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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Huanian Liao Wei Wang Shiqin Wang Xin Xu School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

With the development of computer processing, network communication and other modern technology and equipment, the management of ships on the sea surface is becoming increasingly intelligent and automated. It is very important for navigation safety to obtain the behavior trajectory of the target ship. In this paper, a ship tracking method based on twin-neural network is proposed, which is mainly aimed at the deformation, blurring and blocking of ship movement at sea. The complex target ship in Marine environment around the real-time accurate detection of trace this research emphasis, In this paper, the ship tracking module based on correlation filtering method is firstly used to track the target ship, and then use the peak response than for water mist, and other vessels objects shade to what lead to the loss of the early warning, lost ship call based on the twin of the neural network for retrieving the lost ship detection module, continue to use the tracking module tracking target ship, the ship for a long time tracking under complex environment. Experimental results show that the tracking results of this algorithm are more accurate and real-time than those of typical algorithms.

关键词： Target tracking Navigation Filtering Real-time systems Trajectory Marine vehicles Strain

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A Novel Method based on Character Segmentation for Slant Chinese Screen-render Text Detection and recognition

A Novel Method based on Character Segmentation for Slant Chi...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Tianlun Zheng Xiaofeng Wang Xin Yuan Shiqin Wang School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

Screen rendering text has broad application prospects in the fields of medical records, dictionary screen capture, and screen-assisted reading. However, Chinese screen rendering text always has the challenges of small font size and low resolution. Obtaining a screen-rendered text image in a natural scene will have a certain tilt angle. These all pose great challenges for screen text recognition. This paper proposes a method based on character segmentation. In order to correct the tilt of the text image, a lightweight image text correction method is proposed. In order to obtain better character segmentation accuracy in extreme environments, a Gaussian extremum removal module is designed. Drawing on HCCR-GoogLeNet, a simple and efficient network architecture is designed for character recognition. Finally, this paper will slant text correction, horizontal text line detection, character segmentation, and character recognition to construct a complete network architecture to be applied to the screen rendering text recognition process scheme in natural scenes. The character recognition model was evaluated on ICDAR2013 and the homemade screen rendering dataset, and both achieved good results.

关键词： Image segmentation Text recognition Network architecture Rendering (computer graphics) Optical imaging Character recognition Optical character recognition software

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On the computability of idea creation of creative computing 2nd

On the computability of idea creation of creative computing

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2nd International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2018

作者： Lai, Junjiang Zhang, Fuquan School of Mathematics and Data Sciences Minjiang University Fuzhou China School of Software Beijing Institute of Technology Beijing China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (纸本)9783030045845

Creative computing is an very important emerging technology in nowadays and computability is the necessary of researching creative computing. We demonstrate computability of idea creation of creative computing using the recursion function theory. The algorithm complexity for idea creation is also obtained. © Springer Nature Switzerland AG 2019.

关键词： Computational complexity

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Opinion Dynamics Incorporating Higher-Order Interactions

Opinion Dynamics Incorporating Higher-Order Interactions

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IEEE International Conference on Data Mining (ICDM)

作者： Zuobai Zhang Wanyue Xu Zhongzhi Zhang Guanrong Chen School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China Department of Electrical Engineering City University of Hong Kong Hong Kong SAR China

ISBN: (数字)9781728183169

ISBN: (纸本)9781728183176

The issue of opinion sharing and formation has received considerable attention in the academic literature, and a few models have been proposed to study this problem. However, existing models are limited to the interactions among nearest neighbors, ignoring those second, third, and higher-order neighbors, despite the fact that higher-order interactions occur frequently in real social networks. In this paper, we develop a new model for opinion dynamics by incorporating long-range interactions based on higher-order random walks. We prove that the model converges to a fixed opinion vector, which may differ greatly from those models without higher-order interactions. Since direct computation of the equilibrium opinions is computationally expensive, which involves the operations of huge-scale matrix multiplication and inversion, we design a theoretically convergence-guaranteed estimation algorithm that approximates the equilibrium opinion vector nearly linearly in both space and time with respect to the number of edges in the graph. We conduct extensive experiments on various social networks, demonstrating that the new algorithm is both highly efficient and effective.

关键词： Social networking (online) Computational modeling Heuristic algorithms Estimation Approximation algorithms Graph theory Sparse matrices

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LogoDet-3K: A large-scale image dataset for logo detection

arXiv

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arXiv 2020年

作者： Wang, Jing Min, Weiqing Hou, Sujuan Ma, Shengnan Zheng, Yuanjie Jiang, Shuqiang School of Information Science and Engineering Shandong Normal University Shandong250358 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

Logo detection has been gaining considerable attention because of its wide range of applications in the multimedia field, such as copyright infringement detection, brand visibility monitoring, and product brand management on social media. In this paper, we introduce LogoDet-3K, the largest logo detection dataset with full annotation, which has 3,000 logo categories, about 200,000 manually annotated logo objects and 158,652 images. LogoDet-3K creates a more challenging benchmark for logo detection, for its higher comprehensive coverage and wider variety in both logo categories and annotated objects compared with existing datasets. We describe the collection and annotation process of our dataset, analyze its scale and diversity in comparison to other datasets for logo detection. We further propose a strong baseline method Logo-Yolo, which incorporates Focal loss and CIoU loss into the state-of-the-art YOLOv3 framework for large-scale logo detection. Logo-Yolo can solve the problems of multi-scale objects, logo sample imbalance and inconsistent bounding-box regression. It obtains about 4% improvement on the average performance compared with YOLOv3, and greater improvements compared with reported several deep detection models on LogoDet-3K. The evaluations on other three existing datasets further verify the effectiveness of our method, and demonstrate better generalization ability of LogoDet-3K on logo detection and retrieval tasks. The LogoDet-3K dataset is used to promote large-scale logo-related research and it can be found at https://***/Wangjing1551/LogoDet-3K-Dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Large dataset

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SCHWARZ TYPE LEMMAS AND THEIR APPLICATIONS IN BANACH SPACES

arXiv

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arXiv 2021年

作者： Chen, Shaolin Hamada, Hidetaka Ponnusamy, Saminathan Vijayakumar, Ramakrishnan College of Mathematics and Statistics Hengyang Normal University Hunan Hengyang421002 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application 421002 China Faculty of Science and Engineering Kyushu Sangyo University 3-1 Matsukadai 2-Chome Higashi-Ku Fukuoka813-8503 Japan Department of Mathematics Indian Institute of Technology Madras Chennai600 036 India

The main purpose of this paper is to develop some methods to investigate the Schwarz type lemmas of holomorphic mappings and pluriharmonic mappings in Banach spaces. Initially, we extend the classical Schwarz lemmas of holomorphic mappings to Banach spaces, and then we apply these extensions to establish a sharp Bloch type theorem for pluriharmonic mappings on homogeneous unit balls of Cn and to obtain some sharp boundary Schwarz type lemmas for holomorphic mappings in Banach spaces. Furthermore, we improve and generalize the classical Schwarz lemmas of planar harmonic mappings into the sharp forms of Banach spaces, and present some applications to sharp boundary Schwarz type lemmas for pluriharmonic mappings in Banach spaces. Additionally, using a relatively simple method of proof, we prove some sharp Schwarz-Pick type estimates of pluriharmonic mappings in JB∗-triples, and the obtained results provide the improvements and generalizations of the corresponding results in [9].MSC Codes 32A30, 32U05, 32K05 Copyright © 2021, The Authors. All rights reserved.

关键词： Banach spaces

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CUGE: A Chinese Language Understanding and Generation Evaluation Benchmark

arXiv

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arXiv 2021年

作者： Yao, Yuan Dong, Qingxiu Guan, Jian Cao, Boxi Zhang, Zhengyan Xiao, Chaojun Wang, Xiaozhi Qi, Fanchao Bao, Junwei Nie, Jinran Zeng, Zheni Gu, Yuxian Zhou, Kun Huang, Xuancheng Li, Wenhao Ren, Shuhuai Lu, Jinliang Xu, Chengqiang Wang, Huadong Zeng, Guoyang Zhou, Zile Zhang, Jiajun Li, Juanzi Huang, Minlie Yan, Rui He, Xiaodong Wan, Xiaojun Zhao, Xin Sun, Xu Liu, Yang Liu, Zhiyuan Han, Xianpei Yang, Erhong Sui, Zhifang Sun, Maosong Department of Computer Science and Technology Tsinghua University China MOE Key Lab of Computational Linguistics School of EECS Peking University China Institute of Software Chinese Academy of Sciences China JD AI Research Beijing China School of Information Science Beijing Language and Culture University China School of Information Renmin University of China China National Laboratory of Pattern Recognition Institute of Automation CAS China Gaoling School of Artificial Intelligence Renmin University of China China Wangxuan Institute of Computer Technology Peking University Beijing Academy of Artificial Intelligence China

Realizing general-purpose language intelligence has been a longstanding goal for natural language processing, where standard evaluation benchmarks play a fundamental and guiding role. We argue that for general-purpose language intelligence evaluation, the benchmark itself needs to be comprehensive and systematic. To this end, we propose CUGE, a Chinese Language Understanding and Generation Evaluation benchmark with the following features: (1) Hierarchical benchmark framework, where datasets are principally selected and organized with a language capability-task-dataset hierarchy. (2) Multilevel scoring strategy, where different levels of model performance are provided based on the hierarchical framework. To facilitate CUGE, we provide a public leaderboard that can be customized to support flexible model judging criteria. Evaluation results on representative pre-trained language models indicate ample room for improvement towards general-purpose language intelligence. CUGE is publicly available at ***. Copyright © 2021, The Authors. All rights reserved.

