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浏览/检索结果: 共8条，第1-8条 帮助

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Depth perceptual region-of-interest based multiview video coding 期刊论文  iSwitch采集
Journal of visual communication and image representation, 2010, 卷号: 21, 期号: 5-6, 页码: 498-512
作者:  Zhang, Yun;  Jiang, Gangyi;  Yu, Mei;  Yang, You;  Peng, Zongju
收藏  |  浏览/下载：28/0  |  提交时间：2019/05/10
Depth perceptual region-of-interest based multiview video coding 期刊论文  OAI收割
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2010, 卷号: 21, 期号: 5-6, 页码: 498-512
作者:  Zhang, Yun;  Jiang, Gangyi;  Yu, Mei;  Yang, You;  Peng, Zongju
  |  收藏  |  浏览/下载：28/0  |  提交时间：2019/12/16
Concealment of whole-picture loss in hierarchical b-picture scalable video coding 期刊论文  iSwitch采集
Ieee transactions on multimedia, 2009, 卷号: 11, 期号: 1, 页码: 11-22
作者:  Ji, Xiangyang;  Zhao, Debin;  Gao, Wen
收藏  |  浏览/下载：34/0  |  提交时间：2019/05/10
Concealment of Whole-Picture Loss in Hierarchical B-Picture Scalable Video Coding 期刊论文  OAI收割
IEEE TRANSACTIONS ON MULTIMEDIA, 2009, 卷号: 11, 期号: 1, 页码: 11-22
作者:  Ji, Xiangyang;  Zhao, Debin;  Gao, Wen
  |  收藏  |  浏览/下载：25/0  |  提交时间：2019/12/16
B-picture coding in AVS video compression standard 期刊论文  OAI收割
SIGNAL PROCESSING-IMAGE COMMUNICATION, 2008, 卷号: 23, 期号: 1, 页码: 31-41
作者:  Ji, Xiangyang;  Zhao, Debin;  Wu, Feng;  Lu, Yan;  Gao, Wen
  |  收藏  |  浏览/下载：14/0  |  提交时间：2019/12/16
Block-wise adaptive motion accuracy based b-picture coding with low-complexity motion compensation 期刊论文  iSwitch采集
Ieee transactions on circuits and systems for video technology, 2007, 卷号: 17, 期号: 8, 页码: 1085-1090
作者:  Ji, Xiangyang;  Zhao, Debin;  Gao, Wen
收藏  |  浏览/下载：16/0  |  提交时间：2019/05/10
Block-wise adaptive motion accuracy based B-Picture coding with low-complexity motion compensation 期刊论文  OAI收割
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2007, 卷号: 17, 期号: 8, 页码: 1085-1090
作者:  Ji, Xiangyang;  Zhao, Debin;  Gao, Wen
  |  收藏  |  浏览/下载：23/0  |  提交时间：2019/12/16
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：36/0  |  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