skip to content
Domain adaptation and representation transfer and medical image learning with less labels and imperfect data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings Preview this item
ClosePreview this item
Checking...

Domain adaptation and representation transfer and medical image learning with less labels and imperfect data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings

Author: Qian Wang, (Biomedical engineer); Fausto Milletari; Hien V Nguyen; et al
Publisher: Cham, Switzerland : Springer, 2019.
Series: LNCS sublibrary., SL 6,, Image processing, computer vision, pattern recognition, and graphics ;, 11795.; Lecture notes in computer science, 11795.; LNCS sublibrary., SL 6,, Image processing, computer vision, pattern recognition, and graphics.
Edition/Format:   eBook : Document : Conference publication : EnglishView all editions and formats
Summary:
This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. DART 2019 accepted 12 papers for publication out of 18 submissions. The papers deal with  Read more...
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

Find a copy online

Links to this item

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Genre/Form: Electronic books
Conference papers and proceedings
Congresses
Material Type: Conference publication, Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Qian Wang, (Biomedical engineer); Fausto Milletari; Hien V Nguyen; et al
ISBN: 9783030333911 3030333914
OCLC Number: 1123191840
Notes: Includes author index.
Description: 1 online resource (xvii, 254 pages) : illustrations (some color).
Contents: DART 2019 --
Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation --
Temporal Consistency Objectives Regularize the Learning of Disentangled Representations --
Multi-layer Domain Adaptation for Deep Convolutional Networks --
Intramodality Domain Adaptation using Self Ensembling and Adversarial Training --
Learning Interpretable Disentangled Representations using Adversarial VAEs --
Synthesising Images and Labels Between MR Sequence Types With CycleGAN --
Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning --
Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans --
A Pulmonary Nodule Detection Method Based on Residual Learning and Dense Connection --
Harmonization and Targeted Feature Dropout for Generalized Segmentation: Application to Multi-site Traumatic Brain Injury Images --
Improving Pathological Structure Segmentation Via Transfer Learning Across Diseases --
Generating Virtual Chromoendoscopic Images and Improving Detectability and Classification Performance of Endoscopic Lesions --
MIL3ID 2019 --
Self-supervised learning of inverse problem solvers in medical imaging --
Weakly Supervised Segmentation of Vertebral Bodies with Iterative Slice-propagation --
A Cascade Attention Network for Liver Lesion Classification in Weakly-labeled Multi-phase CT Images --
CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT --
Active Learning Technique for Multimodal Brain Tumor Segmentation using Limited Labeled Images --
Semi-supervised Learning of Fetal Anatomy from Ultrasound --
Multi-modal segmentation with missing MR sequences using pre-trained fusion networks --
More unlabelled data or label more data? A study on semi-supervised laparoscopic image segmentation --
Few-shot Learning with Deep Triplet Networks for Brain Imaging Modality Recognition --
A Convolutional Neural Network Method for Boundary Optimization Enables Few-Shot Learning for Biomedical Ima ge Segmentation --
Transfer Learning from Partial Annotations for Whole Brain Segmentation --
Learning to Segment Skin Lesions from Noisy Annotations --
A Weakly Supervised Method for Instance Segmentation of Biological Cells --
Towards Practical Unsupervised Anomaly Detection on Retinal Images --
Fine tuning U-Net for ultrasound image segmentation: which layers --
Multi-task Learning for Neonatal Brain Segmentation Using 3D Dense-Unet with Dense Attention Guided by Geodesic Distance.
Series Title: LNCS sublibrary., SL 6,, Image processing, computer vision, pattern recognition, and graphics ;, 11795.; Lecture notes in computer science, 11795.; LNCS sublibrary., SL 6,, Image processing, computer vision, pattern recognition, and graphics.
Other Titles: DART 2019
MIL3ID 2019
Responsibility: Qian Wang, Fausto Milletari, Hien V. Nguyen et al. (Eds.)

Abstract:

This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning  Read more...

