机构

• 软件研究所 [3]
• 地理科学与资源研究所 [1]
• 计算技术研究所 [1]
• 长春光学精密机械与物... [1]
• 自动化研究所 [1]

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• OAI收割 [7]

内容类型

• 期刊论文 [4]
• 会议论文 [3]

发表日期

• 2021 [1]
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• 2011 [1]
• 2010 [2]
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学科主题

• Computer S... [1]

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浏览/检索结果: 共7条，第1-7条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Siamese Regression Tracking With Reinforced Template Updating 期刊论文  OAI收割 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 628-640 作者:  Zhao, Fei;  Zhang, Ting;  Song, Yibing;  Tang, Ming;  Wang, Xiaobo   |  收藏  |  浏览/下载：38/0  |  提交时间：2021/03/02 Target tracking  Training  Reinforcement learning  Visualization  Task analysis  Benchmark testing  Head  Siamese regression tracking  actor-critic network  reinforcement learning   ParaML: A Polyvalent Multicore Accelerator for Machine Learning 期刊论文  OAI收割 IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2020, 卷号: 39, 期号: 9, 页码: 1764-1777 作者:  Zhou, Shengyuan;  Guo, Qi;  Du, Zidong;  Liu, Daofu;  Chen, Tianshi   |  收藏  |  浏览/下载：42/0  |  提交时间：2020/12/10 Neural networks  Machine learning  Testing  Support vector machines  Linear regression  Computers  Computer architecture  Accelerator  machine learning (ML) techniques  multicore accelerator   Will This Bug-fixing Change Break Regression Testing? 会议论文  OAI收割 the International Symposium on Empirical Software Engineering and Measurement(ESEM), 中国北京友谊宾馆, 2015-10-25 Xinye Tang; Song Wang; Ke Mao   |  收藏  |  浏览/下载：30/0  |  提交时间：2016/06/04 source code change impact analysis  regression testing  static program analysis   An instream ecological flow method for data-scarce regulated rivers 期刊论文  OAI收割 Journal of Hydrology, 2011, 卷号: 398, 期号: 1-2, 页码: 17-25 Liu C. M.; Zhao changsen(赵长森); Xia J.; Sun C. L.; Wang R.; Liu T. 收藏  |  浏览/下载：34/0  |  提交时间：2012/06/08 Instream ecological flow (IEF)  Instream Ecological Water-level (IEW)  Data-scarce rivers  The Huai River  testing serial-correlation  regression-models  heteroscedasticity  multicollinearity   testing in parallel: a need for practical regression testing 会议论文  OAI收割 5th International Conference on Software and Data Technologies, ICSOFT 2010, Athens, Greece, 37459 Zhang Zhenyu; Tong Zijian; Gao Xiaopeng   |  收藏  |  浏览/下载：14/0  |  提交时间：2011/03/31 Data visualization  Pipelines  Problem solving  Regression analysis  Scheduling  Testing  Visualization   JUTA:一个Java自动化单元测试工具 期刊论文  OAI收割 计算机研究与发展, 2010, 卷号: 47, 期号: 10, 页码: 1840-1848 严俊; 郭涛; 阮辉; 玄跻峰   |  收藏  |  浏览/下载：38/0  |  提交时间：2011/05/23 Java单元测试  动态测试  静态测试  程序分析  符号执行Automatic testing  Data flow analysis  Errors  Java programming language  Regression analysis  Steel bridges   Study on color model conversion for camera with neural network based on the combination between second general revolving combination design and genetic algorithm (EI CONFERENCE) 会议论文  OAI收割 ICO20: Illumination, Radiation, and Color Technologies, August 21, 2005 - August 26, 2005, Changchun, China 作者:  Li Z.;  Zhou F.;  Wang C.;  Li Z. 收藏  |  浏览/下载：38/0  |  提交时间：2013/03/25 Munsell color system is selected to establish the mutual conversion between RGB and L*a*b* color model for camera. The color luminance meter and CCD camera synchronously measure the same color card  XYZ value is gotten from the color luminance meter  the training error is 0.000748566  it can show that the method combining second general revolving combination design with genetic algorithm can optimize the hidden-layer structure of neural network. Using the data of testing set to test this network and calculating the color difference between forecast value and true value  the color picture captured from CCD camera is expressed for RGB value as the input of neural network  and the L*a*b* value converted from XYZ value is regarded as the real color value of target card  which the difference is not obvious comparing with forecast result  the maximum is 5.6357 NBS  namely the output of neural network. The neural network of two hidden-layers is considered  the minimum is 0.5311 NBS  so the second general revolving combination design is introduced into optimizing the structure of neural network  and the average of color difference is 3.1744 NBS.  which can carry optimization through unifying project design  data processing and the precision of regression equation. Their mathematics model of encoding space is gained  and the significance inspection shows the confidence degree of regression equation is 99%. The mathematics model is optimized by genetic algorithm  optimization solution is gotten  and function value of the goal is 0.0007168. The neural network of the optimization solution is trained