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  • Produktbild: Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
  • Produktbild: Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
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Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 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

57,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

14.11.2021

Abbildungen

XXV, 190 p. 78 illus., 67 illus. in color.

Herausgeber

Michal Rosen-Zvi + weitere

Verlag

Springer

Seitenzahl

190

Maße (L/B/H)

23,5/15,5/1,2 cm

Gewicht

335 g

Auflage

1st ed. 2021

Sprache

Englisch

ISBN

978-3-030-90873-7

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

14.11.2021

Abbildungen

XXV, 190 p. 78 illus., 67 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

190

Maße (L/B/H)

23,5/15,5/1,2 cm

Gewicht

335 g

Auflage

1st ed. 2021

Sprache

Englisch

ISBN

978-3-030-90873-7

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
  • Produktbild: Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
  • Intestine segmentation with small computational cost for diagnosis assistance of ileus and intestinal obstruction.- Generation of Patient-Specific, Ligamentoskeletal, Finite Element Meshes for Scoliosis Correction Planning.- Bayesian Graph Neural Networks For EEG-based Emotion Recognition.- ViTBIS: Vision Transformer for Biomedical Image Segmentation.- Attention-guided pancreatic duct segmentation from abdominal CT volumes.- Development of the Next Generation Hand-Held Doppler With Waveform Phasicity Predictive Capabilities Using Deep Learning.- Learning from mistakes: an error-driven mechanism to improve segmentation performance based on expert feedback.- TMJOAI: an artificial web-based intelligence tool for early diagnosis of the Temporomandibular Joint Osteoarthritis.- COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty.- Multi-task Federated Learning for Heterogeneous Pancreas Segmentation.- Federated Learning in the Cloud for Analysis of Medical Images- Experience with Open Source Frameworks.- On the Fairness of Swarm Learning in Skin Lesion Classification.- Lessons learned from the development and application of medical imaging-based AI technologies for combating COVID-19: why discuss, what next.- The Role of Pleura and Adipose in Lung Ultrasound AI.- DuCN: Dual-children Network for Medical Diagnosis and Similar Case Recommendation towards COVID-19.- Data imputation and reconstruction of distributed Parkinson's disease clinical assessments: A comparative evaluation of two aggregation algorithms.- Defending Medical Image Diagnostics against Privacy Attacks using Generative Methods: Application to Retinal Diagnostics.