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检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

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the Research and application of Human Detection Based on Support Vector machine using in Intelligent Video Surveillance System

The Research and Application of Human Detection Based on Sup...

引用

4th international conference on Natural Computation (ICNC 2008)

作者： Fan, Xinnan Xu, Lizhong Zhang, Xuewu Chen, Lei Hohai Univ Comp & Informat Inst Changzhou 213022 Peoples R China

ISBN: (纸本)9780769533049

this paper presented a special design and implementation of human detection based on SVM (support vector machine) and this method is used in intelligent video surveillance system. In order to simplify the design of the SVM classifier and improve efficiency of machine learning, both a grid vector representation and a center radiating vector representation are proposed to abstract features of the object. the sample data is obtained through processing and analysis including human and no-human which forms the training input to SVM. Finally, we used the trained recognizer to identify whether there is somebody broken into the object region. If there is, the automatic warning device gives the alarm, which guarantees a real-time surveillance.

关键词： Support vector machines

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An application with UML Object-based Petri Nets for C4ISR architecture simulation validation

An application with UML Object-based Petri Nets for C4ISR ar...

引用

7th international conference on machine learning and Cybernetics

作者： Bai, Xiao-Hui Heilongjiang Univ Coll Informat Sci & Technol Harbin Heilongjiang 150080 Peoples R China

ISBN: (纸本)9781424420957

Architecture validation plays an important role in military command and control system design. the paper applies some kinds of views of UML (Unified Modeling Language) to describe the relative C4ISR (Command, Control, Communication, computer, Intelligence, Surveillance and Reconnaissance) architecture products. Considering the relationship among the products, the architecture products modeling in UML diagram is transformed to the executable OPN (Object-based Petri Nets) models based on the transformation rules. It shows the process of OPN mechanisms application for the C4ISR system design validation. Finally, the paper gives one system validation example in the air defense system using the proposed validation method. through analyzing model execution process and result, the performance of C4ISR system can be tested.

关键词： Enterprise Architecture (ES) C4ISR system Unified Modeling Language (UML) Object-based Petri Nets (OPN) architecture validation executable model

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Digital agriculture: learning to feed a hungry world

Digital agriculture: Learning to feed a hungry world

引用

4th IEEE international conference on eScience, eScience 2008

作者： Myers, James McLaren, Terry Wadsworth, Andrew National Center for Super Computing Applications University of Illinois Urbana IL 61801 United States

ISBN: (纸本)9780769535357

A synthesis framework integrates data from multiple sources, enables on-demand execution of scientific workflows, and associates data outputs with multiple visualization and analysis widgets in a dynamically-generated web application. this poster presents an implementation of NCSA's Digital Synthesis Framework (DSF) that incorporates a state-of-the-art generic crop growth simulation model and historic weather data for the purposes of designing educational activities for young learners. the work is the result of a collaboration between NCSA and local 4-H curriculum specialists. © 2008 IEEE.

关键词： Data visualization

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Self-optimizing memory controllers:: A reinforcement learning approach 08

Self-optimizing memory controllers:: A reinforcement learnin...

引用

35th Annual international Symposium on computer Architecture

作者： Ipek, Engin Mutlu, Onur Martinez, Jose F. Caruana, Rich Cornell Univ Ithaca NY 14850 USA Microsoft Res Redmond WA 98052 USA

ISBN: (纸本)9780769531748

Efficiently utilizing off-chip DRAM bandwidth is a critical issue in designing cost-effective, high-performance chip multiprocessors (CMPs). Conventional memory controllers deliver relatively low performance in part because they often employ fixed, rigid access scheduling policies designed for average-case application behavior. As a result, they cannot learn and optimize the long-term performance impact of their scheduling decisions, and cannot adapt their scheduling policies to dynamic workload behavior. We propose a new, self-optimizing memory controller design that operates using the principles of reinforcement learning (RL) to overcome these limitations. Our RL-based memory controller observes the system state and estimates the long-term performance impact of each action it can take. In this way, the controller learns to optimize its scheduling policy on the fly to maximize long-term performance. Our results show that an RL-based memory controller improves the performance of a set of parallel applications run on a 4-core CMP by 19% on average (up to 33%), and it improves DRAM bandwidth utilization by 22% compared to a state-of-the-art controller.

