Deep Generative Models, and Data Augmentation, Labelling, and Imperfections (Record no. 186324)

MARC details
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001 - CONTROL NUMBER
control field 978-3-030-88210-5
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control field DE-He213
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control field 20240423130223.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030882105
-- 978-3-030-88210-5
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-030-88210-5
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA1501-1820
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA1634
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYT
Source bicssc
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Subject category code COM016000
Source bisacsh
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Subject category code UYT
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006
Edition number 23
245 10 - TITLE STATEMENT
Title Deep Generative Models, and Data Augmentation, Labelling, and Imperfections
Medium [electronic resource] :
Remainder of title First Workshop, DGM4MICCAI 2021, and First Workshop, DALI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /
Statement of responsibility, etc edited by Sandy Engelhardt, Ilkay Oksuz, Dajiang Zhu, Yixuan Yuan, Anirban Mukhopadhyay, Nicholas Heller, Sharon Xiaolei Huang, Hien Nguyen, Raphael Sznitman, Yuan Xue.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2021.
264 #1 -
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-- Springer International Publishing :
-- Imprint: Springer,
-- 2021.
300 ## - PHYSICAL DESCRIPTION
Extent XV, 278 p. 104 illus., 82 illus. in color.
Other physical details online resource.
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490 1# - SERIES STATEMENT
Series statement Image Processing, Computer Vision, Pattern Recognition, and Graphics,
International Standard Serial Number 3004-9954 ;
Volume number/sequential designation 13003
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note DGM4MICCAI 2021 - Image-to-Image Translation, Synthesis -- Frequency-Supervised MRI-to-CT Image Synthesis -- Ultrasound Variational Style Transfer to Generate Images Beyond the Observed Domain -- 3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images -- Bridging the gap between paired and unpaired medical image translation -- Conditional generation of medical images via disentangled adversarial inference. -CT-SGAN: Computed Tomography Synthesis GAN -- Hierarchical Probabilistic Ultrasound Image Inpainting via Variational Inference -- CaCL: class-aware codebook learning for weakly supervised segmentation on diffuse image patterns -- BrainNetGAN: Data augmentation of brain connectivity using generative adversarial network for dementia classification -- Evaluating GANs in medical imaging -- DGM4MICCAI 2021 - AdaptOR challenge -- Improved Heatmap-based Landmark Detection -- Cross-domain Landmarks Detection in Mitral Regurgitation -- DALI2021 -- Scalable Semi-supervised Landmark Localization for X-ray Images using Few-shot Deep Adaptive Graph -- Semi-supervised Surgical Tool Detection Based on Highly Confident Pseudo Labeling and Strong Augmentation Driven Consistency -- One-shot Learning for Landmarks Detection -- Compound Figure Separation of Biomedical Images with Side Loss -- Data Augmentation with Variational Autoencoders and Manifold Sampling -- Medical image segmentation with imperfect 3D bounding boxes -- Automated Iterative Label Transfer Improves Segmentation of Noisy Cells in Adaptive Optics Retinal Images -- How Few Annotations are Needed for Segmentation using a Multi-planar U-Net? -- FS-Net: A New Paradigm of Data Expansion for Medical Image Segmentation -- An Efficient Data Strategy for the Detection of Brain Aneurysms from MRA with Deep Learning -- Evaluation of Active Learning Techniques on Medical Image Classification with Unbalanced Data Distributions -- Zero-Shot Domain Adaptation in CT Segmentation by Filtered Back Projection Augmentation -- Label Noise in Segmentation Networks : Mitigation Must Deal with Bias -- DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization -- MetaHistoSeg: A Python Framework for Meta Learning in Histopathology Image Segmentation.
520 ## - SUMMARY, ETC.
Summary, etc This book constitutes the refereed proceedings of the First MICCAI Workshop on Deep Generative Models, DG4MICCAI 2021, and the First MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2021, held in conjunction with MICCAI 2021, in October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic. DG4MICCAI 2021 accepted 12 papers from the 17 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community. For DALI 2021, 15 papers from 32 submissions were accepted for publication. They focus on rigorousstudy of medical data related to machine learning systems. .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Image processing
General subdivision Digital techniques.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer vision.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Bioinformatics.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Imaging, Vision, Pattern Recognition and Graphics.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computational and Systems Biology.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Engelhardt, Sandy.
Relator term editor.
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Personal name Oksuz, Ilkay.
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Zhu, Dajiang.
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Yuan, Yixuan.
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Personal name Mukhopadhyay, Anirban.
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Personal name Heller, Nicholas.
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Personal name Huang, Sharon Xiaolei.
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Personal name Nguyen, Hien.
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Personal name Sznitman, Raphael.
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Xue, Yuan.
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-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030882099
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030882112
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Image Processing, Computer Vision, Pattern Recognition, and Graphics,
-- 3004-9954 ;
Volume number/sequential designation 13003
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-030-88210-5">https://doi.org/10.1007/978-3-030-88210-5</a>
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Koha item type eBooks-CSE-Springer

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