Zobrazeno 1 - 10
of 128
pro vyhledávání: '"Fu Jie Huang"'
Autor:
Zhu, Guangxu1 (AUTHOR), Jiao, Xuguang1 (AUTHOR), Zhou, Shengjie2 (AUTHOR), Zhu, Qingshun1 (AUTHOR), Yu, Lei3 (AUTHOR), Sun, Qihang4 (AUTHOR), Li, Bowen4 (AUTHOR), Fu, Hao1 (AUTHOR), Huang, Jie1 (AUTHOR), Lang, Wei1 (AUTHOR), Lang, Xiaomin1 (AUTHOR), Zhai, Shengyong1,5 (AUTHOR), Xiong, Jinqiu1 (AUTHOR), Fu, Yanan1 (AUTHOR), Liu, Chunxiao1 (AUTHOR), Qu, Jianjun1 (AUTHOR) 1538385217@qq.com
Publikováno v:
BMC Gastroenterology. 7/23/2024, Vol. 24 Issue 1, p1-14. 14p.
Autor:
Fu, De Sheng1 (AUTHOR), Huang, Jie2 (AUTHOR), Hazra, Dibyanarayan3 (AUTHOR), Dwivedi, Amit Kumar3 (AUTHOR), Gupta, Suneet Kumar4 (AUTHOR) suneet.banda@gmail.com, Shivahare, Basu Dev5 (AUTHOR), Garg, Deepak6 (AUTHOR)
Publikováno v:
PLoS ONE. 7/11/2024, Vol. 19 Issue 7, p1-37. 37p.
Publikováno v:
Predicting Structured Data; 2007, p191-197, 7p
Publikováno v:
ICDAR
The machine learning and pattern recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization problem is related to the difficulty of training probabilistic models over
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4b96deea250efe49b059da0ce4ea469
https://doi.org/10.1109/icdar.2007.4378728
https://doi.org/10.1109/icdar.2007.4378728
Publikováno v:
CVPR
We present an unsupervised method for learning a hierarchy of sparse feature detectors that are invariant to small shifts and distortions. The resulting feature extractor consists of multiple convolution filters, followed by a feature-pooling layer t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c88ad8103281a90fe1e67672d0dbe75
https://doi.org/10.1109/cvpr.2007.383157
https://doi.org/10.1109/cvpr.2007.383157
Publikováno v:
Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition; 2002, p396-401, 6p
Autor:
Fu Jie Huang, Tsuhan Chen
Publikováno v:
2001 IEEE Fourth Workshop on Multimedia Signal Processing (Cat. No.01TH8564); 2001, p613-618, 6p
Publikováno v:
Proceedings Fourth IEEE International Conference on Automatic Face & Gesture Recognition (Cat. No. PR00580); 2000, p245-250, 6p
Autor:
Yann LeCun, Fu Jie Huang
Publikováno v:
CVPR (1)
The detection and recognition of generic object categories with invariance to viewpoint, illumination, and clutter requires the combination of a feature extractor and a classifier. We show that architectures such as convolutional networks are good at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ac15fdd58f1cf99baee3d00f3cc43bf
https://doi.org/10.1109/cvpr.2006.164
https://doi.org/10.1109/cvpr.2006.164
Publikováno v:
CVPR (2)
We assess the applicability of several popular learning methods for the problem of recognizing generic visual categories with invariance to pose, lighting, and surrounding clutter. A large dataset comprising stereo image pairs of 50 uniform-colored t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1beaf591111553d2d4679e5b7f64658b
https://doi.org/10.1109/cvpr.2004.1315150
https://doi.org/10.1109/cvpr.2004.1315150