Zobrazeno 1 - 10
of 81
pro vyhledávání: '"Ren, Shaoqing"'
Publikováno v:
In Journal of Alloys and Compounds 25 October 2024 1003
Autor:
Ren, Shaoqing, Lv, Ke, Li, Han, Xie, Jihao, Jin, Jiaying, Zhao, Mingjing, Li, Quan, Jiang, Yizhou, Zhang, Zhongye, Yan, Mi
Publikováno v:
In Journal of Magnetism and Magnetic Materials 15 September 2024 606
Autor:
Li, Han, Ren, Shaoqing, Xie, Jihao, Lv, Ke, Chen, Yanping, Zhao, Mingjing, Li, Quan, Zhang, Zhongye
Publikováno v:
In Journal of Magnetism and Magnetic Materials 15 September 2024 606
Autor:
Zhao, Dong, Liu, Fugang, Gao, Yu, Jiang, Pan, Liu, Limin, Zhao, Mingjing, Ren, Shaoqing, Pei, Wenli
Publikováno v:
In Journal of Magnetism and Magnetic Materials 1 December 2022 563
Autor:
Chen, Wang, Jin, Jiaying, Ren, Shaoqing, Peng, Baixing, Zhou, Liang, Wu, Chen, Liu, Guozheng, Yan, Mi
Publikováno v:
In Materials Characterization August 2022 190
Fully convolutional networks (FCNs) have been proven very successful for semantic segmentation, but the FCN outputs are unaware of object instances. In this paper, we develop FCNs that are capable of proposing instance-level segment candidates. In co
Externí odkaz:
http://arxiv.org/abs/1603.08678
Deep residual networks have emerged as a family of extremely deep architectures showing compelling accuracy and nice convergence behaviors. In this paper, we analyze the propagation formulations behind the residual building blocks, which suggest that
Externí odkaz:
http://arxiv.org/abs/1603.05027
Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. We explicitly reformulate the layers as learning residual function
Externí odkaz:
http://arxiv.org/abs/1512.03385
State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet and Fast R-CNN have reduced the running time of these detection networks, exposing region proposal computation as a
Externí odkaz:
http://arxiv.org/abs/1506.01497
Most object detectors contain two important components: a feature extractor and an object classifier. The feature extractor has rapidly evolved with significant research efforts leading to better deep convolutional architectures. The object classifie
Externí odkaz:
http://arxiv.org/abs/1504.06066