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  • Produktbild: Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health
  • Produktbild: Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health
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Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health Third MICCAI Workshop, DART 2021, and First MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings

Aus der Reihe Image Processing, Computer Vision, Pattern Recognition, and Graphics

64,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

24.09.2021

Abbildungen

XV, 264 p. 95 illus., 90 illus. in color.

Herausgeber

Konstantinos Kamnitsas + weitere

Verlag

Springer

Seitenzahl

264

Maße (L/B/H)

23,5/15,5/1,6 cm

Gewicht

429 g

Auflage

1st ed. 2021

Sprache

Englisch

ISBN

978-3-030-87721-7

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

24.09.2021

Abbildungen

XV, 264 p. 95 illus., 90 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

264

Maße (L/B/H)

23,5/15,5/1,6 cm

Gewicht

429 g

Auflage

1st ed. 2021

Sprache

Englisch

ISBN

978-3-030-87721-7

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health
  • Produktbild: Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health

  • Domain Adaptation and Representation Transfer.- A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis.- Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning.- FDA: Feature Decomposition and Aggregation for Robust Airway Segmentation.- Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation.- Self-Supervised Multimodal Generalized Zero Shot Learning For Gleason Grading.- Self-Supervised Learning of Inter-Label Geometric Relationships For Gleason Grade Segmentation.- Stop Throwing Away Discriminators! Re-using Adversaries for Test-Time Training.- Transductive image segmentation: Self-training and effect of uncertainty estimation.- Unsupervised Domain Adaptation with Semantic Consistency across Heterogeneous Modalities for MRI Prostate Lesion Segmentation.- Cohort Bias Adaptation in Federated Datasets for Lesion Segmentation.- Exploring Deep Registration Latent Spaces.- Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift.- Unsupervised Domain Adaption via Similarity-based Prototypes for Cross-Modality Segmentation.- A ordable AI and Healthcare.- Classification and Generation of Microscopy Images with Plasmodium Falciparum via Arti cial Neural Networks using Low Cost Settings.- Contrast and Resolution Improvement of POCUS Using Self-Consistent CycleGAN.- Low-Dose Dynamic CT Perfusion Denoising without Training Data.- Recurrent Brain Graph Mapper for Predicting Time-Dependent Brain Graph Evaluation Trajectory.- COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19Patient Cases from Point-of-care Ultrasound Imaging.- Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning.- Sickle Cell Disease Severity Prediction from Percoll Gradient Images using Graph Convolutional Networks.- Continual Domain Incremental Learning for Chest X-ray Classificationin Low-Resource Clinical Settings.- Deep learning based Automatic detection of adequately positioned mammograms.- Can non-specialists provide high quality Gold standard labels in challenging modalities.