Zobrazeno 1 - 7
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pro vyhledávání: '"Zhengsu Chen"'
Using a large number of parameters , deep neural networks have achieved remarkable performance on computer vison and natural language processing tasks. However the networks usually suffer from overfitting by using too much parameters. Dropout is a wi
Externí odkaz:
http://arxiv.org/abs/1810.09849
Publikováno v:
International Journal of Computer Vision. 130:820-835
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fd0edafcc51530016ab2bf6d0c91a2c
https://doi.org/10.1007/s11263-021-01566-5
https://doi.org/10.1007/s11263-021-01566-5
The past year has witnessed the rapid development of applying the Transformer module to vision problems. While some researchers have demonstrated that Transformer-based models enjoy a favorable ability of fitting data, there are still growing number
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cfc3d85025c51f67ab191efc109abbe9
http://arxiv.org/abs/2104.12533
http://arxiv.org/abs/2104.12533
Autor:
LINGXI XIE, XIN CHEN, KAIFENG BI, LONGHUI WEI, YUHUI XU, LANFEI WANG, ZHENGSU CHEN, AN XIAO, JIANLONG CHANG, XIAOPENG ZHANG, QI TIAN
Publikováno v:
ACM Computing Surveys; Dec2022, Vol. 54 Issue 9, p1-37, 37p
Publikováno v:
IJCAI
Convolutional neural networks (CNNs) have achieved remarkable success in image recognition. Although the internal patterns of the input images are effectively learned by the CNNs, these patterns only constitute a small proportion of useful patterns c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7128df5a512504bf82b887a70eaad890
https://doi.org/10.24963/ijcai.2020/73
https://doi.org/10.24963/ijcai.2020/73
Publikováno v:
CVPR
Automatic designing computationally efficient neural networks has received much attention in recent years. Existing approaches either utilize network pruning or leverage the network architecture search methods. This paper presents a new framework nam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11415bfadc3dc30cd5b5857ac7483703
http://arxiv.org/abs/2004.02767
http://arxiv.org/abs/2004.02767
Although deep learning models like CNNs have achieved great success in medical image analysis, the small size of medical datasets remains a major bottleneck in this area. To address this problem, researchers have started looking for external informat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca7693cb3851827ed254a9f1e56d5082