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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： C.L. Xu D.K. Qu C.D. Wu Z. Z. Li P. Di J. L. Song D. J. Tian Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China SIASUN Robot & Automation Co. Ltd Shenyang Liaoning China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

The autonomous navigation algorithm of ORB-SLAM and its problems were studied and improved in this paper. ORB-SLAM is a fast and accurate navigation algorithm using visual image feature to calculate the position and attitude. But when there are few characteristic points in the unknown environment, ORB-SLAM algorithm falls into the situation of infinite solution, local localization error occurs, and global mapping is interrupted. Researchers have proposed an IMU/Vision fusion algorithm that neatly solves this problem. In this process, the calibration between inertial components and camera is very important, the desirable outcome of which will slow down the divergence speed of autonomous navigation system and further improve the system accuracy. In this paper, the algorithm of calibration between IMU/OE and Stereo vision exploiting the improved recursive least squares with forgetting factor (RFF) method is proposed, and then the algorithm is verified by experimental datas. The results show that the accuracy and the stability of the DR navigation system are improved, which can be applied to IMU/Vision integrated navigation system and enhance robustness of navigation system.

关键词： Simultaneous localization and mapping Dead reckoning Acceleration Autonomous robots Visualization

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A Cascade Dual-Decoder Model for Joint Entity and Relation Extraction

arXiv

引用

arXiv 2021年

作者： Cheng, Jian Zhang, Tian Zhang, Shuang Ren, Huimin Yu, Guo Zhang, Xiliang Gao, Shangce Ma, Lianbo The Research Institute of Mine Artificial Intelligence in Chinese Institute of Coal Science State Key Laboratory of Intelligent Coal Mining and Strata Control Tiandi Science and Technology Co. Ltd. Beijing100013 China The College of Software Northeastern University Shenyang China The Institute of Intelligent Manufacturing Nanjing Tech University Nanjing211816 China The School of Intelligent Manufacturing and Control Engineering Shanghai Polytechnic University Shanghai China The Faculty of Engineering University of Toyama Toyama-shi930-8555 Japan Foshan Graduate School of Innovation Northeastern University Foshan China

In knowledge graph construction, a challenging issue is how to extract complex (e.g., overlapping) entities and relationships from a small amount of unstructured historical data. The traditional pipeline methods are to divide the extraction into two separate subtasks, which misses the potential interaction between the two subtasks and may lead to error propagation. In this work, we propose an effective cascade dual-decoder method to extract overlapping relational triples, which includes a text-specific relation decoder and a relation-corresponded entity decoder. Our approach is straightforward and it includes a text-specific relation decoder and a relation-corresponded entity decoder. The text-specific relation decoder detects relations from a sentence at the text level. That is, it does this according to the semantic information of the whole sentence. For each extracted relation, which is with trainable embedding, the relation-corresponded entity decoder detects the corresponding head and tail entities using a span-based tagging scheme. In this way, the overlapping triple problem can be tackled naturally. We conducted experiments on a real-world open-pit mine dataset and two public datasets to verify the method's generalizability. The experimental results demonstrate the effectiveness and competitiveness of our proposed method and achieve better F1 scores under strict evaluation metrics. Our implementation is available at https://***/prastunlp/DualDec. Copyright © 2021, The Authors. All rights reserved.

关键词： Decoding

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Saliency detection based region extraction for pedestrian detection system with thermal imageries

Saliency detection based region extraction for pedestrian de...

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作者： Xu, Ming Yu, Xiaosheng Wu, Chengdong Chen, Dongyue College of Information Science and Engineering Northeastern University Shenyang110-819 China Faculty of Robot Science and Engineering Northeastern University Shenyang110-819 China

A robust pedestrian detection approach in thermal infrared imageries for an all-day surveillance is proposed. Firstly, the candidate regions which are likely to contain pedestrians are extracted based on a saliency detection method. Then a deep convolutional network with a multi-task loss is constructed to recognize the pedestrians. The experimental results show the superiority of the proposed approach in pedestrian detection. © 2018 The Institute of Electronics, Information and Communication Engineers.

