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Research on Network Chinese Pornography Characteristic and Corresponding Filtering System's Model

Research on Network Chinese Pornography Characteristic and C...

引用

International Conference on Internet Technology and Applications (iTAP)

作者： Yu-zhong Peng School of Computer & Information Engineering Key Laboratory of Scientific computing & intelligent information processing Guangxi Teachers Education University Nanning China

At present,the internet pornographic text is in varied forms and changeful, although it is prohibited ever. It severely harms people's mental and physical health development and social stability. There are IP-based,keyword-based and intelligent content analysis filtering system against it today. But they are difficult to deal with manifestations of diversity, changeful, and increasingly concealed porn. In this paper, a in-depth research has done for the appeared characteristics of such undesirable information on our statistical analysis. And based on this characteristics, a new text pre-processing algorithm PA-PTCI is proposed, and a effective model combined with content filtering technology to the current text information filtering pornography problem is designed. The experimental result shows the PA-PTCI algorithm and the model of Chinese pornography text filtering are quite effective.

关键词： Support vector machines information filtering Educational institutions Internet Computational modeling Artificial intelligence

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Preface-GCIS 2013

Proceedings - 2013 4th Global Congress on Intelligent System...

引用

Proceedings - 2013 4th Global Congress on intelligent Systems, GCIS 2013 2013年 xi-xii页

作者： Xu, Li Da Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

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The architecture and implementation of resource space model system

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4th International Conference on Grid and Cooperative computing - GCC 2005

作者： Shi, Peng Xing, Yunpeng Yao, Erlin Wang, Zhen Yuan, Kehua Zhang, Junsheng Wang, Jianzeng Guo, Fei Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate School Chinese Academy of Sciences Beijing China Hunan Knowledge Grid Lab Hunan University of Science and Technology Hunan China

ISBN: (纸本)3540305106

Resource Space Model (RSM) is a semantic model to manage and share heterogeneous resources on the Internet. This paper focuses on the general architecture, physical implementation and application of RSM. The RSM system adopts Client/Server mode for users to utilize resource spaces through the Internet. The resource spaces are designed based on domain knowledge and stored as XML files in the server. The tool 3DBrowser provides a friendly interface with three-dimensional scene to display resource spaces, locate and operate on resources. Based on the architecture and tools, a Dunhuang RSM system has been developed as a collaboration platform to organize and share the resources of Dunhuang Culture Grid. The system provides an efficient resource locating way based on the classification of resources and improves the efficiency of research. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Semantics

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Occlusion-free Face Alignment: Deep Regression Networks Coupled with De-corrupt AutoEncoders

Occlusion-free Face Alignment: Deep Regression Networks Coup...

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IEEE Conference on Computer Vision and Pattern Recognition

作者： Jie Zhang Meina Kan Shiguang Shan Xilin Chen Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology

ISBN: (纸本)9781467388528

Face alignment or facial landmark detection plays an important role in many computer vision applications, e.g., face recognition, facial expression recognition, face animation, etc. However, the performance of face alignment system degenerates severely when occlusions occur. In this work, we propose a novel face alignment method, which cascades several Deep Regression networks coupled with De-corrupt Autoencoders (denoted as DRDA) to explicitly handle partial occlusion problem. Different from the previous works that can only detect occlusions and discard the occluded parts, our proposed de-corrupt autoencoder network can automatically recover the genuine appearance for the occluded parts and the recovered parts can be leveraged together with those non-occluded parts for more accurate alignment. By coupling de-corrupt autoencoders with deep regression networks, a deep alignment model robust to partial occlusions is achieved. Besides, our method can localize occluded regions rather than merely predict whether the landmarks are occluded. Experiments on two challenging occluded face datasets demonstrate that our method significantly outperforms the state-of-the-art methods.

关键词： Occlusion Face Face occluding landmarks Alignment Regression (Psychology) Facial Recognition images computer vision coupling

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Counter designs in quantum-dot cellular automata

Counter designs in quantum-dot cellular automata

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2010 10th IEEE Conference on Nanotechnology, NANO 2010

作者： Kong, Kun Shang, Yun Lu, Ruqian Institute of Mathematics Academy of Mathematics and Systems Science CAS Beijing 100190 China Shanghai Key Lab. of Intelligent Information Processing Fudan University Shanghai 200433 China CAS Key Lab. of IIP Institute of Computing Technology CAS Beijing 100190 China

ISBN: (纸本)9781424470334

In this paper, we present a new method for the design of an n-bit synchronous binary up counter in quantum-dot cellular automata (QCA). This method is based on the JK flip-flop which almost always produces the simplest combinational logic in traditional sequential circuits. We implement a new QCA architecture for the JK flip-flop. Compared to the existing QCA JK flip-flop, the majority gate count, cell count, clock cycle count, and area of our QCA JK flip-flop are reduced by 57.1%, 88.1%, 55.6%, and 92.0%, respectively. Based on our QCA JK flip-flop, a method of extending state cells is proposed to design the QCA layout of the n-bit counter, such that all the clock cycle counts between any two state cells become 1. This feature can ensure that one count just takes one clock cycle, in existing methods, however, one count needs to take n-1 clock cycles. Comparisons indicate that, by applying our method, the hardware requirements (i.e., complexity and area) for QCA n-bit counter can be greatly reduced. ©2010 IEEE.

