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dc.contributor.advisor 박상현 -
dc.contributor.author Mungi Kwon -
dc.date.accessioned 2020-06-22T16:00:35Z -
dc.date.available 2020-06-22T16:00:35Z -
dc.date.issued 2020 -
dc.identifier.uri http://dgist.dcollection.net/common/orgView/200000285883 en_US
dc.identifier.uri http://hdl.handle.net/20.500.11750/11958 -
dc.description Nuclear, Instance segmentation, Deep convolutional neural network, Watershed algorithm, Siamese network, Using unlabeled data, Label smoothing -
dc.description.statementofresponsibility prohibition -
dc.description.tableofcontents Ⅰ. INTRODUCTION 1
1.1 Introduction 1
1.2 Related works 2
ⅠⅠ. Method 4
2.1 Nuclei segmentation using deep learning based watershed algorithm 4
A. Deep learning based watershed algorithm 4
B. Implementation details 5
2.2 Separation of adjacent nuclei using a Siamese neural network 5
A. Overall procedure 6
B. Proposed network 7
C. Implementation details 8
2.3 Segmentation using unlabeled data 9
A. Label smoothing 9
B. Implementation details 10
ⅠⅠⅠ. Experimental results 10
3.1 Data set 10
3.2 Evaluation metrics 11
3.3 Comparison methods 11
3.4 Segmentation accuracy 13
3.5 Classification accuracy 13
3.6 Accuracy with labeled and unlabeled data 15
VI. Conclusion 17
References 18
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dc.format.extent 30 -
dc.language eng -
dc.publisher DGIST -
dc.title Nuclear Segmentation Using Convolutional Neural Networks with Limited Training Data -
dc.type Thesis -
dc.identifier.doi 10.22677/Theses.200000285883 -
dc.description.degree Master -
dc.contributor.department Robotics Engineering -
dc.contributor.coadvisor Jaeyoun Hwang -
dc.date.awarded 2020-02 -
dc.publisher.location Daegu -
dc.description.database dCollection -
dc.citation XT.RM 권36 202002 -
dc.date.accepted 2020-01-20 -
dc.contributor.alternativeDepartment 로봇공학전공 -
dc.embargo.liftdate 2022-11-01 -
dc.contributor.affiliatedAuthor Hwang, Jaeyoun -
dc.contributor.affiliatedAuthor Kwon, Mungi -
dc.contributor.affiliatedAuthor Park, Sanghyun -
dc.contributor.alternativeName 황재윤 -
dc.contributor.alternativeName 권문기 -
dc.contributor.alternativeName Sanghyun Park -
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