关键词： Convolution

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Dense Stereo Matching Optimization Algorithm based on Image Segmentation and ORB Gravitational Field

Dense Stereo Matching Optimization Algorithm based on Image ...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Chenglong Xu Chengdong Wu Daokui Qu Daji Tian Jilai Song Xiaofeng Wang Faculty of Robot Science and Engineering Northeastern University SIASUN Robot & Automation Co. Ltd Shenyang China Faculty of Robot Science and Engineering Northeastern University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences SIASUN Robot & Automation Co. Ltd Shenyang China SIASUN Robot & Automation Co. Ltd Shenyang China

ISBN: (纸本)9781728137933

This paper reference the data field ideology from Cognitive Physics, presents a novel dense stereo matching method, in which the cost metric of robustness to texture-less and occluded regions. In order to correct the mismatching and constrain error propagation in cost aggregation, Oriented FAST and Rotated BRIEF (ORB) gravitational field is introduced to the traditional matching cost metrics on the basis of previous studies. Strong feature points can be regarded as correct depth estimation points, which can be used as the center to establish gravitational field for effective energy transmission of each pixel. Then the combined matching cost metrics are aggregated exploiting image segmentation structure. Finally, the experiments on the stereo images of datasets and ours prove that the proposed algorithm has better performance in matching accuracy and robustness.

关键词： Measurement robots Automation Robustness Smoothing methods Matched filters Image segmentation

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Bimodal Face Recognition Based on Liveness Detection

Bimodal Face Recognition Based on Liveness Detection

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Wenlong Gao Kai Jia Fang Xu Fengshan Zou Jilai Song Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning China SIASUN Robot & Automation Co. Ltd. Shenyang Liaoning China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

In this paper, we proposed a three-dimensional face recognition method based on liveness detection. Firstly, one liveness detection method based on the three-dimensional structure of the face was proposed. According to the face feature point localization algorithm combined with the RANSAC fitting algorithm and the SVM model training prediction method, the depth information was used to judge the reality of the face, and the detection of the photo and video attacker behavior were solved. In this paper, the traditional loss function and the new central loss function were used as the supervised signals in the face recognition process. We used model fine-tuning to train two independent convolutional neural networks, and then we used the score fusion approach to fuse facial feature matching. Finally, we evaluated the Eurecom and Vap public test sets based on the way of actual application. The experimental results showed that compared with the traditional in liveness detection, our algorithm made use of the advantages of three-dimensional information to realize the judgment of face reality, and the algorithm had better accuracy in three-dimensional face recognition section.

关键词： Face Face recognition Face detection Feature extraction Image color analysis Fitting Training

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A Nonlinear Control Method for Asymmetric Hydraulic Cylinder Based on Incremental Digital Valve Control

A Nonlinear Control Method for Asymmetric Hydraulic Cylinder...

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International Conference on Intelligent Computing, Automation and Systems (ICICAS)

作者： Shenghao Zhou Depeng Dong Lijin Fang School of Mechanical Engineering and Automation Northeastern University Shenyang China School of Science and Engineering Robot Northeastern University Shenyang China

ISBN: (数字)9781728161068

ISBN: (纸本)9781728161075

In this paper, an output feedback nonlinear control is proposed for an asymmetric hydraulic cylinder based on incremental digital valve control system with unmodeled disturbances and parametric uncertainties. It's composed of a high gain state observer (HGO) and a dynamic surface sliding mode controller. The high gain state observer is designed to estimate the unmeasured system states. The dynamic surface sliding mode controller is designed to stabilize the closed-loop system. The proposed controller accounts for not only the unmodeled disturbances, but also the parametric uncertainties. In theory, the controller guarantees a prescribed tracking transient performance and final tracking accuracy even in the presence of unmodeled disturbances and parametric uncertainties. The effectiveness of the proposed method is verified via simulation.

关键词： adaptive control closed loop systems control system synthesis digital control feedback hydraulic systems nonlinear control systems observers robust control uncertain systems valves variable structure systems Closed loop systems Variable structure systems Hydraulic system control system synthesis Observers Nonlinear control systems uncertain systems Robust control adaptive control VALVE GATE Numerical controls Feedback HYDRAULIC CYLINDERS nonlinear control

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A Propagation Condition Identification and Non-Line of Sight Error Mitigation Algorithm in Wireless Sensor Network

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Journal of Physics: Conference Series 2020年第1期1453卷

作者： Hao chu Siyi Lian Hao Yang Rongguang Wu Faculty of Robot Science and Engineering Northeastern University Shenyang Liaoning 110000 China

Node localization is one of key technologies in wireless sensor networks (WSN). In practice, the occlusion of obstacles often leads to large non-line-of-sight (NLOS) error. Therefore, the misidentification of LOS (line-of-sight)/NLOS conditions can seriously reduce the accuracy of localization algorithms in WSN. In this paper, we propose a novel localization algorithm based on hypothesis testing method, which combines the NLOS condition identification algorithm and the extended Kalman filter method to mitigate the NLOS error. Moreover, we introduce the false alarm rate fa to fuse the estimated values in the LOS/NLOS condition to obtain more accurate results. The simulations demonstrate that the proposed algorithm can effectively reduce the influence of NLOS error and improve the localization accuracy.

