語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Distributed, collaborative, and fede...
~
Albarqouni, Shadi.
FindBook
Google Book
Amazon
博客來
Distributed, collaborative, and federated learning, and affordable AI and healthcare for resource diverse global health = third MICCAI Workshop, DeCaF 2022 and second MICCAI Workshop, FAIR 2022, held in conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022 : proceedings /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Distributed, collaborative, and federated learning, and affordable AI and healthcare for resource diverse global health/ edited by Shadi Albarqouni ... [et al.].
其他題名:
third MICCAI Workshop, DeCaF 2022 and second MICCAI Workshop, FAIR 2022, held in conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022 : proceedings /
其他題名:
DeCaF 2022
其他作者:
Albarqouni, Shadi.
出版者:
Cham :Springer Nature Switzerland : : 2022.,
面頁冊數:
xv, 204 p. :ill. (chiefly color), digital ;24 cm.
內容註:
Distributed, Collaborative, and Federated Learning -- Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation -- FedAP: Adaptive Personalization in Federated Learning for Non-IID Data Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes? -- Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes? -- Can collaborative learning be private, robust and scalable? -- Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-Modal Brain Tumor Segmentation -- Joint Multi Organ and Tumor Segmentation from Partial Labels using Federated Learning -- Fuh, Kensaku Mori, Weichung Wang, Holger R Roth GAN Latent Space Manipulation and Aggregation for Federated Learning in Medical Imaging -- A Specificity-Preserving Generative Model for Federated MRI Translation -- Content-Aware Differential Privacy with Conditional Invertible Neural Networks -- DeMed: A Novel and Efficient Decentralized Learning Framework for Medical Images Classification on Blockchain -- Cluster Based Secure Multi-Party Computation in Federated Learning for Histopathology Images -- Towards More Efficient Data Valuation in Healthcare Federated Learning using Ensembling -- Towards Real-World Federated Learning in Medical Image Analysis Using Kaapana -- Towards Sparsified Federated Neuroimaging Models via Weight Pruning -- Affordable AI and Healthcare -- Enhancing Portable OCT Image Quality via GANs for AI-Based Eye Disease Detection -- Deep Learning-based Segmentation of Pleural Effusion From Ultrasound Using Coordinate Convolutions -- Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks -- LRH-Net: A Multi-Level Knowledge Distillation Approach for Low-Resource Heart Network.
Contained By:
Springer Nature eBook
標題:
Diagnostic imaging - Congresses. - Data processing -
電子資源:
https://doi.org/10.1007/978-3-031-18523-6
ISBN:
9783031185236
Distributed, collaborative, and federated learning, and affordable AI and healthcare for resource diverse global health = third MICCAI Workshop, DeCaF 2022 and second MICCAI Workshop, FAIR 2022, held in conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022 : proceedings /
Distributed, collaborative, and federated learning, and affordable AI and healthcare for resource diverse global health
third MICCAI Workshop, DeCaF 2022 and second MICCAI Workshop, FAIR 2022, held in conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022 : proceedings /[electronic resource] :DeCaF 2022edited by Shadi Albarqouni ... [et al.]. - Cham :Springer Nature Switzerland :2022. - xv, 204 p. :ill. (chiefly color), digital ;24 cm. - Lecture notes in computer science,135730302-9743 ;. - Lecture notes in computer science ;13573..
Distributed, Collaborative, and Federated Learning -- Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation -- FedAP: Adaptive Personalization in Federated Learning for Non-IID Data Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes? -- Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes? -- Can collaborative learning be private, robust and scalable? -- Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-Modal Brain Tumor Segmentation -- Joint Multi Organ and Tumor Segmentation from Partial Labels using Federated Learning -- Fuh, Kensaku Mori, Weichung Wang, Holger R Roth GAN Latent Space Manipulation and Aggregation for Federated Learning in Medical Imaging -- A Specificity-Preserving Generative Model for Federated MRI Translation -- Content-Aware Differential Privacy with Conditional Invertible Neural Networks -- DeMed: A Novel and Efficient Decentralized Learning Framework for Medical Images Classification on Blockchain -- Cluster Based Secure Multi-Party Computation in Federated Learning for Histopathology Images -- Towards More Efficient Data Valuation in Healthcare Federated Learning using Ensembling -- Towards Real-World Federated Learning in Medical Image Analysis Using Kaapana -- Towards Sparsified Federated Neuroimaging Models via Weight Pruning -- Affordable AI and Healthcare -- Enhancing Portable OCT Image Quality via GANs for AI-Based Eye Disease Detection -- Deep Learning-based Segmentation of Pleural Effusion From Ultrasound Using Coordinate Convolutions -- Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks -- LRH-Net: A Multi-Level Knowledge Distillation Approach for Low-Resource Heart Network.
This book constitutes the refereed proceedings of the Third MICCAI Workshop on Distributed, Collaborative, and Federated Learning, DeCaF 2022, and the Second MICCAI Workshop on Affordable AI and Healthcare, FAIR 2022, held in conjunction with MICCAI 2022, in Singapore in September 2022. FAIR 2022 was held as a hybrid event. DeCaF 2022 accepted 14 papers from the 18 submissions received. The workshop aims at creating a scientific discussion focusing on the comparison, evaluation, and discussion of methodological advancement and practical ideas about machine learning applied to problems where data cannot be stored in centralized databases or where information privacy is a priority. For FAIR 2022, 4 papers from 9 submissions were accepted for publication. The topics of the accepted submissions focus on deep ultrasound segmentation, portable OCT image quality enhancement, self-attention deep networks and knowledge distillation in low-regime setting.
