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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Fang Zhou Jun Yang Guangcai Sun Jiajia Zhang School of Computer and Information Hefei University of Technology Hefei China National Key Lab of Radar Signal Processing Xidian University Xi'an China Key Laboratory of Aperture Array and Space Application East China Research Institute of Electronic Engineering Hefei China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

The small satellite SAR has received increasing attention due to its flexibility and low cost. But limited by the data transmission technology, real-time transmission of a large amount of raw data generated by the spaceborne spotlight SAR can hardly be achieved. Meanwhile, the azimuth bandwidth of the spotlight mode is larger than the PRF, resulting in aliasing of the azimuth spectrum. Based on these, this paper proposes a real-time scheme for small satellite SAR with spotlight mode. The method can solve the problem of data transmission and eliminate spectrum overlap in Doppler domain by means of sub-aperture processing. The modified range migration algorithm (RMA) is used to perform range compression and range cell migration compensation (RCMC) on sub-aperture data. Then dechirp in the azimuth time domain is applied to obtain the low-resolution complex image focused in the range time-azimuth frequency domain. Finally, all theected onto a grid image with azimuth interval matching the azimuth full-resolution to complete image fusion.

关键词： Azimuth Spaceborne radar Real-time systems Synthetic aperture radar Doppler effect Imaging Bandwidth

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3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video

arXiv

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arXiv 2021年

作者： Wang, Guangming Zhong, Jiquan Zhao, Shijie Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Department of Engineering Mechanics Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Depth and ego-motion estimations are essential for the localization and navigation of autonomous robots and autonomous driving. Recent studies make it possible to learn the per-pixel depth and ego-motion from the unlabeled monocular video. A novel unsupervised training framework is proposed with 3D hierarchical refinement and augmentation using explicit 3D geometry. In this framework, the depth and pose estimations are hierarchically and mutually coupled to refine the estimated pose layer by layer. The intermediate view image is proposed and synthesized by warping the pixels in an image with the estimated depth and coarse pose. Then, the residual pose transformation can be estimated from the new view image and the image of the adjacent frame to refine the coarse pose. The iterative refinement is implemented in a differentiable manner in this paper, making the whole framework optimized uniformly. Meanwhile, a new image augmentation method is proposed for the pose estimation by synthesizing a new view image, which creatively augments the pose in 3D space but gets a new augmented 2D image. The experiments on KITTI demonstrate that our depth estimation achieves state-of-the-art performance and even surpasses recent approaches that utilize other auxiliary tasks. Our visual odometry outperforms all recent unsupervised monocular learning-based methods and achieves competitive performance to the geometry-based method, ORB-SLAM2 with back-end optimization. Copyright © 2021, The Authors. All rights reserved.

关键词： Robots

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Preliminary ideas for intelligent recognition paths of anomie behaviors among MOOC learners 2nd

Preliminary ideas for intelligent recognition paths of anomi...

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

作者： Liu, Shutang Zhang, Fuquan Jiang, Chunfen Academic Affairs Office Minjiang University Fuzhou University Town Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China School of Foreign Language Minjiang University Fuzhou University Town Fuzhou350108 China

ISBN: (纸本)9783030045845

This paper identifies the characteristics of anomie behaviors of MOOC learners through the cluster analysis of those anomie behaviors, and finds out the initial paths of intelligent recognition through online analysis of the background data characteristics of these anomie behaviors. The paper also suggests that these identification paths are not difficult to find, but there are still some profound reasons why many MOOC companies have not adopted those paths so far. © Springer Nature Switzerland AG 2019.

关键词： Cluster analysis

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Control-oriented fault detection of solid oxide fuel cell system unknown input on fuel supply

Control-oriented fault detection of solid oxide fuel cell sy...

