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Design of a new kind of chemical experiment container with virtual reality fusion

Virtual Reality & intelligent Hardware 2023年第4期5卷 317-337页

作者： Lurong YANG Zhiquan FENG Junhong MENG Department of Information Science and Engineering University of JinanJinan 250022China Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan 250022China

Background At present,the teaching of experiments in primary and secondary schools is affected by cost and security *** research on virtual experiment platforms has alleviated these ***,the lack of real experimental equipment and use of a single channel to understand user intentions weaken these platforms operationally and degrade the naturalness of *** To solve these problems,we propose an intelligent experimental container structure and a situational awareness algorithm,both of which are verified and applied to a chemical experiment involving virtual-real ***,the acquired images are denoised in the visual channel using the maximum diffuse reflection chroma to remove ***,container situational awareness is realized by segmenting the image liquid level and establishing a relation-fitting ***,strategies for constructing complete behaviors and making priority comparisons among behaviors are adopted for information complementarity and independence,respectively.A multichannel intentional understanding model and an inter-active paradigm that integrates vision,hearing,and touch are *** The experimental results show that the accuracy of the intelligent container situation awareness proposed in this paper reaches 99%,and the accuracy of the proposed intention understanding algorithm reaches 94.7%.The test shows that the intelligent experimental system based on the new interaction paradigm also has better performance and a more realistic sense of operation experience in terms of experimental *** The results indicate that the proposed experimental container and algorithm can achieve a natural level of human-computer interaction in a virtual chemical experiment platform,enhance the user′s sense of operation,and achieve high levels of user satisfaction.

关键词： Multichannel intent fusion understanding Virtual-real fusion Natural interaction Remove image highlights Nonlinear curve fitting

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Progress and Challenge of Artificial Intelligence

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Journal of Computer Science & Technology 2006年第5期21卷 810-822页

作者：史忠植郑南宁 Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 P.R. China The Laboratory of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an 710049 P.R. China

Artificial Intelligence （AI） is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

关键词： artificial intelligence visual perception machine learning agent computing semantic web intelligence science

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An intelligent navigation experimental system based on multi-mode fusion

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Virtual Reality & intelligent Hardware 2020年第4期2卷 345-353页

作者： Rui HAN Zhiquan FENG Jinglan TIAN Xue FAN Xiaohui YANG Qingbei GUO School of Information Science and Engineering University of JinanJinan 250022China Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan 250022China

At present,most experimental teaching systems lack guidance of an operator,and thus users often do not know what to do during an *** user load is therefore increased,and the learning efficiency of the students is *** solve the problem of insufficient system interactivity and guidance,an experimental navigation system based on multi-mode fusion is proposed in this *** system first obtains user information by sensing the hardware devices,intelligently perceives the user intention and progress of the experiment according to the information acquired,and finally carries out a multi-modal intelligent navigation process for *** an innovative aspect of this study,an intelligent multi-mode navigation system is used to guide users in conducting experiments,thereby reducing the user load and enabling the users to effectively complete their *** results prove that this system can guide users in completing their experiments,and can effectively reduce the user load during the interaction process and improve the efficiency.

关键词： Navigation interaction Chemical experiment system Multi-mode fusion

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Hand gesture tracking algorithm based on visual attention

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Journal of Beijing Institute of Technology 2016年第4期25卷 491-501页

作者：冯志全徐涛吕娜唐好魁蒋彦梁丽伟 School of Information Science and Engineering University of JinanJinan 250022China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing Jinan 250022China

In the majority of the interaction process, the operator often focuses on the tracked 3D hand gesture model at the ＂interaction points＂ in the collision detectionscene, such as ＂grasp＂ and ＂release＂ and objects in the scene, without paying attention to the tracked 3D hand gesture model in the total procedure. Thus in this paper, a visual attention distribution model of operator in the ＂grasp＂, ＂translation＂, ＂release＂ and other basic operation procedures is first studied and a 3D hand gesture tracking algorithm based on this distribution model is proposed. Utilizing the algorithm, in the period with a low degree of visual attention, a pre-stored 3D hand gesture animation can be used to directly visualise a 3D hand gesture model in the interactive scene; in the time period with a high degree of visual attention, an existing ＂frame-by-frame tracking＂ approach can be adopted to obtain a 3D gesture model. The results demonstrate that the proposed method can achieve real-time tracking of 3D hand gestures with an effective improvement on the efficiency, fluency, and availability of 3D hand gesture interaction.

关键词： visual attention 3D hand gesture tracking hand gesture interaction

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Plankton classification with deep convolutional neural networks

Plankton classification with deep convolutional neural netwo...

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2016 IEEE information Technology, networking, Electronic and Automation Control Conference, ITNEC 2016

作者： Py, Ouyang Hong, Hu Zhongzhi, Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467391924

Traditional methods for measuring and monitoring plankton populations are time consuming and can not scale to the granularity or scope necessary for large-scale studies. Improved approaches are needed. Manual analysis of the imagery captured by underwater camera system is infeasible. Automated image classification using machine learning tools is an alternative to the manual approach. In this paper, we present a deep neural network model for plankton classification which exploits translational and rotational symmetry. In this work, we propose two constrains in the design of deep convolutional neural network structure to guarantee the performance gain when going deep. Firstly, for each convolutional layer, its capacity of learning more complex patterns should be guaranteed;Secondly, the receptive field of the topmost layer should be no larger than the image region. We also developed a 'inception layer' like structure to deal with multi-size imagery input with convolutional neural network. The experimental result on Plankton Set 1.0 imagery data set show the feasibility and effectiveness of the proposed method. © 2016 IEEE.