关键词： Chip Multiprocessors Memory Systems Memory Controller machine learning Reinforcement learning

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Prosody variation: application to automatic prosody evaluation of mandarin speech

Prosody variation: Application to automatic prosody evaluati...

引用

4th international conference on Speech Prosody 2008, SP 2008

作者： Jia, Huibin Tao, Jianhua Wang, Xia National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 10080 China Nokia Research Centre China

ISBN: (纸本)9780616220030

Prosody evaluation is an essential part of computer-aided language learning system. In the paper, prosodic variability among inter-speakers is investigated based on a database containing eight repetitions of 200 sentences. For Mandarin of reading style, its variability can be analyzed from rhythm, intonation and tone. Experimental results show that the mean correlation of tone between inter-speakers is 0.70, intonation and rhythm are 0.81. Based on these analyses, the prosodic similarity between the tested and standard utterances is calculated to automatically evaluate prosody quality. the standard utterances were recorded by multiple speakers, so they can cover different prosody patterns for the same utterance. the prosodic similarities are calculated from three aspects: tone, intonation and rhythm. Based on these similarities, the prosody quality can be graded. the method evaluated on the collected database has achieved good performance, and the correlation of human-machine scores is close to that of human-human scores.

关键词： Quality control

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A New Support Vector machine Model and its application in Time-varying Signal Classification

A New Support Vector Machine Model and its Application in Ti...

引用

4th international conference on Natural Computation (ICNC 2008)

作者： Xu Shao-Hua Wang Bing Daqing Petr Inst Sch Comp & Informat Technol Daqing Heilongjiang Peoples R China

ISBN: (纸本)9780769533049

Aiming at the problem that conventional methods of Support Vector machine (SVM) are difficult to solve classification of Time-Varying Signal patterns directly, this paper presents a Process Support Vector machine (PSVM) model. the input of PSVM can be functions with time-varying (or function vector). through the kernel function transforming, dynamic pattern is mapped into high-dimensional feature space. After learning classification characteristic of the training samples, PSVM can extract process characteristics Of time-varying function adoptively and classify time-varying signals directly. Some theoretical problems were proved, such as the equivalence of PSVM's dynamic pattern classification injunction space and SVM's pattern classification in high-dimensional metric space under a group of orthogonal function basis, the equivalence on two-category ability of PSVM and three-layer Feedforward Process Neural Networks, etc. the model of PSVM and its solving algorithm were given. the results of simulation experiments confirmed the efficiency of the model and algorithm.

关键词： Support vector machines

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Improving XCS Performance by Distribution

Improving XCS Performance by Distribution

引用

7th international conference on Simulated Evolution and learning

作者： Richter, Urban Prothmann, Holger Schmeck, Hartmut Karlsruhe Inst Technol Inst AIFB D-76128 Karlsruhe Germany

ISBN: (纸本)9783540896937

learning Classifier Systems (LCSs) axe rule-based evolutionary reinforcement, learning (RL) systems. Today, especially variants of Wilson's extended Classifier System (XCS) are widely applied for machine learning. Despite their widespread application, LCSs have drawbacks: the number of reinforcement cycles an LCS requires for learning largely depends on the complexity of the learning task. A straightforward way to reduce this complexity is to split the task into smaller sub-problems. Whenever this can be done, the performance should lie improved significantly. In this paper, a nature-inspired multi-agent scenario is used to evaluate and compare different distributed LCS variants. Results show that improvements in learning speed can be achieved by cleverly dividing a problem into smaller learning sub-problems.