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.
Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


\n\n

Primary Entity<\/h3>\n
<http:\/\/www.worldcat.org\/oclc\/1123191840<\/a>> # Domain adaptation and representation transfer and medical image learning with less labels and imperfect data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Book<\/a>, schema:CreativeWork<\/a>, schema:MediaObject<\/a> ;\u00A0\u00A0\u00A0\nlibrary:oclcnum<\/a> \"1123191840<\/span>\" ;\u00A0\u00A0\u00A0\nlibrary:placeOfPublication<\/a> <http:\/\/id.loc.gov\/vocabulary\/countries\/sz<\/a>> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/dewey.info\/class\/616.0754\/e23\/<\/a>> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Topic\/diagnostic_imaging_data_processing<\/a>> ; # Diagnostic imaging--Data processing<\/span>\n\u00A0\u00A0\u00A0\nschema:alternateName<\/a> \"MIL3ID 2019<\/span>\" ;\u00A0\u00A0\u00A0\nschema:alternateName<\/a> \"DART 2019<\/span>\" ;\u00A0\u00A0\u00A0\nschema:bookFormat<\/a> schema:EBook<\/a> ;\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Meeting\/international_conference_on_medical_image_computing_and_computer_assisted_intervention_22nd_2019_shenzhen_shi_china<\/a>> ; # International Conference on Medical Image Computing and Computer-Assisted Intervention (22nd : 2019 : Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Meeting\/mil3id_workshop_1st_2019_shenzhen_shi_china<\/a>> ; # MIL3ID (Workshop) (1st : 2019 : Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\nschema:creator<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Meeting\/dart_workshop_1st_2019_shenzhen_shi_china<\/a>> ; # DART (Workshop) (1st : 2019 : Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\nschema:datePublished<\/a> \"2019<\/span>\" ;\u00A0\u00A0\u00A0\nschema:description<\/a> \"DART 2019 -- Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation -- Temporal Consistency Objectives Regularize the Learning of Disentangled Representations -- Multi-layer Domain Adaptation for Deep Convolutional Networks -- Intramodality Domain Adaptation using Self Ensembling and Adversarial Training -- Learning Interpretable Disentangled Representations using Adversarial VAEs -- Synthesising Images and Labels Between MR Sequence Types With CycleGAN -- Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning -- Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans -- A Pulmonary Nodule Detection Method Based on Residual Learning and Dense Connection -- Harmonization and Targeted Feature Dropout for Generalized Segmentation: Application to Multi-site Traumatic Brain Injury Images -- Improving Pathological Structure Segmentation Via Transfer Learning Across Diseases -- Generating Virtual Chromoendoscopic Images and Improving Detectability and Classification Performance of Endoscopic Lesions -- MIL3ID 2019 -- Self-supervised learning of inverse problem solvers in medical imaging -- Weakly Supervised Segmentation of Vertebral Bodies with Iterative Slice-propagation -- A Cascade Attention Network for Liver Lesion Classification in Weakly-labeled Multi-phase CT Images -- CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT -- Active Learning Technique for Multimodal Brain Tumor Segmentation using Limited Labeled Images -- Semi-supervised Learning of Fetal Anatomy from Ultrasound -- Multi-modal segmentation with missing MR sequences using pre-trained fusion networks -- More unlabelled data or label more data? A study on semi-supervised laparoscopic image segmentation -- Few-shot Learning with Deep Triplet Networks for Brain Imaging Modality Recognition -- A