关键词： Design

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Emotion detection from natural walking 1

引用

2nd International Conference on Human Centered computing, HCC 2016

作者： Cui, Liqing Li, Shun Zhu, Tingshao Beijing100101 China National Computer System Engineering Research Institute of China Beijing100083 China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

ISBN: (数字)9783319318547

ISBN: (纸本)9783319318530

Emotion identification, which aims to determine a person’s affective state automatically, has immense potential value in many areas, such as action tendency, health care, psychological detection and human-computer (robot) interaction. In this paper, we propose a novel method for identifying emotion from natural walking. After obtaining the three-axis acceleration data of wrist and ankle recorded by smartphone, we run a moving average filter window with different length w, then cut actual data into slices. 114 features are extracted from each slice, and Principal Component Analysis (PCA) is used for feature selection. We train SVM, Decision Tree, Multilayerperception, Random Tree and Random Forest classifiers, and compare the accuracy of emotion identification using different datasets (wrist vs. ankle) on different models. Results show that acceleration data from ankle has better performance in emotion identification than wrist. Among these models, SVM has the highest accuracy of 90.31 % for identifying anger vs. neutral, 89.76 % for happy vs. neutral, and 87.10 % for anger vs. happy. The model for identifying anger/neutral/happy yields the best accuracy of 85 %-78 %-78 %. The results show that we could identify people’s emotional states through the gait of walking with high accuracy. © Springer International Publishing Switzerland 2016.

关键词： Smartphones

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Collecting valuable information from fast text streams 8

Collecting valuable information from fast text streams

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8th IFIP International Conference on intelligent information processing, IIP 2014

作者： Qi, Baoyuan Ma, Gang Shi, Zhongzhi Wang, Wei Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100190 China Beijing Lexo Technologies Co. Ltd Beijing100080 China

ISBN: (纸本)9783662449790

It has become a challenging work to collect valuable information from fast text streams. In this work, we propose a method which gains useful information effectively and efficiently. Firstly, we maintain an analyzer based on the Trie structure and the dynamic N-Gram tokenizer;secondly, unlike the traditional search engine principle, we consider the documents as a query by building the indexes for the whole query base. The experimental results show that it has the strong adaption ability, low latency and high quality support for the complex query combination compared with the conventional methods. © IFIP International Federation for information processing 2014.

关键词： Search engines

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Sub-sentence division for tree-based machine translation

Sub-sentence division for tree-based machine translation

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Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and 4th International Joint Conference on Natural Language processing of the AFNLP, ACL-IJCNLP 2009

作者： Xiong, Hao Xu, Wenwen Mi, Haitao Liu, Yang Liu, Qun Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China Key Lab. of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

ISBN: (纸本)9781617382581

Tree-based statistical machine translation models have made significant progress in recent years, especially when replacing 1-best trees with packed forests. However, as the parsing accuracy usually goes down dramatically with the increase of sentence length, translating long sentences often takes long time and only produces degenerate translations. We propose a new method named subsentence division that reduces the decoding time and improves the translation quality for tree-based translation. Our approach divides long sentences into several sub-sentences by exploiting tree structures. Large-scale experiments on the NIST 2008 Chinese-to-English test set show that our approach achieves an absolute improvement of 1.1 BLEU points over the baseline system in 50% less time. © 2009 ACL and AFNLP.

关键词： Machine translation

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A Sentiment Classification Model Based on Syntactic Graph Attention Networks 24

A Sentiment Classification Model Based on Syntactic Graph At...

引用

2024 International Conference on intelligent Education and Computer Technology, IECT 2024

作者： Cheng, Yan Zhou, Ziwei School of Computer Information Engineering Jiangxi Normal University Jiangxi Nanchang330022 China Prov. Key Lab. of Intelligent Information Processing and Affective Computing of Jiangxi Province 330022 China School of Software Jiangxi Normal University 330022 China

ISBN: (纸本)9798400709920

Text Sentiment Classification, a significant task in Natural Language processing, aims to comprehend user needs and expectations by categorizing the sentiments of texts posted on platforms. Despite their utility, existing models for this task do not fully account for the influence of contextual and syntactic text features on sentiment classification. To address these issues, a text sentiment classification model based on syntactic graph attention network is proposed in this study. The model begins by extracting the contextual features of a sentence using BiGRU. It then generates a syntactic graph through a syntactic analyzer, using the contextual features as the node features of the syntactic graph. A syntactic graph attention network is constructed to extract the syntactic features of the syntactic graph. These feature vectors are then input into a softmax function to achieve text sentiment classification. Experimental results indicate that the proposed model outperforms similar models on two public datasets in terms of classification accuracy, thus demonstrating its effectiveness. © 2024 ACM.

关键词： Syntactics

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Urban road network extraction from SAR image

Urban road network extraction from SAR image

引用

MIPPR 2007: Remote Sensing and GIS Data processing and Applications;and Innovative Multispectral Technology and Applications

作者： Cheng, Pengxue Hu, Maolin Lab. of Intelligent Computing and Signal Processing Anhui University Hefei Anhui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469540

In this paper, a technique for the extraction of roads in a high resolution synthetic aperture radar (SAR) image is presented. And a three-step method is developed for the extraction of road network from space borne SAR image: the process of the feature points, road candidate detection and connection. Roads in a high resolution SAR image can be modeled as a homogeneous dark area bounded by two parallel boundaries. Dark areas, which represent the candidate positions for roads, are extracted from the image by a Gaussian probability iteration segmentation. Possible road candidates are further processed using the morphological operators. And the roads are accurately detected by Hough Transform, and the extraction of lines is achieved by searching the peak values in Hough Space. In this process, to detect roads more accurately, post-processing, including noisy dark regions removal and false roads removal is performed. At last, Road candidate connection is carried out hierarchically according to road established models. Finally, the main road network is established from the SAR image successfully. As an example, using the ERS-2SAR image data, automatic detection of main road network in Shanghai Pudong area is presented.

关键词： Feature extraction

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