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arXiv 2017年

作者： Xu, Zhaowei Zhang, Wenhui Sui, Yuefei State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

The general completeness problem of Hoare logic relative to the standard model N of Peano arithmetic has been studied by Cook, and it allows for the use of arbitrary arithmetical formulas as assertions. In practice, the assertions would be simple arithmetical formulas, e.g. of a low level in the arithmetical hierarchy. In addition, we find that, by restricting inputs to N, the complexity of the minimal assertion theory for the completeness of Hoare logic to hold can be reduced. This paper further studies the completeness of Hoare Logic relative to N by restricting assertions to subclasses of arithmetical formulas (and by restricting inputs to N). Our completeness results refine Cook’s result by reducing the complexity of the assertion theory. Copyright © 2017, The Authors. All rights reserved.

关键词： computer circuits

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TasselNet: Counting maize tassels in the wild via local counts regression network

arXiv

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arXiv 2017年

作者： Lu, Hao Cao, Zhiguo Xiao, Yang Zhuang, Bohan Shen, Chunhua National Key Laboratory of Science and Technology on Multi-Spectral Information Processing School of Automation Huazhong University of Science and Technology Wuhan430074 China School of Computer Science University of Adelaide AdelaideSA5005 Australia

Background: Accurately counting maize tassels is important for monitoring the growth status of maize plants. This tedious task, however, is still mainly done by manual efforts. In the context of modern plant phenotyping, automating this task is required to meet the need of large-scale analysis of genotype and phenotype. In recent years, computer vision technologies have experienced a significant breakthrough due to the emergence of large-scale datasets and increased computational resources. Naturally image-based approaches have also received much attention in plant-related studies. Yet a fact is that most image-based systems for plant phenotyping are deployed under controlled laboratory environment. When transferring the application scenario to unconstrained in-field conditions, intrinsic and extrinsic variations in the wild pose great challenges for accurate counting of maize tassels, which goes beyond the ability of conventional image processing techniques. This calls for further robust computer vision approaches to address in-field variations. Results: This paper studies the in-field counting problem of maize tassels. To our knowledge, this is the first time that a plant-related counting problem is considered using computer vision technologies under unconstrained field-based environment. With 361 field images collected in four experimental fields across China between 2010 and 2015 and corresponding manually-labelled dotted annotations, a novel Maize Tassels Counting (MTC) dataset is created and will be released with this paper. To alleviate the in-field challenges, a deep convolutional neural network-based approach termed Tasselnet is proposed. Tasselnet can achieve good adaptability to in-field variations via modelling the local visual characteristics of field images and regressing the local counts of maize tassels. Extensive results on the MTC dataset demonstrate that Tasselnet outperforms other state-of-the-art approaches by large margins and achieves the over

关键词： computer vision

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An attention-based syntax-tree and tree-LSTM model for sentence summarization

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International Journal of Performability Engineering 2017年第5期13卷 775-782页

作者： Liu, Wenfeng Liu, Peiyu Yang, Yuzhen Gao, Yaling Yi, Jing School of Information Science and Engineering Shandong Normal University Jinan250014 China Department of Computer and Information Engineering Heze University Heze274015 China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250014 China Ruipu Peony Industrial Technology Development Co. Ltd 274015 China School of Computer Science and Technology Shandong Jianzhu University Jinan250101 China

Generative Summarization is of great importance in understanding large-scale textual data. In this work, we propose an attention-based Tree-LSTM model for sentence summarization, which utilizes an attention-based syntactic structure as auxiliary information. Thereinto, block-alignment is used to align the input and output syntax blocks, while inter-alignment is used for alignment of words within that of block pairs. To some extent, block-alignment can prevent structural deviations on the long sentences and inter-alignment is capable of increasing the flexibility of the generation in the blocks. This model can be easily trained to end-to-end mode and deal with any length of the input sentences. Compared with several relatively strong baselines, our model has achieved the state-of-art on DUC-2004 shared task. © 2017 Totem Publisher, Inc. All rights reserved.

关键词： Alignment

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Clothing Co-Segmentation Based on HOG Features and E-SVM Classifier 6

Clothing Co-Segmentation Based on HOG Features and E-SVM Cla...

