咨询与建议

限定检索结果

文献类型

  • 1,394 篇 会议
  • 1,043 篇 期刊文献
  • 2 册 图书

馆藏范围

  • 2,439 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 1,528 篇 工学
    • 1,073 篇 计算机科学与技术...
    • 909 篇 软件工程
    • 344 篇 信息与通信工程
    • 172 篇 电气工程
    • 172 篇 控制科学与工程
    • 146 篇 电子科学与技术(可...
    • 144 篇 生物工程
    • 123 篇 机械工程
    • 103 篇 光学工程
    • 81 篇 生物医学工程(可授...
    • 79 篇 化学工程与技术
    • 56 篇 仪器科学与技术
    • 54 篇 动力工程及工程热...
    • 42 篇 材料科学与工程(可...
    • 38 篇 建筑学
    • 36 篇 土木工程
    • 35 篇 网络空间安全
    • 30 篇 交通运输工程
  • 938 篇 理学
    • 596 篇 数学
    • 243 篇 物理学
    • 174 篇 生物学
    • 160 篇 统计学(可授理学、...
    • 84 篇 化学
    • 74 篇 系统科学
  • 428 篇 管理学
    • 235 篇 图书情报与档案管...
    • 206 篇 管理科学与工程(可...
    • 74 篇 工商管理
  • 70 篇 医学
    • 55 篇 临床医学
    • 44 篇 基础医学(可授医学...
  • 46 篇 法学
    • 35 篇 社会学
  • 37 篇 农学
  • 23 篇 经济学
  • 15 篇 教育学
  • 9 篇 哲学
  • 7 篇 艺术学
  • 4 篇 军事学
  • 3 篇 文学

主题

  • 108 篇 feature extracti...
  • 95 篇 semantics
  • 67 篇 information proc...
  • 62 篇 training
  • 59 篇 laboratories
  • 51 篇 computers
  • 43 篇 face recognition
  • 43 篇 computational mo...
  • 42 篇 image segmentati...
  • 42 篇 visualization
  • 40 篇 data mining
  • 38 篇 optimization
  • 37 篇 machine learning
  • 36 篇 humans
  • 35 篇 accuracy
  • 33 篇 deep learning
  • 33 篇 robustness
  • 30 篇 support vector m...
  • 29 篇 predictive model...
  • 29 篇 decoding

机构

  • 436 篇 key laboratory o...
  • 212 篇 university of ch...
  • 83 篇 key laboratory o...
  • 83 篇 key laboratory o...
  • 63 篇 peng cheng labor...
  • 63 篇 college of compu...
  • 52 篇 college of mathe...
  • 48 篇 key laboratory o...
  • 45 篇 hunan provincial...
  • 45 篇 the key laborato...
  • 43 篇 key laboratory o...
  • 43 篇 college of infor...
  • 43 篇 graduate univers...
  • 42 篇 school of comput...
  • 40 篇 chinese academy ...
  • 38 篇 fujian provincia...
  • 37 篇 fujian key labor...
  • 35 篇 key laboratory o...
  • 32 篇 school of comput...
  • 31 篇 anhui university...

作者

  • 95 篇 zhongzhi shi
  • 93 篇 shi zhongzhi
  • 74 篇 xilin chen
  • 71 篇 shiguang shan
  • 62 篇 liu qun
  • 61 篇 huang qingming
  • 49 篇 li yingsong
  • 41 篇 huang zhixiang
  • 41 篇 xu qianqian
  • 40 篇 feng yang
  • 37 篇 he qing
  • 35 篇 yingsong li
  • 32 篇 wen gao
  • 31 篇 qing he
  • 29 篇 jiang kai
  • 29 篇 zhixiang huang
  • 28 篇 li hua
  • 28 篇 zhuang fuzhen
  • 27 篇 guo wenzhong
  • 26 篇 yang zhiyong

