|
Showing 1 - 3 of
3 matches in All Departments
|
Machine Learning in Medical Imaging - 13th International Workshop, MLMI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings (Paperback, 1st ed. 2022)
Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Zhiming Cui
|
R2,511
Discovery Miles 25 110
|
Ships in 10 - 15 working days
|
This book constitutes the proceedings of the 13th International
Workshop on Machine Learning in Medical Imaging, MLMI 2022, held in
conjunction with MICCAI 2022, in Singapore, in September 2022. The
48 full papers presented in this volume were carefully reviewed and
selected from 64 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 in Medical Imaging - 12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings (Paperback, 1st ed. 2021)
Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Pingkun Yan
|
R3,092
Discovery Miles 30 920
|
Ships in 10 - 15 working days
|
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 in Medical Imaging - 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings (Paperback, 1st ed. 2020)
Mingxia Liu, Pingkun Yan, Chunfeng Lian, Xiaohuan Cao
|
R3,086
Discovery Miles 30 860
|
Ships in 10 - 15 working days
|
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.
|
You may like...
Not available
|