关键词： Reinforcement learning

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Semi-supervised learning Algorithm Based on Simplified Association Rules Combining with k-mean and Its application in Land Evaluation

Semi-supervised Learning Algorithm Based on Simplified Assoc...

引用

4th international conference on Natural Computation (ICNC 2008)

作者： Li, Ting Yang, Jingfeng Peng, Xiaoqin Chen, Zhimin Lu, Chengyang South China Agr Univ Guangzhou 510642 Guangdong Peoples R China Zhongshan Torch Polytech Zhongshan 528436 Peoples R China Tianfu Coll Southwestern Univ Finance & Econ Mianyang 621000 Peoples R China Chung Tak Lighting Control Syst Guangzhou Ltd Guangzhou 511400 Guangdong Peoples R China

ISBN: (纸本)9780769533049

In order to construct intelligible and effective land evaluation classifier, a semi-supervised learning algorithm constructed by utilizing simplified association rules combining with k-mean clustering algorithm is proposed in this paper. To reduce the complexity of the land evaluation models and improve the efficiency and intelligibility of association rules further, an algorithm to eliminate redundant rules for obtaining the simplified association rules is presented Experimental results of Guangdong Province land resource demonstrate that, by only using 500 training samples chosen randomly, 89.5143% correct area rate of land evaluation could be obtained by the semi-supervised learning algorithm. It provides a higher precision with the accuracy improved by 14.3484%, comparing with the results of the method k-mean and 7.1159% comparing with the results of the method support vector machine in the same condition.

关键词： Simplified Association rules k-mean Semi-supervised learning Fuzzy decision Land evaluation

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On the quantitative analysis of Deep Belief Networks 08

On the quantitative analysis of Deep Belief Networks

引用

25th international conference on machine learning, ICML 2008

作者： Salakhutdinov, Ruslan Murray, Iain Department of Computer Science University of Toronto Toronto ON M5S 3G4 Canada

ISBN: (纸本)9781605582054

Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allowed these models to be applied successfully in many application domains. the main building block of a DBN is a bipartite undirected graphical model called a restricted Boltzmann machine (RBM). Due to the presence of the partition function, model selection, complexity control, and exact maximum likelihood learning in RBM's are intractable. We show that Annealed Importance Sampling (AIS) can be used to efficiently estimate the partition function of an RBM, and we present a novel AIS scheme for comparing RBM's with different architectures. We further show how an AIS estimator, along with approximate inference, can be used to estimate a lower bound on the log-probability that a DBN model with multiple hidden layers assigns to the test data. this is, to our knowledge, the first step towards obtaining quantitative results that would allow us to directly assess the performance of Deep Belief Networks as generative models of data.

关键词： Inference engines

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A novel multi-robot coordination method based on reinforcement learning

引用

4th international conference on Intelligent Computing

作者： Fan, Jian Fei, MinRui Sha, LiKang Huang, Feng Shanghai Univ Coll Mech Engn & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200072 Peoples R China Nanjing Army Command Coll Operat Res Ctr Nanjing 210045 Peoples R China PLA Artillery Acad Hefei 230031 Peoples R China PLA Inst Commun & Command Staff Room Peoples Air Def Command & Commun Wuhan 430010 Peoples R China

ISBN: (纸本)9783540874409

Focusing on multi-robot coordination, role transformation and reinforcement learning method are combined in this paper. Under centralize control framework, the distance nearest rule which means that the nearest robot ranges from obstacles is selected to be the master robot for controlling salve robots is presented. Meanwhile, different from traditional way which reinforcement learning is applied in online learning of multi-robot coordination, this paper proposed a novel behavior weight method based on reinforcement learning, the robot behavior weights are optimized through interacting with environment and the coordination policy based on maximum behavior value is presented to plan the collision avoidance behavior of robot. the learning method proposed in this paper is applied to the application related to collaboration movement of mobile robots and demonstrated by the simulation results presented in this paper.

关键词： Behavior weight Multi-robot Reinforcement learning Role transformation

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