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6th International Conference on Digital Home, ICDH 2016

作者： Zhang, Jianhong Liu, Li Huang, Dongyan Fu, Xiaodong Huang, Qingsong Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China

ISBN: (纸本)9781509044009

To improve the accuracy of clothing segmentation, a novel co-segmentation method is proposed in this paper based on HOG(Histogram of Oriented Gradients) features and E-SVM(Exemplar Support Vector Machine) classifier. The cosegmentation method uses an auxiliary dataset and is implemented with three steps: superpixel grouping, E-SVM classifier training, and segmentation propagation. Firstly, image input by user is segmented in superpixel, such that the images in auxiliary dataset can be divided into multi-regions. Secondly, some regions are selected to a positive segmentation and HOG information is used to train E-SVM classifiers. Finally, the cloth is segmented into user image with E-SVM classifiers and segmentation propagation. Experimental results show that the proposed method can segment clothing images with high accuracy. © 2016 IEEE.

关键词： Superpixels

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Effective blog pages extractor for better UGC accessing

arXiv

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arXiv 2017年

作者： Zhao, Kui Wang, Yi Hu, Xia Wang, Can Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science and Technology Zhejiang University Hangzhou310027 China Hangzhou S&T Information Research Institute Hangzhou310014 China

Blog is becoming an increasingly popular media for information publishing. Besides the main content, most of blog pages nowadays also contain noisy information such as advertisements etc. Removing these unrelated elements can improves user experience, but also can better adapt the content to various devices such as mobile phones. Though template-based extractors are highly accurate, they may incur expensive cost in that a large number of template need to be developed and they will fail once the template is updated. To address these issues, we present a novel template-independent content extractor for blog pages. First, we convert a blog page into a DOM-Tree, where all elements including the title and body blocks in a page correspond to subtrees. Then we construct subtree candidate set for the title and the body blocks respectively, and extract both spatial and content features for elements contained in the subtree. SVM classifiers for the title and the body blocks are trained using these features. Finally, the classifiers are used to extract the main content from blog pages. We test our extractor on 2,250 blog pages crawled from nine blog sites with obviously different styles and templates. Experimental results verify the effectiveness of our extractor. Copyright © 2017, The Authors. All rights reserved.

关键词： Blogs

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Design of Flight Attitude Control Model for the Mini-quadrotor

Design of Flight Attitude Control Model for the Mini-quadrot...

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IEEE International Conference on Mechatronics and Automation

作者： Ma Zhongli Li Huixin Li Qianqian Gu Yanming Li Zuoyong College of Automation Harbin Engineering University Heilongjiang 150001 China School of Astronautics Harbin Institute of Technology Heilongjiang 150001 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou 350121 China

ISBN: (纸本)9781509067602

Micro-quadrotor has recently been used in different areas even military field. However, controlling mini-quadrotor to flight attitude in the air has not been perfectly achieved due to mini-quad rotor's small size and light weight. The purpose of this paper is to introduce the flight attitude control system of mini-quadrotor, including design and simulation of calculations and controllers. By using distributed multi-sensors, the attitude and horizontal position information of mini-quadrotor is obtained. The simulation of the attitude controller is applied with the MATLAB Simulink library. In conclusion, the designed attitude controller can make mini-quadrotor have smooth flight and move in all directions and enable the mini-quadrotor to properly flight.

关键词： Mini-quadrotor Flight attitude control system Calculation Controller

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Online optimization scheduling for scientific workflows with deadline constraint on hybrid clouds

Online optimization scheduling for scientific workflows with...