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Prediction of a Heusler alloy with switchable metal-to-half-metal behavior

arXiv

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arXiv 2021年

作者： Buchelnikov, Vasiliy D. Sokolovskiy, Vladimir V. Miroshkina, Olga N. Baigutlin, Danil R. Zagrebin, Mikhail A. Barbiellini, Bernardo Lähderanta, Erkki Faculty of Physics Chelyabinsk State University Chelyabinsk454001 Russia National University of Science and Technology "MISiS" Moscow119049 Russia Department of Physics School of Engineering Science LUT University LappeenrantaFI-53850 Finland University of Duisburg-Essen Duisburg47048 Germany National Research South Ural State University Chelyabinsk454080 Russia Physics Department Northeastern University BostonMA02115 United States

We propose a ferromagnetic Heusler alloy that can switch between a metal and a half-metal. This effect can provide tunable spintronics properties. Using the density functional theory (DFT) with reliable implementations of the electron correlation effects, we find Mn2ScSi total energy curves consisting of distinct branches with a very small energy difference. The phase at low lattice crystal volume is a low magnetic half-metallic state while the phase at high lattice crystal volume is a high magnetic metallic state. We suggest that the transition between half-metallic and metallic states can be triggered by a triaxial contraction/expansion of the crystal lattice or by an external magnetic field if we assume that the lattice is cubic and remains cubic under expansion/contraction. However, the phase at high volume can also undergo an austenite-martensite phase transition because of the presence of Jahn-Teller active 3d electrons on the Mn atoms. Copyright © 2021, The Authors. All rights reserved.

关键词： Density functional theory

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Towards a cloud performance research repository 2

Towards a cloud performance research repository

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2nd IEEE/ACM International Workshop on Establishing a Community-Wide Infrastructure for Architecture-Based Software engineering, ECASE 2019

作者： Gorton, Ian Rajagopal, Shravanthi Liu, Yan Khoury College of Computer Sciences Northeastern University Seattle Campus SeattleWA United States Faculty of Engineering and Computer Science Concordia University MontrealCA Canada

ISBN: (纸本)9781728122410

In this paper, we describe our goals and initial efforts to create a community wide infrastructure for empirical research on cloud systems performance modeling. Performance analysis and prediction has long been an active research area in software engineering. Recent work in this area has focused on cloud-deployed applications that are characteristic of an ever growing percentage of modern software systems. The drivers for cloud deployment are improved quality attributes such as performance and scalability, access to advanced cloud-based technologies, and reduced costs. In terms of research, efforts include optimizing resource utilization for cloud systems under various workloads, understanding the influence on performance of various cloud-based infrastructure components, and architecture design trade-offs. To support these efforts and energize the creation of new models and methods, our goal is to build a repository that stores both raw and analyzed performance results from a collection of benchmarks characterizing different types of cloud applications. This data can be used by researchers to explore, calibrate and validate higher fidelity performance models and identify new research directions. Results from benchmarks can also help architects understand the effects of their architectural decisions and cloud services selections and configurations on application quality attributes. © 2019 IEEE.

关键词： Scalability

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A novel method for quality assessment of image stitching based on the gabor filtering

A novel method for quality assessment of image stitching bas...

引用

2018 IEEE International Conference on Information and Automation, ICIA 2018

作者： Zhu, Shangdong Zhang, Yunzhou Tao, Liang Liu, Tongbo Liu, Yanjiao Faculty of Robot Science and Engineering Northeastern University Shenyang China College of Information Science and Engineering Northeastern University Shenyang China School of Computer and Communication Engineering University of Science and Techonology of Beijing Beijing China

ISBN: (纸本)9781538680698

Predicting perceptual quality is the main goal of the Image Quality Assessment (IQA) and image stitching is an exceedingly important branch in the field of computer vision, especially for panoramic maps. Nevertheless, there are few existing objective IQA methods suitable for the quality assessment of stitched images. In order to better reflect people's subjective feelings and verify the validity of stitching and fusion algorithms in the reverse direction, an overall IQA framework is proposed in this paper based on characteristics of the image stitching and the Human Vision System (HVS), named Difference Information Sensing Model (DISM). The presented method first uses the Gabor filtering to detect the edge of the image, then constructs the difference image, and finally forms the assessment model combined with the Just Noticeable Difference (JND) threshold. Meanwhile, an improved edge detection algorithm is proposed, which filters out more high-frequency information and preserves the edge of the image skeleton. Furthermore, we developed an edge difference image generation algorithm which can obtain the butt seam, dislocations and brightness differences in the process of stitching. Experimental results demonstrate the efficacy of the proposed method outperforming prior work for quality assessment of image stitching. © 2018 IEEE.

关键词： Edge detection

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