搜索筛选:
搜索耗时2.3675秒,为你在为你在102,285,761篇论文里面共找到 27 篇相符的论文内容
类      型:
[期刊论文] 作者:Guo Da, 来源:中国社会科学:英文版 年份:1985
This huge volume of approximately 7.5 million words synthesizes the results ofancient and modern scholarship, while avoiding these predecessors’ shortcomings,...
[期刊论文] 作者:Li Chonghuai Guo Da, 来源:中国社会科学:英文版 年份:1985
In his article 'On the Demonetization of Gold: A Reply to Professor Li Chong-huai' which appeared in Social Sciences in China (English edition,1984,No.2...
[期刊论文] 作者:CAI Kang-xu,GUO Da, 来源:煤炭学报(英文版) 年份:2006
The main factors that affect infrared surveying in roadway include that property of rock, electromechanical equipments running, environmental temperature, hydrogeology and support material etc. This paper sums up the expression features of ......
[期刊论文] 作者:GUO Da,ZHENG Qingfang,PENG Xia, 来源:中兴通讯技术:英文版 年份:2019
This paper proposes a universal framework,termed as Multi-Task Hybrid Convolutional Neural Network(MHCNN),for joint face detection,facial landmark detection,fac...
[期刊论文] 作者:XU Xiaoping,LI Zhongqin,GUO Da, 来源:中国反应性高分子:英文版 年份:2007
[期刊论文] 作者:HU Zhao-ling,DU Pei-jun,GUO Da, 来源:中国矿业大学学报:英文版 年份:2006
基于 Xuzhou 城市的卫星遥感 TM/ETM 图象,关于从 1994 ~ 2000 的城市的陆地使用的基本数据与一种总线标准软件,和陆地使用的动态变换矩阵的神经网络分类模块被获得因此被计算。...
[期刊论文] 作者:HU Zhao-ling,DU Pei-jun,GUO Da, 来源:中国矿业大学学报:英文版 年份:2007
基于 Xuzhou 城市的卫星遥感 TM/ETM+ 图象,在 1987, 1994 和 2000 的城市的陆地使用形式被使用一个神经网络分类方法提取。扩大贡献率和每个行政区域的年度扩大紧张索引被计算...
[期刊论文] 作者:WEI Junhao,QIU Xiaoping,GUO Da, 来源:地质学报(英文版) 年份:2004
On the basis of detailed geological studies of the Wulong gold deposit, three metallogenic stages can be identified. With quartz fluid inclusions as an object o...
[期刊论文] 作者:HU Zhao-ling,DU Pei-jun,GUO Da, 来源:中国矿业大学学报(英文版) 年份:2004
Based on the satellite remote sensing TM/ETM images of Xuzhou city, basic data about land use of the city from 1994 to 2000 are obtained with the neural network...
[期刊论文] 作者:HU Zhao-ling,DU Pei-jun,GUO Da, 来源:中国矿业大学学报(英文版) 年份:2004
Based on satellite remote sensing TM/ETM+ images of Xuzhou city, land use forms of the city in 1987, 1994 and 2000 were extracted by using a neural network clas...
[期刊论文] 作者:Siyue Guo,Da Yan,Chenxi Gui, 来源:建筑模拟(英文版) 年份:2020
[期刊论文] 作者:DONG Zhi-hui,FU Wei-guo,GUO Da, 来源:中华医学杂志(英文版) 年份:2006
Rupture of isolated hypogastric artery aneurysm (HAA) is rarely encountered and is associated with a high mortality rate. Conventional surgery can not achieve...
[期刊论文] 作者:GUO Da,CHENG Gang,ZHANG Yong,S, 来源:中国通信:英文版 年份:2015
Most of data distribution mechanism in Opportunistic Networks is derived by Epidemic data distribution,and Epidemic data distribution means that when each node...
[期刊论文] 作者:GUO Da,ZHENG Qingfang,PENG Xiaojiang,LIU Ming, 来源:中兴通讯技术(英文版) 年份:2019
This paper proposes a universal framework, termed as Multi-Task Hybrid Convo-lutional Neural Network (MHCNN), for joint face detection, facial landmark detectio...
[期刊论文] 作者:GUO Da,ZHENG Qingfang,PENG Xiaojiang,LIU Ming,, 来源:ZTE Communications 年份:2019
This paper proposes a universal framework, termed as Multi-Task Hybrid Convolutional Neural Network(MHCNN), for joint face detection, facial landmark detection, facial quality, and facial attribute an...
[期刊论文] 作者:GUO Da ZHENG Qingfang PENG Xiaojiang LIU Ming, 来源:ZTE Communications 年份:2019
Abstract: This paper proposes a universal framework, termed as Multi?Task Hybrid Convolutional Neural Network (MHCNN), for joint face detection, facial landmark detection, facial quality, and facial a...
[期刊论文] 作者:GUO Da,CHENG Gang,ZHANG Yong,SONG Mei,Amanda Matthews,, 来源:中国通信 年份:2015
Most of data distribution mechanism in Opportunistic Networks is derived by Epidemic data distribution,and Epidemic data distribution means that when each node...
[期刊论文] 作者:CHENG Gang,ZHANG Yong,SONG Mei,GUO Da,Amanda Matthews,, 来源:中国通信 年份:2015
In the paper, we concentrate on the infl uence of heterogeneity on the performance of forwarding algorithms under opportunistic networks. Therefore, we first de...
[会议论文] 作者:Xiaozhi Guo,Da Qin,Yanhong Luo,Dongmei Li,Qingbo Meng, 来源:ICAM新能源材料中的物理国际研讨会 年份:2010
[期刊论文] 作者:Zhang Zhao,Zhang Yong,Teng Yinglei,Guo Da,Deng Haiqin, 来源:中国邮电高校学报(英文版) 年份:2019
Human activity recognition (HAR) for dense prediction is proven to be of good performance,but it relies on labeling every point in time series with the high cost.In addition,the performance of HAR model will show significant degradation whe......
相关搜索: