Zobrazeno 1 - 10
of 20
pro vyhledávání: '"NANQING DONG"'
Publikováno v:
ACM Computing Surveys. 55:1-35
Recent years have witnessed the widespread popularity of Internet of things (IoT). By providing sufficient data for model training and inference, IoT has promoted the development of artificial intelligence (AI) to a great extent. Under this backgroun
Publikováno v:
The Journal of Portfolio Management. 49:175-187
Data government has played an instrumental role in securing the privacy-critical infrastructure in the medical domain and has led to an increased need of federated learning (FL). While decentralization can limit the effectiveness of standard supervis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88598993bbfb1b47a4aec87fd9573f3a
https://ora.ox.ac.uk/objects/uuid:bfc576bc-c7c9-4a9b-933a-410b0805c39d
https://ora.ox.ac.uk/objects/uuid:bfc576bc-c7c9-4a9b-933a-410b0805c39d
Autor:
Xingying Chen, Zidong Wang, Haochen Hua, Nanqing Dong, Zhaoming Qin, Maojiao Ye, Yuchao Qin, Junwei Cao
Publikováno v:
IEEE Transactions on Sustainable Energy. 13:315-327
The development of energy Internet (EI) makes it possible to achieve better utilization of distributed renewable energy sources with the power sharing functionality introduced by energy routers (ERs). In this paper, a bottom-up EI architecture is des
Ubiquitous accumulation of large volumes of data, and in- creased availability of annotated medical data in particular, has made it possible to show the many and varied benefits of deep learning to the semantic segmentation of medical im- ages. Never
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d2a1d2fca47b92a23b46ec650b899cf
https://ora.ox.ac.uk/objects/uuid:ec5d1512-97d2-40ae-aff9-b48bfaa1bbef
https://ora.ox.ac.uk/objects/uuid:ec5d1512-97d2-40ae-aff9-b48bfaa1bbef
Due to the high human cost of annotation, it is non-trivial to curate a large-scale medical dataset that is fully labeled for all classes of interest. Instead, it would be convenient to collect multiple small partially labeled datasets from different
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::931a817c7fee7aeeaaa957432e2bfee8
http://arxiv.org/abs/2204.08954
http://arxiv.org/abs/2204.08954
Entanglement is a physical phenomenon, which has fueled recent successes of quantum algorithms. Although quantum neural networks (QNNs) have shown promising results in solving simple machine learning tasks recently, for the time being, the effect of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee6477efd948a51610444f54f8f3bba5
https://hdl.handle.net/10037/27740
https://hdl.handle.net/10037/27740
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031164514
Using decentralized data for federated training is one promising emerging research direction for alleviating data scarcity in the medical domain. However, in contrast to large-scale fully labeled data commonly seen in general object recognition tasks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6903d4ee99dc80b3ead0b0c0a4e33e62
Autor:
Nanqing Dong, Irina Voiculescu
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030871987
MICCAI (3)
MICCAI (3)
A label-efficient paradigm in computer vision is based on self-supervised contrastive pre-training on unlabeled data followed by fine-tuning with a small number of labels. Making practical use of a federated computing environment in the clinical doma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a25f06d36113424aa32ab5a00a28a4a7
https://ora.ox.ac.uk/objects/uuid:16cdf7ad-e966-4a90-a4d0-57dd52fe79e9
https://ora.ox.ac.uk/objects/uuid:16cdf7ad-e966-4a90-a4d0-57dd52fe79e9
Publikováno v:
Machine Learning and Knowledge Discovery in Databases. Research Track ISBN: 9783030865221
ECML/PKDD (3)
ECML/PKDD (3)
Self-supervised representation learning has achieved promising results for downstream visual tasks in natural images. However, its use in the medical domain, where there is an underlying anatomical structural similarity, remains underexplored. To add
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5416f407a7a228ae71d80a95d41eac9b
https://doi.org/10.1007/978-3-030-86523-8_47
https://doi.org/10.1007/978-3-030-86523-8_47