中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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浏览/检索结果: 共12条,第1-10条 帮助

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Optimus: An Operator Fusion Framework for Deep Neural Networks 期刊论文  OAI收割
ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2023, 卷号: 22, 期号: 1, 页码: 26
作者:  
Cai, Xuyi;  Wang, Ying;  Zhang, Lei
  |  收藏  |  浏览/下载:16/0  |  提交时间:2023/07/12
Design and implementation of embedded network master and slave communication based on Modbus/TCP 会议论文  OAI收割
International Conference on Information Technology and Intelligent Manufacturing (ITIM), Zhengzhou, China, Audest 5-6, 2017
作者:  
Jin N(金妮);  Liu MZ(刘明哲);  Wang CX(王晨曦);  Zhang JL(张吉龙);  Xu AD(徐皑冬)
  |  收藏  |  浏览/下载:30/0  |  提交时间:2017/12/11
A real-time small immobile object recognition system using wavelet moment invariants 会议论文  OAI收割
Beijing, China, Aug. 2-5
作者:  
Gu, Jiaojiao;  Wang, Zhao;  Song, Haitao;  Xiao, Han;  He, Wenhao
  |  收藏  |  浏览/下载:118/0  |  提交时间:2016/10/17
a radio-driven time synchronization protocol in hybrid simulation systems 会议论文  OAI收割
2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation, PADS 2012, Zhangjiajie, China, July 15, 2012 - July 19, 2012
Huang Zhiyu
  |  收藏  |  浏览/下载:28/0  |  提交时间:2013/09/22
网络化控制系统的实时性研究与应用 学位论文  OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2007
作者:  
吴金华
收藏  |  浏览/下载:59/0  |  提交时间:2015/09/02
智能轮椅控制及人机接口技术研究 学位论文  OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2007
作者:  
鲁涛
收藏  |  浏览/下载:173/0  |  提交时间:2015/09/02
Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文  OAI收割
4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China
作者:  
Liu H.;  Liu H.;  Liu H.
收藏  |  浏览/下载:38/0  |  提交时间:2013/03/25
An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS). as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image  thus facilitating accurate diagnosis  of course at the expense of higher bit rates  i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization  wavelet coding  neural networks  and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1  or even more)  they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image  but the achievable compression ratios are only of the order 2:1  up to 4:1. In our paper  we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time  we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance  so that all the low rate codes are included at the beginning of the bit stream. Typically  the encoding process stops when the target bit rate is met. Similarly  the decoder can interrupt the decoding process at any point in the bil stream  and still reconstruct the image. Therefore  a compression scheme generating an embedded code can start sending over the network the coarser version of the image first  and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.  
嵌入式网络化控制系统研究与实现 学位论文  OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2005
作者:  
李驹光
收藏  |  浏览/下载:29/0  |  提交时间:2015/09/02
Research on mobile GIS based on LBS 会议论文  OAI收割
IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, New York
Chen, FX; Yang, CJ; Yu, WY; Le, XQ; Yang, JY
收藏  |  浏览/下载:23/0  |  提交时间:2014/12/07
Easisoc: towards cheaper and smaller 期刊论文  iSwitch采集
Mobile ad-hoc and sensor networks, proceedings, 2005, 卷号: 3794, 页码: 229-238
作者:  
Huang, X;  Zhao, Z;  Cui, L
收藏  |  浏览/下载:18/0  |  提交时间:2019/05/10