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作者： Lin, Bing Guo, Wenzhong Lin, Xiuyan School of Mathematics and Computer Science Fuzhou University Fuzhou350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China

The tremendous parallel computing ability of cloud computing encourages investigators to research its drawbacks and advantages on processing large-scale scientific applications such as workflows. The current cloud market is composed of numerous diverse public clouds and a local private cloud, and workflow scheduling is one of the biggest challenges on hybrid clouds due to the highly fragmented cloud market with respect to service provisions, pricing models, and bandwidths. In this paper, we propose an online-scheduling strategy for continuous submitted scientific workflows on hybrid clouds, which aims to complete the deadline-constrained applications as more as possible at a lower price. Firstly, a hierarchical iterative application partition (HIAP) algorithm is proposed to partition the application into a set of dependent tasks. Moreover, many online-scheduling algorithms cooperated with HIAP are presented to finish the workflows with a low average payment. Our strategy takes into account the basic characteristics on hybrid clouds such as bandwidth constraints, data transfer cost and computational cost. Various well-known workflows are used for evaluating the multiple scheduling algorithms and the results show that the MLF_ID approach can achieve a promising performance. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： Data transfer

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Enabling fast recovery from unanticipated data access failure in named data networking 16

Enabling fast recovery from unanticipated data access failur...

引用

11th International Conference on Future Internet Technologies, CFI 2016

作者： Hu, Xiaoyan Gong, Jian School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China Jiangsu Provincial Key Laboratory of Computer Network Technology China

ISBN: (纸本)9781450341813

We show that an aggregated Interest in Named Data Networking (NDN) may fail to retrieve desired data as the Interest sent upstream in advance is recognized as a duplicate one due to its multipath forwarding and dropped by an upstream node. Furthermore, we introduce NDRUDAF, a mechanism based on negative acknowledgement for the router that aggregates the Interests to detect such unanticipated data access failure and assist the requester whose Interest is aggregated fast recovering from the failure. We qualitatively analyze the performance of the NDN with our proposal NDRUDAF and compare its performance with that of the present NDN. NDRUDAF improves the system performance in case of the unanticipated data access failure in terms of data access delay and network resource utilization efficiency at routers. © Copyright 2016 ACM.

关键词： Routers

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Single image super-resolution via a lightweight residual convolutional neural network

arXiv

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arXiv 2017年

作者： Liang, Yudong Yang, Ze Zhang, Kai He, Yihui Wang, Jinjun Zheng, Nanning Key Laboratory of Computational Intelligence Chinese Information Processing of Ministry of Education School of Computer and Information Technology Shanxi University 92 Wucheng Road Taiyuan Shanxi Province030006 China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Harbin Institute of Technology

Recent years have witnessed great success of con-volutional neural network (CNN) for various problems both in low and high level visions. Especially noteworthy is the residual network which was originally proposed to handle high-level vision problems and enjoys several merits. This paper aims to extend the merits of residual network, such as skip connection induced fast training, for a typical low-level vision problem, i.e., single image super-resolution. In general, the two main challenges of existing deep CNN for supper-resolution lie in the gradient exploding/vanishing problem and large numbers of parameters or computational cost as CNN goes deeper. Correspondingly, the skip connections or identity mapping shortcuts are utilized to avoid gradient exploding/vanishing problem. In addition, the skip connections have naturally centered the activation which led to better performance. To tackle with the second problem, a lightweight CNN architecture which has carefully designed width, depth and skip connections was proposed. In particular, a strategy of gradually varying the shape of network has been proposed for residual network. Different residual architectures for image super-resolution have also been compared. Experimental results have demonstrated that the proposed CNN model can not only achieve state-of-the-art PSNR and SSIM results for single image super-resolution but also produce visually pleasant results. This paper has extended the mmm 2017 oral conference paper with a considerable new analyses and more experiments especially from the perspective of centering activations and ensemble behaviors of residual network. Copyright © 2017, The Authors. All rights reserved.

关键词： Optical resolving power

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Architectures and key DSP Techniques of Next Generation Passive Optical Network (PON)

Architectures and Key DSP Techniques of Next Generation Pass...

引用

Optical Fiber Communication Conference, OFC 2016

作者： Li, Fan Luo, Zhibin Yin, Mingzhu Wang, Xiaowu Li, Zhaohui Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems School of Electronics and Information Technology Sun Yat-Sen University Guangzhou510275 China Zhuhai519080 China

Passive optical network (PON) is continuously explored for new architectures and effective DSP techniques to adapt to the next generation communication. In this paper, we summarize our work and discuss the challenges ...

ISBN: (纸本)9781943580071

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