语言

  • 2,303 篇 英文
  • 85 篇 其他
  • 57 篇 中文
检索条件"机构=The Key Laboratory of Cognitive Computing and Intelligent Information Processing"
2439 条 记 录,以下是291-300 订阅
排序:
CASICT-DCU neural machine translation systems for WMT17  2
CASICT-DCU neural machine translation systems for WMT17
收藏 引用
2nd Conference on Machine Translation, WMT 2017
作者: Zhang, Jinchao Porkaew, Peerachet Hu, Jiawei Zhao, Qiuye Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China ADAPT Centre School of Computing Dublin City University Ireland
We participated in the WMT 2016 shared news translation task on English ? Chinese language pair. Our systems are based on the encoder-decoder neural machine translation model with the attention mechanism. We employ th... 详细信息
来源: 评论
The correspondence between the concepts in description logics for contexts and formal concept analysis
收藏 引用
Science China(information Sciences) 2012年 第5期55卷 1106-1122页
作者: MA Yue 1,2,SUI YueFei 1 & CAO CunGen 1 1 key laboratory of intelligent information processing,Institute of computing Technology,Chinese Academy of Sciences,Beijing 100190,China 2 Graduate University of Chinese Academy of Sciences,Beijing,China 1. Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China2. Graduate University of Chinese Academy of Sciences Beijing 100049 China
Formal concept analysis (FCA) and description logic (DL) are meant to be formalizations of concepts.A formal concept in the former consists of its intent and extent,where the intent is the set of all the attributes sh... 详细信息
来源: 评论
An automatic semantic relationships discovery approach  04
An automatic semantic relationships discovery approach
收藏 引用
13th International World Wide Web Conference on Alternate Track, Papers and Posters, WWW Alt. 2004
作者: Zhuge, Hai Zheng, Liping Zhang, Nan Li, Xiang China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China
An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for const... 详细信息
来源: 评论
A subtree-based factorization of dependency parsing  26
A subtree-based factorization of dependency parsing
收藏 引用
26th International Conference on Computational Linguistics, COLING 2016
作者: Zhao, Qiuye Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China ADAPT Centre School of Computing Dublin City University Ireland
We propose a dependency parsing pipeline, in which the parsing of long-distance projections and localized dependencies are explicitly decomposed at the input level. A chosen baseline dependency parsing model performs ... 详细信息
来源: 评论
Enhancing Multi-turn Dialogue Modeling with Intent information for E-Commerce Customer Service  9th
Enhancing Multi-turn Dialogue Modeling with Intent Informati...
收藏 引用
9th CCF International Conference on Natural Language processing and Chinese computing, NLPCC 2020
作者: Liu, Ruixue Chen, Meng Liu, Hang Shen, Lei Song, Yang He, Xiaodong JD AI Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China
Nowadays, it is a heated topic for many industries to build intelligent conversational bots for customer service. A critical solution to these dialogue systems is to understand the diverse and changing intents of cust... 详细信息
来源: 评论
Viterbi Decoding of Directed Acyclic Transformer for Non-Autoregressive Machine Translation
Viterbi Decoding of Directed Acyclic Transformer for Non-Aut...
收藏 引用
2022 Findings of the Association for Computational Linguistics: EMNLP 2022
作者: Shao, Chenze Ma, Zhengrui Feng, Yang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China
Non-autoregressive models achieve significant decoding speedup in neural machine translation but lack the ability to capture sequential dependency. Directed Acyclic Transformer (DA-Transformer) was recently proposed t... 详细信息
来源: 评论
αSetup-PCTL:An Adaptive Setup-Based Two-Level Preconditioner for Sequence of Linear Systems of Three-Temperature Energy Equations
收藏 引用
Communications in Computational Physics 2022年 第10期32卷 1287-1309页
作者: Silu Huang Xiaoqiang Yue Xiaowen Xu Laboratory of Computational Physics Institute of Applied Physics and ComputationalMathematicsBeijing 100088China National Center for Applied Mathematics in Hunan Key Laboratory of Intelligent Computing and Information Processing of Ministry of EducationHunan Key Laboratory for Computation and Simulation in Science and EngineeringXiangtan UniversityXiangtan 411105China
The iterative solution of the sequence of linear systems arising from threetemperature(3-T)energy equations is an essential component in the numerical simulation of radiative hydrodynamic(RHD)***,due to the complicate... 详细信息
来源: 评论
Motion Matters: Difference-based Multi-scale Learning for Infrared UAV Detection
Motion Matters: Difference-based Multi-scale Learning for In...
收藏 引用
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023
作者: He, Ruian Zhou, Shili Cheng, Ri Sun, Yuqi Tan, Weimin Yan, Bo Shanghai Collaborative Innovation Center of Intelligent Visual Computing Fudan University School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Shanghai China
Unmanned Aerial Vehicle (UAV) detection in the wild is a challenging task due to the presence of background noise and the varying size of the object. To address these obstacles, we propose a novel learning framework f... 详细信息
来源: 评论
MAGE: Multi-agent environment
MAGE: Multi-agent environment
收藏 引用
2003 International Conference on Computer Networks and Mobile computing, ICCNMC 2003
作者: Shi, Zhongzhi Zhang, Haijun Dong, Mingkai Zhao, Zhikung Sheng, Qiujian Jiang, Yuncheng Cheng, Yong Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences PO Box 2704 Beijing100080 China
intelligent agent technology has been raised as the primary technology in the intelligent Internet and mobile computing. In this paper, MAGE (multi-agent environment) is introduced which is an environment for rapidly ... 详细信息
来源: 评论
intelligent science  1
收藏 引用
12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular computing, RSFDGrC 2009
作者: Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Kexueyuan Nanlu #6 Beijing 100190 China
Intelligence Science is an interdisciplinary subject which dedicates to joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. Brain scie... 详细信息
来源: 评论