Convolutional Neural Network Method for Boundary Optimization Enables Few-Shot Learning for Biomedical Ima ge Segmentation -- Transfer Learning from Partial Annotations for Whole Brain Segmentation -- Learning to Segment Skin Lesions from Noisy Annotations -- A Weakly Supervised Method for Instance Segmentation of Biological Cells -- Towards Practical Unsupervised Anomaly Detection on Retinal Images -- Fine tuning U-Net for ultrasound image segmentation: which layers -- Multi-task Learning for Neonatal Brain Segmentation Using 3D Dense-Unet with Dense Attention Guided by Geodesic Distance.<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:description<\/a> \"This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. DART 2019 accepted 12 papers for publication out of 18 submissions. The papers deal with methodological advancements and ideas that can improve the applicability of machine learning and deep learning approaches to clinical settings by making them robust and consistent across different domains. MIL3ID accepted 16 papers out of 43 submissions for publication, dealing with best practices in medical image learning with label scarcity and data imperfection.<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:editor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Person\/wang_qian_biomedical_engineer<\/a>> ; # (Biomedical engineer) Qian Wang<\/span>\n\u00A0\u00A0\u00A0\nschema:editor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Person\/milletari_fausto<\/a>> ; # Fausto Milletari<\/span>\n\u00A0\u00A0\u00A0\nschema:editor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Person\/nguyen_hien_v<\/a>> ; # Hien V. Nguyen<\/span>\n\u00A0\u00A0\u00A0\nschema:exampleOfWork<\/a> <http:\/\/worldcat.org\/entity\/work\/id\/9582790603<\/a>> ;\u00A0\u00A0\u00A0\nschema:genre<\/a> \"Conference publication<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:genre<\/a> \"Electronic books<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:genre<\/a> \"Conference papers and proceedings<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:inLanguage<\/a> \"en<\/span>\" ;\u00A0\u00A0\u00A0\nschema:isPartOf<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Series\/lecture_notes_in_computer_science<\/a>> ; # Lecture notes in computer science ;<\/span>\n\u00A0\u00A0\u00A0\nschema:isPartOf<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Series\/lncs_sublibrary_sl_6_image_processing_computer_vision_pattern_recognition_and_graphics<\/a>> ; # LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics<\/span>\n\u00A0\u00A0\u00A0\nschema:isPartOf<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Series\/lncs_sublibrary<\/a>> ; # LNCS sublibrary.<\/span>\n\u00A0\u00A0\u00A0\nschema:name<\/a> \"Domain adaptation and representation transfer and medical image learning with less labels and imperfect data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:productID<\/a> \"1123191840<\/span>\" ;\u00A0\u00A0\u00A0\nschema:url<\/a> <https:\/\/doi.org\/10.1007\/978-3-030-33391-1<\/a>> ;\u00A0\u00A0\u00A0\nschema:url<\/a> <https:\/\/ezproxy.lau.edu.lb:2443\/login?url=https:\/\/doi.org\/10.1007\/978-3-030-33391-1<\/a>> ;\u00A0\u00A0\u00A0\nschema:workExample<\/a> <http:\/\/worldcat.org\/isbn\/9783030333911<\/a>> ;\u00A0\u00A0\u00A0\nschema:workExample<\/a> <http:\/\/dx.doi.org\/10.1007\/978-3-030-33391-1<\/a>> ;\u00A0\u00A0\u00A0\numbel:isLike<\/a> <http:\/\/bnb.data.bl.uk\/id\/resource\/GBB9H5806<\/a>> ;\u00A0\u00A0\u00A0\nwdrs:describedby<\/a> <http:\/\/www.worldcat.org\/title\/-\/oclc\/1123191840<\/a>> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n\n

Related Entities<\/h3>\n
<http:\/\/dewey.info\/class\/616.0754\/e23\/<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/dx.doi.org\/10.1007\/978-3-030-33391-1<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:IndividualProduct<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Meeting\/dart_workshop_1st_2019_shenzhen_shi_china<\/a>> # DART (Workshop) (1st : 2019 : Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:Meeting<\/a>, schema:Event<\/a> ;\u00A0\u00A0\u00A0\nschema:location<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Place\/shenzhen_shi_china<\/a>> ; # Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\nschema:name<\/a> \"DART (Workshop) (1st : 2019 : Shenzhen Shi, China),<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Meeting\/international_conference_on_medical_image_computing_and_computer_assisted_intervention_22nd_2019_shenzhen_shi_china<\/a>> # International Conference on Medical Image Computing and Computer-Assisted Intervention (22nd : 2019 : Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:Meeting<\/a>, schema:Event<\/a> ;\u00A0\u00A0\u00A0\nschema:location<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Place\/shenzhen_shi_china<\/a>> ; # Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\nschema:name<\/a> \"International Conference on Medical Image Computing and Computer-Assisted Intervention (22nd : 2019 : Shenzhen Shi, China),<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Meeting\/mil3id_workshop_1st_2019_shenzhen_shi_china<\/a>> # MIL3ID (Workshop) (1st : 2019 : Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:Meeting<\/a>, schema:Event<\/a> ;\u00A0\u00A0\u00A0\nschema:location<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Place\/shenzhen_shi_china<\/a>> ; # Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\nschema:name<\/a> \"MIL3ID (Workshop) (1st : 2019 : Shenzhen Shi, China),<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Person\/milletari_fausto<\/a>> # Fausto Milletari<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Milletari<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Fausto<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Fausto Milletari<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Person\/nguyen_hien_v<\/a>> # Hien V. Nguyen<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Nguyen<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Hien V.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Hien V. Nguyen<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Person\/wang_qian_biomedical_engineer<\/a>> # (Biomedical engineer) Qian Wang<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Wang<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Qian<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"(Biomedical engineer) Qian Wang<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Place\/shenzhen_shi_china<\/a>> # Shenzhen Shi, China),<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Place<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Shenzhen Shi, China),<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Series\/lecture_notes_in_computer_science<\/a>> # Lecture notes in computer science ;<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:PublicationSeries<\/a> ;\u00A0\u00A0\u00A0\nschema:hasPart<\/a> <http:\/\/www.worldcat.org\/oclc\/1123191840<\/a>> ; # Domain adaptation and representation transfer and medical image learning with less labels and imperfect data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings<\/span>\n\u00A0\u00A0\u00A0\nschema:name<\/a> \"Lecture notes in computer science ;<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Series\/lncs_sublibrary<\/a>> # LNCS sublibrary.<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:PublicationSeries<\/a> ;\u00A0\u00A0\u00A0\nschema:hasPart<\/a> <http:\/\/www.worldcat.org\/oclc\/1123191840<\/a>> ; # Domain adaptation and representation transfer and medical image learning with less labels and imperfect data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings<\/span>\n\u00A0\u00A0\u00A0\nschema:name<\/a> \"LNCS sublibrary.<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Series\/lncs_sublibrary_sl_6_image_processing_computer_vision_pattern_recognition_and_graphics<\/a>> # LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:PublicationSeries<\/a> ;\u00A0\u00A0\u00A0\nschema:hasPart<\/a> <http:\/\/www.worldcat.org\/oclc\/1123191840<\/a>> ; # Domain adaptation and representation transfer and medical image learning with less labels and imperfect data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings<\/span>\n\u00A0\u00A0\u00A0\nschema:name<\/a> \"LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/9582790603#Topic\/diagnostic_imaging_data_processing<\/a>> # Diagnostic imaging--Data processing<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Diagnostic imaging--Data processing<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/id.loc.gov\/vocabulary\/countries\/sz<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:Place<\/a> ;\u00A0\u00A0\u00A0\ndcterms:identifier<\/a> \"sz<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/worldcat.org\/isbn\/9783030333911<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:ProductModel<\/a> ;\u00A0\u00A0\u00A0\nschema:isbn<\/a> \"3030333914<\/span>\" ;\u00A0\u00A0\u00A0\nschema:isbn<\/a> \"9783030333911<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/www.worldcat.org\/title\/-\/oclc\/1123191840<\/a>>\u00A0\u00A0\u00A0\u00A0a \ngenont:InformationResource<\/a>, genont:ContentTypeGenericResource<\/a> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/www.worldcat.org\/oclc\/1123191840<\/a>> ; # Domain adaptation and representation transfer and medical image learning with less labels and imperfect data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings<\/span>\n\u00A0\u00A0\u00A0\nschema:dateModified<\/a> \"2020-01-20<\/span>\" ;\u00A0\u00A0\u00A0\nvoid:inDataset<\/a> <http:\/\/purl.oclc.org\/dataset\/WorldCat<\/a>> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n\n

Content-negotiable representations<\/p>\n