关键词： Image classification

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Effectively Discriminating Fighting Shots in Action Movies

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Journal of Computer Science & Technology 2011年第1期26卷 187-194页

作者：马述高王伟强 School of Information Science and Engineering Graduate University of Chinese Academy of Sciences Computer Science Department Boston UniversityBoston MA 02215U.S.A. Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

Fighting shots are the highlights of action movies and an effective approach to discriminating fighting shots is very useful for many applications, such as movie trailer construction, movie content filtering, and movie content retrieval. In this paper, we present a novel method for this task. Our approach first extracts the reliable motion information of local invariant features through a robust keypoint tracking computation; then foreground keypoints are distinguished from background keypoints by a sophisticated voting process; further, the parameters of the camera motion model is computed based on the motion information of background keypoints, and this model is then used as a reference to compute the actual motion of foreground keypoints; finally, the corresponding feature vectors are extracted to characterizing the motions of foreground keypoints, and a support vector machine （SVM） classifier is trained based on the extracted feature vectors to discriminate fighting shots. Experimental results on representative action movies show our approach is very effective.

关键词： video analysis motion concept learning

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network link weight optimization based on antisymmetric deep graph networks and reinforcement learning 6

Network link weight optimization based on antisymmetric deep...

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6th International Conference on Next Generation Data-Driven networks, NGDN 2024

作者： Chen, Yuhan Guo, Yingya Department of Computer and Data Science Fuzhou University Fuzhou China Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (纸本)9798350388374

Route optimization is a key core technology to optimize network traffic distribution, achieve network load balancing, and improve network performance. Traditional distributed networks widely run shortest-path based routing protocols, and the path of traffic is determined by the link weights of the distributed network, so routing optimization methods are usually optimized around the link weights of the network. Heuristics-based link weight optimization methods are widely used. However, heuristic methods rely on manually set rules, which are poorly generalized and cannot adapt well to dynamically changing traffic demands. Compared to heuristics, deep reinforcement learning (DRL) has the advantage of extracting more accurate feature representations in addition to its ability to handle high-dimensional state and action spaces. We propose a network link weight optimization method based on anti-symmetric deep graph networks (A-DGN) and reinforcement learning using a novel GNN framework anti-symmetric deep graph networks, where link weights are adjusted to reduce the network link utilization with the optimization objective of minimizing the maximum link utilization in the network. Experimental results show that the proposed method achieves significant performance improvements in the link weight optimization problem in four real-world network topology scenarios. © 2024 IEEE.

关键词： Deep reinforcement learning

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Effectively constructing reliable data for cross-domain text classification

Effectively constructing reliable data for cross-domain text...

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7th IFIP International Conference on intelligent information processing, IIP 2012

作者： Zhuang, Fuzhen He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783642328909

Traditional classification algorithms often fail when the independent and identical distributed (i.i.d.) assumption does not hold, and the cross-domain learning emerges recently is to deal with this problem. Actually, we observe that though the trained model from training data may not perform well over all test data, it can give much better prediction results on a subset of the test data with high prediction confidence. Also this subset of data from test data set may have more similar distribution with the test data. In this study, we propose to construct the reliable data set with high prediction confidence, and use this reliable data as training data. Furthermore, we develop an EM algorithm to refine the model trained from the reliable data. The extensive experiments on text classification verify the effectiveness and efficiency of our methods. It is worth to mention that the model trained from the reliable data achieves a significant performance improvement compared with the one trained from the original training data, and our methods outperform all the baseline algorithms. © 2012 IFIP International Federation for information processing.

关键词： Forecasting

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An orientation model for hierarchical phrase-based translation

An orientation model for hierarchical phrase-based translati...

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2011 International Conference on Asian Language processing, IALP 2011

作者： Xiao, Xinyan Su, Jinsong Liu, Yang Liu, Qun Lin, Shouxun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769545547

The hierarchical phrase-based (HPB) translation exploits the power of grammar to perform long distance reorderings, without specifying nonterminal orientations against adjacent blocks or considering the lexical information covered by nonterminals. In this paper, we borrow from phrase-based system the idea of orientation model to enhance the reordering ability of HPB translation. We distinguish three orientations (monotone, swap, discontinuous) of a nonterminal based on the alignment of grammar, and select the appropriate orientation of nonterminal using lexical information covered by it. By incorporating the orientation model, our approach significantly outperforms a standard HPB system up to 1.02 Bleu on large scale NIST Chinese-English translation task, and 0.51 Bleu on WMT German-English translation task. © 2011 IEEE.

关键词： Natural language processing systems

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Circular spot detection and segmentation with rotating line local binary analysis

Circular spot detection and segmentation with rotating line ...

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作者： Zhang, Dongbo Liu, Xia College of Information Engineering Xiangtan University China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education China

ISBN: (纸本)9781479957514

The circular spots appear as round local peaks/valleys in image space, and they reflect omnidirectional symmetry and Gaussian distribution characteristics. According to these observations, a novel rotating line scan operator is proposed to achieve feature analysis of the spot object. Experimental tests show that the proposed algorithm is robust to spots' appearance variation (size, local contrast and intensity). The method presents promising performance in various real images. © 2014 IEEE.

关键词： Circular spot detection local binary analysis rotating line

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