为了解决大型工程项目中文件的传输时间与成本问题,提出一个基于文件工作流的工程项目文件管理优化方法。首先,构建了工程项目文件管理环境和具有逻辑顺序的文件工作流模型,分析了文件的传输和缓存。在此基础上,将文件管理优化问题建模...为了解决大型工程项目中文件的传输时间与成本问题,提出一个基于文件工作流的工程项目文件管理优化方法。首先,构建了工程项目文件管理环境和具有逻辑顺序的文件工作流模型,分析了文件的传输和缓存。在此基础上,将文件管理优化问题建模为马尔可夫过程,通过设计状态空间、动作空间及奖励函数等实现文件工作流的任务完成时间与缓存成本的联合优化。其次,采用对抗式双重深度Q网络(dueling double deep Q network,D3QN)来降低训练时间,提高训练效率。仿真结果验证了提出方案在不同参数配置下文件传输的有效性,并且在任务体量增大时仍能保持较好的优化能力。展开更多
In this study,an underwater image enhancement method based on multi-scale adversarial network was proposed to solve the problem of detail blur and color distortion in underwater images.Firstly,the local features of ea...In this study,an underwater image enhancement method based on multi-scale adversarial network was proposed to solve the problem of detail blur and color distortion in underwater images.Firstly,the local features of each layer were enhanced into the global features by the proposed residual dense block,which ensured that the generated images retain more details.Secondly,a multi-scale structure was adopted to extract multi-scale semantic features of the original images.Finally,the features obtained from the dual channels were fused by an adaptive fusion module to further optimize the features.The discriminant network adopted the structure of the Markov discriminator.In addition,by constructing mean square error,structural similarity,and perceived color loss function,the generated image is consistent with the reference image in structure,color,and content.The experimental results showed that the enhanced underwater image deblurring effect of the proposed algorithm was good and the problem of underwater image color bias was effectively improved.In both subjective and objective evaluation indexes,the experimental results of the proposed algorithm are better than those of the comparison algorithm.展开更多
Aiming at the problem of small area human occlusion in gait recognition,a method based on generating adversarial image inpainting network was proposed which can generate a context consistent image for gait occlusion a...Aiming at the problem of small area human occlusion in gait recognition,a method based on generating adversarial image inpainting network was proposed which can generate a context consistent image for gait occlusion area.In order to reduce the effect of noise on feature extraction,the stacked automatic encoder with robustness was used.In order to improve the ability of gait classification,the sparse coding was used to express and classify the gait features.Experiments results showed the effectiveness of the proposed method in comparison with other state-of-the-art methods on the public databases CASIA-B and TUM-GAID for gait recognition.展开更多
文摘为了解决大型工程项目中文件的传输时间与成本问题,提出一个基于文件工作流的工程项目文件管理优化方法。首先,构建了工程项目文件管理环境和具有逻辑顺序的文件工作流模型,分析了文件的传输和缓存。在此基础上,将文件管理优化问题建模为马尔可夫过程,通过设计状态空间、动作空间及奖励函数等实现文件工作流的任务完成时间与缓存成本的联合优化。其次,采用对抗式双重深度Q网络(dueling double deep Q network,D3QN)来降低训练时间,提高训练效率。仿真结果验证了提出方案在不同参数配置下文件传输的有效性,并且在任务体量增大时仍能保持较好的优化能力。
文摘In this study,an underwater image enhancement method based on multi-scale adversarial network was proposed to solve the problem of detail blur and color distortion in underwater images.Firstly,the local features of each layer were enhanced into the global features by the proposed residual dense block,which ensured that the generated images retain more details.Secondly,a multi-scale structure was adopted to extract multi-scale semantic features of the original images.Finally,the features obtained from the dual channels were fused by an adaptive fusion module to further optimize the features.The discriminant network adopted the structure of the Markov discriminator.In addition,by constructing mean square error,structural similarity,and perceived color loss function,the generated image is consistent with the reference image in structure,color,and content.The experimental results showed that the enhanced underwater image deblurring effect of the proposed algorithm was good and the problem of underwater image color bias was effectively improved.In both subjective and objective evaluation indexes,the experimental results of the proposed algorithm are better than those of the comparison algorithm.
基金Project(51678075) supported by the National Natural Science Foundation of ChinaProject(2017GK2271) supported by Hunan Provincial Science and Technology Department,China
文摘Aiming at the problem of small area human occlusion in gait recognition,a method based on generating adversarial image inpainting network was proposed which can generate a context consistent image for gait occlusion area.In order to reduce the effect of noise on feature extraction,the stacked automatic encoder with robustness was used.In order to improve the ability of gait classification,the sparse coding was used to express and classify the gait features.Experiments results showed the effectiveness of the proposed method in comparison with other state-of-the-art methods on the public databases CASIA-B and TUM-GAID for gait recognition.
