Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Sui, Xiuchao"'
Autor:
Sui, Xiuchao, Li, Shaohua, Geng, Xue, Wu, Yan, Xu, Xinxing, Liu, Yong, Goh, Rick, Zhu, Hongyuan
Optical flow estimation aims to find the 2D motion field by identifying corresponding pixels between two images. Despite the tremendous progress of deep learning-based optical flow methods, it remains a challenge to accurately estimate large displace
Externí odkaz:
http://arxiv.org/abs/2203.16896
Autor:
Li, Shaohua, Sui, Xiuchao, Fu, Jie, Fu, Huazhu, Luo, Xiangde, Feng, Yangqin, Xu, Xinxing, Liu, Yong, Ting, Daniel, Goh, Rick Siow Mong
Deep neural networks (DNNs) trained on one set of medical images often experience severe performance drop on unseen test images, due to various domain discrepancy between the training images (source domain) and the test images (target domain), which
Externí odkaz:
http://arxiv.org/abs/2107.04805
Medical image segmentation is important for computer-aided diagnosis. Good segmentation demands the model to see the big picture and fine details simultaneously, i.e., to learn image features that incorporate large context while keep high spatial res
Externí odkaz:
http://arxiv.org/abs/2105.09511
Convolutional Neural Networks (CNNs) are known to be brittle under various image transformations, including rotations, scalings, and changes of lighting conditions. We observe that the features of a transformed image are drastically different from th
Externí odkaz:
http://arxiv.org/abs/2004.05554
Robotic drawing has become increasingly popular as an entertainment and interactive tool. In this paper we present RoboCoDraw, a real-time collaborative robot-based drawing system that draws stylized human face sketches interactively in front of huma
Externí odkaz:
http://arxiv.org/abs/1912.05099
Autor:
Li, Shaohua, Liu, Yong, Sui, Xiuchao, Chen, Cheng, Tjio, Gabriel, Ting, Daniel Shu Wei, Goh, Rick Siow Mong
Deep learning for medical image classification faces three major challenges: 1) the number of annotated medical images for training are usually small; 2) regions of interest (ROIs) are relatively small with unclear boundaries in the whole medical ima
Externí odkaz:
http://arxiv.org/abs/1907.02413
Akademický článek
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Akademický článek
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Publikováno v:
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI); 2015, p470-473, 4p
