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Etat : As New. Unread book in perfect condition.

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Etat : As New. Unread book in perfect condition.

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Paperback. Etat : Brand New. 157 pages. 9.25x6.10x0.35 inches. In Stock.

Paperback. Etat : Brand New. 180 pages. 9.25x6.10x0.39 inches. In Stock.

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 4th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2022, held in conjunction with MICCAI 2022, in September 2022.DART 2022 accepted 13 papers from the 25 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.…

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023.The 16 full papers presented in this book were carefully reviewed and selected from 32 submissions. They discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.…

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Taschenbuch. Etat : Neu. Domain Adaptation and Representation Transfer | 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings | Lisa Koch (u. a.) | Taschenbuch | Lecture Notes in Computer Science | x | Englisch | 2023 | Springer | EAN 9783031458569 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Taschenbuch. Etat : Neu. Domain Adaptation and Representation Transfer | 4th MICCAI Workshop, DART 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings | Konstantinos Kamnitsas (u. a.) | Taschenbuch | Lecture Notes in Computer Science | x | Englisch | 2022 | Springer | EAN 9783031168512 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Etat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023. The 16 full papers presented in this book were carefully reviewed and selected from 32 submissions. They discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.…

Etat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book constitutes the refereed proceedings of the 4th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2022, held in conjunction with MICCAI 2022, in September 2022. DART 2022 accepted 13 papers from the 25 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.…

Etat : new. Questo è un articolo print on demand.

Etat : new. Questo è un articolo print on demand.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the 4th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2022, held in conjunction with MICCAI 2022, in September 2022.DART 2022 accepted 13 papers from the 25 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. 160 pp. Englisch.…

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023.The 16 full papers presented in this book were carefully reviewed and selected from 32 submissions. They discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. 180 pp. Englisch.…

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Etat : New. PRINT ON DEMAND.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023.&nbspThe 16 full papers presented in this book w.…

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 180 pp. Englisch.…

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification.- Benchmarking Transformers for Medical Image Classification.- Supervised domain adaptation using gradients transfer for improved medical image analysis.- Stain-AgLr: Stain Agnostic Learning for Computational Histopathology using Domain Consistency and Stain Regeneration Loss.- MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ Segmentation.- Unsupervised site adaptation by intra-site variability alignment.- Discriminative, Restorative, and Adversarial Learning: Stepwise Incremental Pretraining.- POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis.- Feather-Light Fourier Domain Adaptation in Magnetic Resonance Imaging.- Seamless Iterative Semi-Supervised Correction of Imperfect Labels in Microscopy Images.- Task-agnostic Continual Hippocampus Segmentation for Smooth Population Shifts.- Adaptive Optimization with Fewer Epochs Improves Across-Scanner Generalization of U-Net based Medical Image Segmentation.- CateNorm: Categorical Normalization for Robust Medical Image Segmentation.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 160 pp. Englisch.…