ISBN: 9783031185236
Standard No.: 10.1007/978-3-031-18523-6doiSubjects--Topical Terms:
893542
Diagnostic imaging
--Data processing--Congresses.
LC Class. No.: TA1634 / .D57 2022
Dewey Class. No.: 616.0757
Distributed, collaborative, and federated learning, and affordable AI and healthcare for resource diverse global health = third MICCAI Workshop, DeCaF 2022 and second MICCAI Workshop, FAIR 2022, held in conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022 : proceedings /
LDR
:04185nmm a2200373 a 4500
001
2304737
003
DE-He213
005
20221008115510.0
006
m d
007
cr nn 008maaau
008
230409s2022 sz s 0 eng d
020
$a
9783031185236
$q
(electronic bk.)
020
$a
9783031185229
$q
(paper)
024
7
$a
10.1007/978-3-031-18523-6
$2
doi
035
$a
978-3-031-18523-6
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TA1634
$b
.D57 2022
072
7
$a
UYQV
$2
bicssc
072
7
$a
COM012000
$2
bisacsh
072
7
$a
UYQV
$2
thema
082
0 4
$a
616.0757
$2
23
090
$a
TA1634
$b
.D614 2022
245
0 0
$a
Distributed, collaborative, and federated learning, and affordable AI and healthcare for resource diverse global health
$h
[electronic resource] :
$b
third MICCAI Workshop, DeCaF 2022 and second MICCAI Workshop, FAIR 2022, held in conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022 : proceedings /
$c
edited by Shadi Albarqouni ... [et al.].
246
3
$a
DeCaF 2022
246
3
$a
FAIR 2022
246
3
$a
MICCAI 2022
260
$a
Cham :
$b
Springer Nature Switzerland :
$b
Imprint: Springer,
$c
2022.
300
$a
xv, 204 p. :
$b
ill. (chiefly color), digital ;
$c
24 cm.
490
1
$a
Lecture notes in computer science,
$x
0302-9743 ;
$v
13573
505
0
$a
Distributed, Collaborative, and Federated Learning -- Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation -- FedAP: Adaptive Personalization in Federated Learning for Non-IID Data Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes? -- Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes? -- Can collaborative learning be private, robust and scalable? -- Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-Modal Brain Tumor Segmentation -- Joint Multi Organ and Tumor Segmentation from Partial Labels using Federated Learning -- Fuh, Kensaku Mori, Weichung Wang, Holger R Roth GAN Latent Space Manipulation and Aggregation for Federated Learning in Medical Imaging -- A Specificity-Preserving Generative Model for Federated MRI Translation -- Content-Aware Differential Privacy with Conditional Invertible Neural Networks -- DeMed: A Novel and Efficient Decentralized Learning Framework for Medical Images Classification on Blockchain -- Cluster Based Secure Multi-Party Computation in Federated Learning for Histopathology Images -- Towards More Efficient Data Valuation in Healthcare Federated Learning using Ensembling -- Towards Real-World Federated Learning in Medical Image Analysis Using Kaapana -- Towards Sparsified Federated Neuroimaging Models via Weight Pruning -- Affordable AI and Healthcare -- Enhancing Portable OCT Image Quality via GANs for AI-Based Eye Disease Detection -- Deep Learning-based Segmentation of Pleural Effusion From Ultrasound Using Coordinate Convolutions -- Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks -- LRH-Net: A Multi-Level Knowledge Distillation Approach for Low-Resource Heart Network.
520
$a
This book constitutes the refereed proceedings of the Third MICCAI Workshop on Distributed, Collaborative, and Federated Learning, DeCaF 2022, and the Second MICCAI Workshop on Affordable AI and Healthcare, FAIR 2022, held in conjunction with MICCAI 2022, in Singapore in September 2022. FAIR 2022 was held as a hybrid event. DeCaF 2022 accepted 14 papers from the 18 submissions received. The workshop aims at creating a scientific discussion focusing on the comparison, evaluation, and discussion of methodological advancement and practical ideas about machine learning applied to problems where data cannot be stored in centralized databases or where information privacy is a priority. For FAIR 2022, 4 papers from 9 submissions were accepted for publication. The topics of the accepted submissions focus on deep ultrasound segmentation, portable OCT image quality enhancement, self-attention deep networks and knowledge distillation in low-regime setting.
650
0
$a
Diagnostic imaging
$x
Data processing
$v
Congresses.
$3
893542
650
0
$a
Artificial intelligence
$x
Medical applications
$x
Congresses.
$3
660945
650
0
$a
Machine learning
$x
Congresses.
$3
576368
650
1 4
$a
Computer Vision.
$3
3538524
650
2 4
$a
Artificial Intelligence.
$3
769149
650
2 4
$a
Computing Milieux.
$3
893243
650
2 4
$a
Computer and Information Systems Applications.
$3
3538505
700
1
$a
Albarqouni, Shadi.
$3
3503828
710
2
$a
SpringerLink (Online service)
$3
836513
711
2
$a
DeCaf (Workshop)
$n
(3rd :
$d
2022 :
$c
Singapore)
$3
3607193
711
2
$a
FAIR (Workshop)
$n
(2nd :
$d
2022 :
$c
Singapore)
$3
3607194
711
2
$a
International Conference on Medical Image Computing and Computer-Assisted Intervention
$n
(25th :
$d
2022 :
$c
Singapore)
$3
3605691
773
0
$t
Springer Nature eBook
830
0
$a
Lecture notes in computer science ;
$v
13573.
$3
3607192
856
4 0
$u
https://doi.org/10.1007/978-3-031-18523-6
950
$a
Computer Science (SpringerNature-11645)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9446286
電子資源
11.線上閱覽_V
電子書
EB TA1634 .D57 2022
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入