ICML 2004

ICML 2004 PDF Author: Russell Greiner
Publisher:
ISBN: 9781581138382
Category : Computer science
Languages : en
Pages : 942

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Book Description

ICML 2004

ICML 2004 PDF Author: Russell Greiner
Publisher:
ISBN: 9781581138382
Category : Computer science
Languages : en
Pages : 942

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Book Description


Machine Learning in Medical Imaging

Machine Learning in Medical Imaging PDF Author: Chunfeng Lian
Publisher: Springer Nature
ISBN: 303087589X
Category : Computers
Languages : en
Pages : 723

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Book Description
This book constitutes the proceedings of the 12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.* The 71 papers presented in this volume were carefully reviewed and selected from 92 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc. *The workshop was held virtually.

Machine Learning for Medical Image Reconstruction

Machine Learning for Medical Image Reconstruction PDF Author: Farah Deeba
Publisher: Springer Nature
ISBN: 3030615987
Category : Computers
Languages : en
Pages : 170

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Book Description
This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshop was held virtually. The 15 papers presented were carefully reviewed and selected from 18 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.

Machine Learning in Clinical Neuroimaging

Machine Learning in Clinical Neuroimaging PDF Author: Ahmed Abdulkadir
Publisher: Springer Nature
ISBN: 3030875865
Category : Computers
Languages : en
Pages : 185

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Book Description
This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The workshop was held virtually due to the COVID-19 pandemic. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections named: computational anatomy and brain networks and time series.

Machine Learning Proceedings 1991

Machine Learning Proceedings 1991 PDF Author: Lawrence A. Birnbaum
Publisher: Morgan Kaufmann
ISBN: 1483298175
Category : Computers
Languages : en
Pages : 682

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Book Description
Machine Learning

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures PDF Author: Hayit Greenspan
Publisher: Springer Nature
ISBN: 3030326896
Category : Computers
Languages : en
Pages : 202

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Book Description
This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8th International Workshop on Clinical Image-Based Procedures, CLIP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For UNSURE 2019, 8 papers from 15 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. CLIP 2019 accepted 11 papers from the 15 submissions received. The workshops provides a forum for work centred on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.

Machine Learning in Medical Imaging

Machine Learning in Medical Imaging PDF Author: Mingxia Liu
Publisher: Springer Nature
ISBN: 3030598616
Category : Computers
Languages : en
Pages : 702

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Book Description
This book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 68 papers presented in this volume were carefully reviewed and selected from 101 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.

Machine Learning Proceedings 1992

Machine Learning Proceedings 1992 PDF Author: Peter Edwards
Publisher: Morgan Kaufmann
ISBN: 1483298531
Category : Computers
Languages : en
Pages : 497

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Book Description
Machine Learning Proceedings 1992

Machine Learning

Machine Learning PDF Author:
Publisher:
ISBN: 9781558602007
Category :
Languages : en
Pages :

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Machine Learning for Medical Image Reconstruction

Machine Learning for Medical Image Reconstruction PDF Author: Nandinee Haq
Publisher: Springer
ISBN: 9783030885519
Category : Computers
Languages : en
Pages : 142

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Book Description
This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2021, held in conjunction with MICCAI 2021, in October 2021. The workshop was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic. The 13 papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.