Shulph Ink
Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health
Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health
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- More about Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health
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 Singapore in September 2022, accepted 14 papers from 18 submissions and 4 papers from 9 submissions, respectively, focusing on machine learning applied to problems where data cannot be stored in centralized databases or where information privacy is a priority.
Format: Paperback / softback
Length: 204 pages
Publication date: 09 October 2022
Publisher: Springer International Publishing AG
The Third MICCAI Workshop on Distributed, Collaborative, and Federated Learning (DeCaF 2022) and the Second MICCAI Workshop on Affordable AI and Healthcare (FAIR 2022) were held in conjunction with MICCAI 2022 in Singapore in September 2022. DeCaF 2022 received 14 papers out of 18 submissions, while FAIR 2022 accepted 4 papers from 9 submissions. The workshops aimed to foster a scientific discussion on the comparison, evaluation, and exploration of methodological advancements and practical ideas in machine learning applied to problems where data cannot be stored in centralized databases or where information privacy is a concern.
The accepted submissions for FAIR 2022 covered diverse topics such as deep ultrasound segmentation, portable OCT image quality enhancement, self-attention deep networks, and knowledge distillation in low-regime settings. These submissions highlight the ongoing efforts in developing innovative solutions for healthcare and AI applications.
The Third MICCAI Workshop on Distributed, Collaborative, and Federated Learning (DeCaF 2022) provided a platform for researchers to exchange ideas and discuss emerging trends in distributed, collaborative, and federated learning. The workshop aimed to bring together experts from various fields to explore the challenges and opportunities in these areas, and to identify potential solutions for real-world problems.
Overall, the workshops held in conjunction with MICCAI 2022 showcased the latest advancements in machine learning and provided a valuable opportunity for researchers and practitioners to collaborate and advance the field.
Weight: 343g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031185229
Edition number: 1st ed. 2022
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