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	Transportation 5.0: The DAO to Safe, Secure, and Sustainable Intelligent Transportation Systems 期刊论文 OAI收割 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 页码: 17 作者: Wang, Fei-Yue; Lin, Yilun; Ioannou, Petros A.; Vlacic, Ljubo; Liu, Xiaoming \| 收藏 \| 浏览/下载：20/0 \| 提交时间：2023/11/16 Intelligent transportation systems cyber-physical-social systems parallel intelligence knowledge automation DAOs transportation 5.0
	The Development of AgriVerse: Past, Present, and Future 期刊论文 OAI收割 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2023, 页码: 10 作者: \| 收藏 \| 浏览/下载：42/0 \| 提交时间：2023/02/22 Computational modeling Biological systems Biomass Biological system modeling Production Plants (biology) Metaverse Agricultural metaverse (AgriVerse) agriculture cyber-physical-social system (CPSS) artificial systems computational experiments and parallel execution (ACP) decentralized science (DeSci) knowledge-and-data driven modeling parallel agriculture plant model
	软件定义的系统与知识自动化: 从牛顿到莫顿的平行升华期刊论文 OAI收割自动化学报, 2015, 卷号: 41, 期号: 1, 页码: 1-8 作者: 王飞跃收藏 \| 浏览/下载：33/0 \| 提交时间：2017/02/15 知识自动化, 知识机器人, 网络空间, 社会信号, 默顿系统, 平行系统, 平行控制, 社会物理网络系统 Knowledge automation,knowledge robots, cyberspace, social signals ,Merton systems ,parallel systems,parallel control,cyber-physical-social systems
	乒乓球机器人中的学习机制研究学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院大学, 2013 作者: 黄艳龙收藏 \| 浏览/下载：62/0 \| 提交时间：2015/09/02 乒乓球机器人轨迹预测正则化算法并行模糊学习主动学习综合学习局部加权回归物理知识 Ping-pong playing robot trajectory prediction regularization algorithm parallel fuzzy learning active learning integrated learning locally weighted regression physical knowledge
	Restoration of an atmospherically blurred image based on physical model fusion approach (EI CONFERENCE) 会议论文 OAI收割 2010 IEEE 10th International Conference on Signal Processing, ICSP2010, October 24, 2010 - October 28, 2010, Beijing, China 作者: Wang Y.; Li J.; Li J.; Li J.; Wang Y. 收藏 \| 浏览/下载：26/0 \| 提交时间：2013/03/25 This paper proposes a new restoration method only using the single image information combining atmospheric physical model with fusion techniques to reduce the degradation of the image contrast in bad weather conditions caused by atmospheric aerosols such as haze and fog. The basic idea of this method is to utilize physics-based model method instead of multisensors to generate a serial of virtual images and then to fuse those virtual images into a high contrast image based on the wavelet fusion technique. In contrast to previous methods our restoration technique is not only independent on predicted structure distributions of scene reflectance or detailed knowledge about the particular weather condition but also adapt to the situation without a reference image or images with moving objects captured by a video camera. Experiments on different poorcontrast images demonstrate the availability of the proposed method in case of restoring the atmospherically blurred images. 2010 IEEE.