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A visual awareness pathway in cognitive model ABGP

High technology Letters 2016年第4期22卷 395-403页

作者：马刚 Yang Xi Lu Chengxiang Zhang Bo Shi Zhongzhi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 P. R. China University of Chinese Academy of Sciences Beijing 100190 P. R. China

The cognitive model ABGP is a special model for agents,which consists of awareness,beliefs,goals and plans. The ABGP agents obtain the knowledge directly from the natural scenes only through some single preestablished rules like most agent architectures. Inspired by the biological visual cortex( V1) and the higher brain areas perceiving the visual feature,deep convolution neural networks( CNN) are introduced as a visual pathway into ABGP to build a novel visual awareness module. Then a rat-robot maze search simulation platform is constructed to validate that CNN can be used for the awareness module of ABGP. According to the simulation results,the rat-robot implemented by the ABGP with the CNN awareness module reaches the excellent performance of recognizing guideposts,which directly enhances the capability of the communication between the agent and the natural scenes and improves the ability to recognize the real world,which successfully demonstrates that an agent can independently plan its path in terms of the natural scenes.

关键词： ABGP visual cortex(V1) convolution neural networks(CNN) awareness visual pathway

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A Novel Soft Switching Two-Stage Heating Power Supply Topology for Silicon Growth Furnace 35

A Novel Soft Switching Two-Stage Heating Power Supply Topolo...

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第35届中国控制会议

作者： GUO Xin REN Hai-Peng LIU Ding SUO Jun PENG Shu-Tao School of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Lab.of Complex System Control and Intelligent Information Processing Shaanxi Electric Power Research Institute

ISBN: (纸本)9781509009107

Mono-crystalline silicon is widely applied in the photovoltaic and the integrated circuit *** power supply,as the key element of the mono-crystalline silicon growth furnace,plays an important role in the performance of the whole *** this paper,we propose a new kind of two-stage silicon growth furnace heating power supply topology *** first stage three phase rectifier employs the compound active clamp zero voltage soft switching(CACZVS) three-phase power factor correction(PFC) converter to achieve unity power factor and DC bus voltage regulation,and the second stage DC/DC converter employs phase shifted full bridge zero voltage and zero current soft switching converter(FB-ZVZCS) to regulate the output *** with the heating power supply of non-controlled rectifier type or three-phase power factor correction circuit using hard switching,the proposed two-stage converter structure can achieve high power factor,high efficiency and more flexibility of *** simulation results show the correctness of the analysis.

关键词： Silicon Growth Furnace Heating Power Supply CACZVS three phase PFC converter FB-ZVZCS converter

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Emotion detection from natural walking 1

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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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Joint learning of CNN and LSTM for image captioning

Joint learning of CNN and LSTM for image captioning

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2016 Working Notes of Conference and labs of the Evaluation Forum, CLEF 2016

作者： Zhu, Yongqing Li, Xiangyang Li, Xue Sun, Jian Song, Xinhang Jiang, Shuqiang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences No.6 Kexueyuan South Road Zhongguancun Beijing100190 China

In this paper, we describe the details of our methods for the participation in the subtask of the ImageCLEF 2016 Scalable Image Annotation task: Natural Language Caption Generation. The model we used is the combination of a procedure of encoding and a procedure of decoding, which includes a Convolutional neural network(CNN) and a Long Short-Term Memory(LSTM) based Recurrent Neural Network. We first train a model on the MSCOCO dataset and then fine tune the model on difierent target datasets collected by us to get a more suitable model for the natural language caption generation task. Both of the parameters of CNN and LSTM are learned together.

关键词： Long short-term memory

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Variational neural discourse relation recognizer

Variational neural discourse relation recognizer

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2016 Conference on Empirical Methods in Natural Language processing, EMNLP 2016

作者： Zhang, Biao Xiong, Deyi Su, Jinsong Liu, Qun Ji, Rongrong Duan, Hong Zhang, Min Xiamen University Xiamen361005 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China ADAPT Centre School of Computing Dublin City University Ireland Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9781945626258

Implicit discourse relation recognition is a crucial component for automatic discourse-level analysis and nature language understanding. Previous studies exploit discriminative models that are built on either powerful manual features or deep discourse representations. In this paper, instead, we explore generative models and propose a variational neural discourse relation recognizer. We refer to this model as VarNDRR. VarNDRR establishes a directed probabilistic model with a latent continuous variable that generates both a discourse and the relation between the two arguments of the discourse. In order to perform efficient inference and learning, we introduce neural discourse relation models to approximate the prior and posterior distributions of the latent variable, and employ these approximated distributions to optimize a reparameterized variational lower bound. This allows VarNDRR to be trained with standard stochastic gradient methods. Experiments on the benchmark data set show that VarNDRR can achieve comparable results against state-of-the-art baselines without using any manual features. © 2016 Association for Computational Linguistics

关键词： Gradient methods

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Learning to recognize hand-held objects from scratch 17th

Learning to recognize hand-held objects from scratch

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17th Pacific-Rim Conference on Multimedia, PCM 2016

作者： Li, Xue Jiang, Shuqiang Lv, Xiong Chen, Chengpeng College of Information Science and Engineering Shandong University of Science and Technology Qingdao266590 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783319488950

Real-life environments are open-ended and dynamic: unlearned information comes over time. These changes of environments ask for the systems to have the ability of self growth. A reasonable solution is to build an intelligent human-computer interaction system to simulate the mind at birth, and then automatically teach it by human. In this work, we present a hand-held object recognition system which could incrementally enhance its recognition ability from beginning during the interaction with humans. Automatically capturing the images of handheld objects and the voice of users, our system could refer the interacting person as a strong teacher. This allows the system to learn from scratch and to learn new concepts one after another like humans. Although our system is implemented on hand-held recognition scenario, we also implement experiments on ImageNet dataset to validate the effectiveness of our system. Experimental results illustrate its performance. © Springer International Publishing AG 2016.

