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Showing 1 - 5 of
5 matches in All Departments
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Machine Learning in Medical Imaging - 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings (Paperback, 1st ed. 2018)
Yinghuan Shi, Heung-Il Suk, Mingxia Liu
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R1,579
Discovery Miles 15 790
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Ships in 10 - 15 working days
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This book constitutes the proceedings of the 9th International
Workshop on Machine Learning in Medical Imaging, MLMI 2018, held in
conjunction with MICCAI 2018 in Granada, Spain, in September
2018.The 45 papers presented in this volume were carefully reviewed
and selected from 82 submissions. They focus on major trends and
challenges in the area of machine learning in medical imaging and
aim to identify new cutting-edge techniques and their use in
medical imaging.
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Big Data - 9th CCF Conference, BigData 2021, Guangzhou, China, January 8-10, 2022, Revised Selected Papers (Paperback, 1st ed. 2022)
Xiangke Liao, Wei Zhao, Enhong Chen, Nong Xiao, Li Wang, …
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R2,437
Discovery Miles 24 370
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Ships in 10 - 15 working days
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This book constitutes the proceedings of the 9th CCF Conference on
Big Data, BigData 2021, held in Guangzhou, China, in January 2022.
Due to the COVID-19 pandemic BigData 2021 was postponed to 2022.
The 21 full papers presented in this volume were carefully reviewed
and selected from 66 submissions. They present recent research on
theoretical and technical aspects on big data, as well as on
digital economy demands in big data applications.
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Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings (Paperback, 1st ed. 2017)
Qian Wang, Yinghuan Shi, Heung-Il Suk, Kenji Suzuki
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R2,688
Discovery Miles 26 880
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 8th
International Workshop on Machine Learning in Medical Imaging, MLMI
2017, held in conjunction with MICCAI 2017, in Quebec City, QC,
Canada, in September 2017. The 44 full papers presented in this
volume were carefully reviewed and selected from 63 submissions.
The main aim of this workshop is to help advance scientific
research within the broad field of machine learning in medical
imaging. The workshop focuses on major trends and challenges in
this area, and presents works aimed to identify new cutting-edge
techniques and their use in medical imaging.
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Machine Learning in Medical Imaging - 7th International Workshop, MLMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings (Paperback, 1st ed. 2016)
Li Wang, Ehsan Adeli, Qian Wang, Yinghuan Shi, Heung-Il Suk
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R2,488
Discovery Miles 24 880
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 7th
International Workshop on Machine Learning in Medical Imaging, MLMI
2016, held in conjunction with MICCAI 2016, in Athens, Greece, in
October 2016. The 38 full papers presented in this volume were
carefully reviewed and selected from 60 submissions. The main aim
of this workshop is to help advance scientific research within the
broad field of machine learning in medical imaging. The workshop
focuses on major trends and challenges in this area, and presents
works aimed to identify new cutting-edge techniques and their use
in medical imaging.
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Machine Learning in Medical Imaging - 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings (Paperback, 1st ed. 2015)
Luping Zhou, Li Wang, Qian Wang, Yinghuan Shi
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R2,535
Discovery Miles 25 350
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Ships in 10 - 15 working days
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This book constitutes the proceedings of the 6th International
Workshop on Machine Learning in Medical Imaging, MLMI 2015, held in
conjunction with MICCAI 2015, in Munich in October 2015. The 40
full papers presented in this volume were carefully reviewed and
selected from 69 submissions. The workshop focuses on major trends
and challenges in the area of machine learning in medical imaging
and present works aimed to identify new cutting-edge techniques and
their use in medical imaging.
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