李晓 - 西安电子科技大学 - 计算机科学与技术学院

个人简介

个人简介李晓，西安电子科技大学博士毕业。机器学习方面包括小样本学习，零样本学习，迁移学习及其应用等。深度学习方面包括生成式对抗网络，卷积神经网络等。计算机视觉方面包括图像分类，物体识别，RGB-D图像分类和行为识别等。已经发表了多篇高质量的SCI论文，发表在Knowledge-BasedSystems，PatternRecognition，Neurocomputing等国际期刊上。主持和参与多项科研项目，包括青年科学基金项目和博士后面上项目等。

研究领域

1.机器学习：零样本学习，小样本学习，迁移学习，域自适应等 2.计算机视觉：图像分类，物体识别，行为识别等 3.深度学习：卷积神经网络，生成式对抗网络等

近期论文

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[1]XiaoLi,MinFang,DazhengFeng,HaikunLi,JinqiaoWu.Prototypeadjustmentforzeroshotclassification[J].SignalProcessing:ImageCommunication,2019. [2]XiaoLi,MinFang,DazhengFeng,HaikunLi,JinqiaoWu.ZeroshotlearningbypartialtransferfromsourcedomainwithL2,1normconstraint[J].JournalofVisualCommunicationandImageRepresentation,2019,58:701-711. [3]XiaoLi,MinFang,DazhengFeng,HaikunLi,JinqiaoWu.Learningunseenvisualprototypesforzero-shotclassification[J].Knowledge-BasedSystems,2018,160:176-187. [4]XiaoLi,MinFang,JinqiaoWu.Zero-shotclassificationbytransferringknowledgeandpreservingdatastructure[J].Neurocomputing,2017,238:76-83. [5]XiaoLi,MinFang,Ju-JieZhang,JinqiaoWu.LearningCoupledClassifierswithRGBimagesforRGB-Dobjectrecognition[J].PatternRecognition,2017,61:433-446. [6]XiaoLi,MinFang,Ju-JieZhang,JinqiaoWu.DomainadaptationfromRGB-DtoRGBimages[J].SignalProcessing,2017,131:27-35. [7]XiaoLi,MinFang,Ju-JieZhang,JinqiaoWu.Sampleselectionforvisualdomainadaptationviasparsecoding[J].SignalProcessing:ImageCommunication,2016,44:92-100. [8]XiaoLi,MinFang,Ju-JieZhang.Projectedtransfersparsecodingforcrossdomainimagerepresentation[J].JournalofVisualCommunicationandImageRepresentation,2015,33:265-272 [9]XiaoLi,MinFang,HongchunWang,Ju-JieZhang.Supervisedtransferkernelsparsecodingforimageclassification[J].PatternRecognitionLetters,2015,68:27-33. [10]XiaoLi,MinFang,JinqiaoWu,LiangHe,XianTian.Imageclassificationbysemisupervisedsparsecodingwithconfidentunlabeledsamples[J].JournalofElectronicImaging,2017,26(5):053013. [11]ZhangJJ,FangM,LiX.ClusteredIntrinsicLabelCorrelationsforMulti-labelClassification[J].ExpertSystemswithApplications,2017,81:134-146. [12]ZhangJJ,FangM,WuJQ,Li,X.Robustlabelcompressionformulti-labelclassification[J].Knowledge-BasedSystems,2016,107:32-42. [13]ZhangJJ,FangM,WangH,LiX.Dependencemaximizationbasedlabelspacedimensionreductionformulti-labelclassification[J].EngineeringApplicationsofArtificialIntelligence,2015,45:453-463. [14]ZhangJJ,FangM,LiX.Multi-labellearningwithdiscriminativefeaturesforeachlabel[J].Neurocomputing,2015,154:305-316. [15]FangM,GuoY,ZhangX,LiX.Multi-sourcetransferlearningbasedonlabelsharedsubspace[J].PatternRecognitionLetters,2015,51:101-106.