关键词： Object recognition

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Automatic cross-lingual similarization of dependency grammars for tree-based machine translation

Automatic cross-lingual similarization of dependency grammar...

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2016 Conference on Empirical Methods in Natural Language processing, EMNLP 2016

作者： Jiang, Wenbin Zhang, Wen Xu, Jinan Cai, Rangjia Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China School of Computer and Information Technology Beijing Jiaotong University China Research Center of Tibetan Information Qinghai Normal University China

ISBN: (纸本)9781945626258

Structural isomorphism between languages benefits the performance of cross-lingual applications. We propose an automatic algorithm for cross-lingual similarization of dependency grammars, which automatically learns grammars with high cross-lingual similarity. The algorithm similarizes the annotation styles of the dependency grammars for two languages in the level of classification decisions, and gradually improves the cross-lingual similarity without losing linguistic knowledge resorting to iterative cross-lingual cooperative learning. The dependency grammars given by cross-lingual similarization have much higher cross-lingual similarity while maintaining non-triviality. As applications, the cross-lingually similarized grammars significantly improve the performance of dependency tree-based machine translation. © 2016 Association for Computational Linguistics

关键词： Machine translation

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Hyperspectral light field stereo matching

arXiv

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arXiv 2017年

作者： Zhu, Kang Xue, Yujia Fu, Qiang Kang, Sing Bing Chen, Xilin Yu, Jingyi School of Information Science and Technology ShanghaiTech University Shanghai China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Plex-VR Inc. Shanghai Microsoft Research RedmondWA United States Department of Computer and Information Sciences University of Delaware NewarkDE United States

In this paper, we describe how scene depth can be extracted using a hyperspectral light field capture (H-LF) system. Our H-LF system consists of a 5 × 6 array of cameras, with each camera sampling a different narrow band in the visible spectrum. There are two parts to extracting scene depth. The first part is our novel cross-spectral pairwise matching technique, which involves a new spectral-invariant feature descriptor and its companion matching metric we call bidirectional weighted normalized cross correlation (BWNCC). The second part, namely, H-LF stereo matching, uses a combination of spectral-dependent correspondence and defocus cues that rely on BWNCC. These two new cost terms are integrated into a Markov Random Field (MRF) for disparity estimation. Experiments on synthetic and real H-LF data show that our approach can produce high-quality disparity maps. We also show that these results can be used to produce the complete plenoptic cube in addition to synthesizing all-focus and defocused color images under different sensor spectral responses. Copyright © 2017, The Authors. All rights reserved.

关键词： Cameras

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Viewpoint selection for taking a good photograph of architecture 24

Viewpoint selection for taking a good photograph of architec...

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24th Pacific Conference on Computer Graphics and Applications, Pacific Graphics 2016

作者： He, Jingwu Zhou, Wenzhe Wang, Linbo Zhang, Hongjie Guo, Yanwen National Key Lab for Novel Software Technology Nanjing University NanJing210023 China MOE Key Laboratory of Intelligent Computing and Signal Processing Institute of Media Computing Anhui University HeFei230039 China

ISBN: (纸本)9783038680246

This paper studies the problem of how to choose the viewpoint for taking good photographs for architecture. We achieve this by learning from professional photographs of world famous landmarks that are available in the Internet. Unlike the previous efforts devoted to photo quality assessment which mainly rely on visual features, we show in this paper combining visual features with geometric features computed on the 3D models can result in a more reliable evaluation of viewpoint quality. Specifically, we collect a set of photographs for each of 6 world famous architectures as well as their 3D models from Internet. Viewpoint recovery for images is carried out by an image-model registration process, after which a newly proposed viewpoint clustering strategy is exploited to validate users' viewpoint preference when photographing landmarks. Finally, we extract a number of 2D and 3D features for each image based on multiple visual and geometric cues, and perform viewpoint recommendation by learning from both 2D and 3D features, achieving superior performance over using solely 2D or 3D features. We show the effectiveness of the proposed approach through extensive experiments. © 2016 The Author(s) Eurographics Proceedings © 2016 The Eurographics Association.

关键词： Architecture

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Image projective invariants

arXiv

引用

arXiv 2017年

作者： Li, Erbo Mo, Hanlin Xu, Dong Li, Hua EON Reality Inc IrvineCA92618 United States Key lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Ambry Genetics Aliso ViejoCA92656 United States

In this paper, we propose relative projective differential invariants (RPDIs) which are invariant to general projective transformations. By using RPDIs and the structural frame of integral invariant, projective weighted moment invariants (PIs) can be constructed very easily. It is first proved that a kind of projective invariants exists in terms of weighted integration of images, with relative differential invariants as the weight functions. Then, some simple instances of PIs are given. In order to ensure the stability and discriminability of PIs, we discuss how to calculate partial derivatives of discrete images more accurately. Since the number of pixels in discrete images before and after the geometric transformation may be different, we design the method to normalize the number of pixels. These ways enhance the performance of PIs. Finally, we carry out some experiments based on synthetic and real image datasets. We choose commonly used moment invariants for comparison. The results indicate that PIs have better performance than other moment invariants in image retrieval and classification. With PIs, one can compare the similarity between images under the projective transformation without knowing the parameters of the transformation, which provides a good tool to shape analysis in image processing, computer vision and pattern recognition. Copyright © 2017, The Authors. All rights reserved.

关键词： Object recognition

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