traditional texture synthesis techniques emphasize creation of optimal target textures, and pay insufficient attention to choice of suitable input texture exemplars.Currently, obtaining texture exemplars from natural images is a labor intensive task for the artists,requiring careful photography and significant postprocessing. In this paper, we present an automatic texture exemplar extraction method based on global and local textureness measures. To improve the efficiency of dominant texture identification, we first perform Poisson disk sampling to randomly and uniformly crop patches from a natural image. For global textureness assessment, we use a GIST descriptor to distinguish textured patches from non-textured patches,in conjunction with SVM prediction. To identify real texture exemplars consisting solely of the dominant texture, we further measure the local textureness of a patch by extracting and matching the local structure(using binary Gabor pattern(BGP)) and dominant color features(using color histograms) between a patch and its sub-regions. Finally, we obtain optimal texture exemplars by scoring and ranking extracted patches using these global and local textureness measures.We evaluate our method on a variety of images with different kinds of textures. A convincing visual comparison with textures manually selected by an artist and a statistical study demonstrate its effectiveness. | Huisi Wu Xiaomeng Lyu Zhenkun Wen | 2018 | Computational Visual Media2018，4，2： | 1 |
| 2 | Bioassay of Carcinoembryonic Antigens by Organic Field-effect Transistors Based on D-A Type Conjugated Polymer显示文摘Biosensors based on organic field-effect transistors(OFETs)are one of the most promising electronic devices for emerging bioanalytical applications.The selection of organic semiconductors(OSCs)is essential to improve the sensitivity and reliability of this kind of biosensors.Given the good field effect performance and tunable structures of D-A type conjugated polymers,here,we design two D-A type copolymers[P(BDT-co-DPP2T-ThC_(2))and P(BDT-co-DPP2T-Th)],which are applied as the OSC layers.With carcinoembryonic antigen antibody(anti-CEA)adsorbed onto the OSC layers as the recognition sites,OFETs based biosensors for CEA detection are developed.The experimental findings support that the attachment of ester side groups onto the polymer backbone[as for P(BDT-co-DPP2T-ThC_(2))]is favorable for improved solubility and filming properties of the polymer.The introduction of ester side groups affects molecular stacking and enhances intermolecular forces.The resultant devices show high charge mobility and antibody adsorption ability,both of which are critical for sensitive and facile detection of CEA biomarkers.The reliable determination of CEA down to the picomolar level is determined.It is expected that this kind of biosensors fabricated by D-A type conducting polymers will open new avenues toward the early diagnosis,real-time monitoring and treatment of future cancer diseases. | LYU Xiaomeng DUAN Yuchen CHEN Yulan CHENG Shanshan | 2023 | Chemical Research in Chinese Universities2023，39，6： | 0 |
| 3 | Alarm-Based Root Cause Analysis Based on Weighted Fault Propagation Topology for Distributed Information Network显示文摘A distributed information network with complex network structure always has a challenge of locating fault root causes.In this paper,we propose a novel root cause analysis(RCA)method by random walk on the weighted fault propagation graph.Different from other RCA methods,it mines effective features information related to root causes from offline alarms.Combined with the information,online alarms and graph relationship of network structure are used to construct a weighted graph.Thus,this approach does not require operational experience and can be widely applied in different distributed networks.The proposed method can be used in multiple fault location cases.The experiment results show the proposed approach achieves much better performance with 6%higher precision at least for root fault location,compared with three baseline methods.Besides,we explain how the optimal parameter’s value in the random walk algorithm influences RCA results. | LYU Xiaomeng CHEN Hao WU Zhenyu HAN Junhua GUO Huifeng | 2022 | ZTE Communications2022，20，3： | 0 |
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