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Progress and Challenge of Artificial Intelligence

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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Challenge-aware U-net for breast lesion segmentation in ultrasound images

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Pattern Recognition 2025年 168卷

作者： Dengdi Sun Changxu Dong Yuchen Yan Bo Jiang Yayang Duan Zhengzheng Tu Chaoxue Zhang Key Laboratory of Intelligent Computing & Signal Processing (ICSP) Ministry of Education School of Artificial Intelligence Anhui University China Institute of Artificial Intelligence Hefei Comprehensive National Science Center China Anhui Provincial Key Laboratory of Multimodal Cognitive Computing School of Computer Science and Technology Anhui University China Department of Ultrasound the First Affiliated Hospital of Anhui Medical University China

Deep learning methods can enhance the efficiency of tumor segmentation in breast ultrasound (BUS) images. However, noise interference, small tumors, and blurred boundaries can reduce segmentation accuracy. We design a three-branch challenge-aware U-net (CAU-net) to address these main challenges in BUS images. Our CAU-net extracts the features from three challenge-aware encoders in parallel first. Secondly, we propose an adaptive aggregation layer (AAL) to merge the multi-scale features of three challenging branches, enabling the network to adaptively handle different breast lesion samples with these main challenges. To further enhance the accuracy of segmentation, we introduce the graph reasoning module (GRM) to the network to model the correlation between the channels of the features and acquire the global information in the features. The result of our experiment on two datasets demonstrates the superiority of CAU-net over the advanced medical image segmentation methods. Our code can be downloaded from https://***/tzz-ahu .

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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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Detection of Impurity and Bubble Defects in Tire X-Ray Image Based on Improved Extremum Filter and Locally Adaptive-threshold Binaryzation

Detection of Impurity and Bubble Defects in Tire X-Ray Image...

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2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018

作者： Zheng, Xiunan Ding, Jianpei Pang, Zengzhi Li, Jinping Shandong Provincial Key Laboratory of Network Based Intelligent Computing China Shandong College University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-year China School of Information Science and Engineering University of Jinan China

ISBN: (纸本)9781728105512

The manufacturing technology of all steel radial tire is complex. Some defects will inevitably appear in the tire due to the complex production process. Impurity and bubble are two typical kinds of defects in the tire. In this study, a unified detection of impurity and bubble defects in tire X-ray images is proposed by means of improved extremum filter and improved locally adaptive-threshold binaryzation. Firstly, the tire image is divided into cords and background by extremum filter. Secondly, an improved locally adaptive-threshold binaryzation is used to separate defects from the background. Finally, image denoising and marking are processed. In the experiment, we tested the proposed approach by using 280 tires with various types of defects from a tire factory. For the detection of clear and blur impurities and clear bubbles, the precision of our method can reach 97%, and the recall is 95.7%. It is to be noted that the proposed method can only be used to detect those two defects in sidewall and shoulder of the tire which we refer as the carcass. © 2018 IEEE.

关键词： Radial tires

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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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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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Polynomial stacked-attention network for nationality classification

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Frontiers of Computer Science 2022年第4期16卷 215-217页

作者： Kunyan Li Jie Zhang Shiguang Shan Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing100190China University of Chinese Academy of Sciences Beijing100049China

1Introduction In recent years,nationality and region inference has atracted more and_more *** anthropological researches indicate that human faces are influenced by genes,and other external factors,e.g-,geographical environment[1].This relevance provides possible solutions for geographical area inference by ***,it remains a challenging task due to the tiny differences on faces for various countries,which is even hard for human beings to tell.

关键词： Polynomial s. network

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A High Efficiency Wireless Charging Antenna with Embedded Magnetic Core of Segmented Two-turns Loop 7

A High Efficiency Wireless Charging Antenna with Embedded Ma...

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2017 7th IEEE International Symposium on Microwave, Antenna, Propagation, and EMC Technologies

作者： Yong Song Kaihong Song Xianliang Wu Zhixiang Huang Xiaojing Kuang Yanyan Zhu Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Electronic Information Engineering Hefei Normal University

ISBN: (纸本)9781509059300;9781509059294

In this paper, a high-efficiency transceiver antenna with embedded high magnetic permeability core of segmented two-turns loop is presented. It can be applied in the implanted device of monitoring human body neural with a wireless charging and bi-directional data transmission. The whole structure of transmitting and receiving antenna is basically similar;the difference is that receiving antenna is composed of double-sided ring and an embedded magnetic core at central position, transmitting antenna can be realized by dividing ring and welding fixed-value capacitor at corresponding position. The efficiency of wireless energy transfer has been improved and the specific absorption rate value has been reducing by simulation optimization. Compared with conventional loop antenna, our transmission efficiency has been exceed doubled and average SAR reduced by approximately 52%, when the distance of wireless transmission is 5 mm. Finally, we fabricate a conventional loop antenna, a segmented loop antenna with embedded magnetic core and a kind of mixed liquid that have the same dielectric parameters with skin at 402 MHz. Experiences show that actual results of transmission efficiency are in good agreement with the simulation results.

关键词： Implantable Wireless charging Segment Magnetic core Bi-directional data transmission

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