关键词： Natural language processing systems

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Moving objects elimination towards enhanced dynamic SLAM fusing LiDAR and mmW-radar

Moving objects elimination towards enhanced dynamic SLAM fus...

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IEEE MTT-S International Conference on Microwaves for intelligent Mobility (ICMIM)

作者： Xiangwei Dang Xingdong Liang Yanlei Li Zheng Rong National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728167558

ISBN: (纸本)9781728167565

Robust and accurate localization and mapping are essential for autonomous driving. The traditional SLAM methods generally work under the assumption that the environment is static, while in dynamic environment the performance will be degenerate. In this paper, we propose an efficient and effective method to eliminate the influence of dynamic environment on SLAM by fusing LiDAR and mmW-radar, which significantly improves the robustness and accuracy of localization and mapping. The method fully utilizes the advantages of different measurement characteristics of two sensors, efficient moving object detection based on Doppler effect by radar and accurate object segmentation and localization by LiDAR, to remove the moving objects and uses the resulting filtered point cloud as the input of SLAM towards enhanced performance. The proposed approach is evaluated through experiments in various real world scenarios, and the results demonstrate the effectiveness of the method to improve the robustness and accuracy of SLAM in dynamic environments.

关键词： Simultaneous localization and mapping Laser radar Three-dimensional displays Radar measurements Radar detection Sensor phenomena and characterization Robustness

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An ontology-supported inquiry learning technique

Journal of Network Intelligence

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Journal of Network Intelligence 2021年第1期6卷 16-28页

作者： Xue, Xingsi Zhang, Jie Yang, Chaofan Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No.33 Xuefu South Road University Town Minhou Fuzhou Fujian350118 China School of Computer Science and Engineering Yulin Normal University No.299 Education Middle Road Yulin City Guanxi Province537000 China School of Computer Science and Mathematics Intelligent Information Processing Research Center Fujian University of Technology No.33 Xueyuan Road University Town Minhou Fuzhou Fujian350118 China Guangxi Key Laboratory of Automatic Detecting Technology and Instruments Guilin University of Electronic Technology No.1 Jinji Road Guilin Guangxi541004 China

Although Inquiry-based Learning (IBL) offers compelling opportunities for the engineering education, one of the challenges to the implementation of it is that the learner always lacks of the background knowledge. To provide him with the necessary knowledge when making the inquiry, this paper proposes an Ontology Supported Inquiry Learning technique (OSIL), which works on the basis of two ontologies, i.e. curriculum ontology and the learner’s ontology. The experimental results show that the constructed curriculum ontology and learner ontology is of high-quality, and the answers recommended by OSIL almost perfectly match with the true answers. From the experimental results, we can see that it is a feasible way of using the software engineering and prototype evolution method to construct the curriculum and learner ontology, and the individual inquiry based on two ontologies is able to provide the learners with high-quality personalized services. © 2021, Taiwan Ubiquitous information. All rights reserved.

关键词： Curricula

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On fuzzy alternate control systems

On fuzzy alternate control systems

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Babatunde Oluwaseun Onasanya Yuming Feng Wei Zhang Shiping Wen Ning Tang Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing China University of Ibadan Ibadan Nigeria Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology Chongqing Three Gorges University Wanzhou Chongqing China School of Computer Science and Engineering Chongqing Three Gorges University Wanzhou Chongqing China Australian AI Institute Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China

Some researchers have worked on intermittent control and alternate control. In both cases, the choice of the control was a constant quantity. But, in real life, this situation is hard to come by for the reason that control may vary with time and circumstances owing to machine or human errors or both. Hence is the need to employ a method in which the control matrix is rather uncertain as is obtainable in real life. In this paper, we consider a more general model of both intermittent and alternate control which allows the control matrix to be fuzzy (uncertain). It turns out that both the classical intermittent and classical alternate controls are recovered in this mode.

关键词： Adaptation models Computational modeling Control systems Computational intelligence

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