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作者： Wu, Xiao-long Xu, Yuan-wu Xue, Tao Shuai, Junchao Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China Wuhan Industrial Economic Development Research Center Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China

As the solid oxide fuel cell (SOFC) system work environment is a high-temperature environment for a long time, it is difficult to obtain the SOFC stack internal state change directly. When the fault occurs, it is difficult to determine where the fault occurs. Moreover, the existing literature ignores the impact of faults, which creates many problems for SOFC system control. Therefore, a state observer-based fault detection method, which is used to detect the input flow sensor fault and the fuel input fault, is proposed. Their advantage is that they do not need data processing. To realize the fault detection, the observer is used to track the changes of SOFC stack chamber temperature. To obtain the observer estimation parameter, an approach from the actual stack structure parameters is employed to approximate the observer parameters. The results show the proposed fault detect method can judge fuel input fault type quickly and shield the disturbances signals from the sensor effectively. The proposed method also can be used to other operating points or air input fault. © 2018 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd

关键词： Fault detection

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A Novel Economical Design of Multistage Decimators for Low Latency Audio Applications

A Novel Economical Design of Multistage Decimators for Low L...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Wei Hu Chongwei Zheng Yonghao Wang Jing Liu Cen Chen Zeng Zeng College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Digital Media Technology lab Birmingham City University Birmingham UK Institute for Infocomm Research Singapore

ISBN: (纸本)9781728176499;9781728176505

The oversampling sigma-delta analog-to-digital converter (ADC) is widely used in digital audio systems for its low hardware cost and high precision. The digital filter part of the ADC is the primary source of the silicon and power cost. In this work, we proposed an economical multistage decimation filter architecture to meet the requirements of commercial ADC specifications with a further novel multi-objective optimization strategy. We took group delay and computational cost as objective functions and used annealing algorithm to readjust the stopband attenuation, stopband edge and passband ripple of each filter. Our multistage architecture combines cascaded integrator-comb (CIC) filters, compensating filters and equiripple finite impulse response (FIR) filters at the different stages to balance the overall performance. The experimental results showed that our design approach worked with multi-objective optimization strategy could achieve low group delay with lower cost compared to traditional designs.

关键词： Sigma-delta modulation Finite impulse response filters computer architecture Filtering algorithms Attenuation Linear programming Silicon

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Efficient Design of Hybrid Half-band Multi-stage Filter Based on Simulated Annealing Algorithm

Efficient Design of Hybrid Half-band Multi-stage Filter Base...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Wei Hu Chongwei Zheng Yonghao Wang Jin Zhang Cen Chen Zeng Zeng College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Digital Media Technology lab Birmingham City University Birmingham UK Institute for Infocomm Research Singapore

ISBN: (纸本)9781728176499;9781728176505

The oversampling sigma-delta based analog-to-digital converter and digital-to-analog converter (ADC/DAC) architecture can achieve high resolution with effective low hardware cost. It normally introduces latency due to the internal high-performance finite impulse response (FIR) digital filters. In this work, we proposed a novel approach to reduce latency and accurately predict latency caused by the group delay. We propose a filter structure applied to ADC, using the infinite impulse response (IIR) filter and half-band filter (HBF) to construct a hybrid half-band filter (HHBF). A novel modified Simulated Annealing (SA) algorithm is proposed to optimize the best distribution of passband ripple and transition bandwidth that is suitable for audio processing with low latency and computation cost. The experiments show that hybrid HBF proposed in this paper improves the efficiency of the filter in terms of filter cost and group delay comparing to traditional design.

关键词： Sigma-delta modulation Finite impulse response filters IIR filters Simulated annealing Bandwidth Filtering algorithms Prediction algorithms

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CloudBrain-ReconAI: A Cloud Computing Platform for MRI Reconstruction and Radiologists’ Image Quality Evaluation

arXiv

引用

arXiv 2022年

作者： Zhou, Yirong Qian, Chen Li, Jiayu Wang, Zi Hu, Yu Qu, Biao Zhu, Liuhong Zhou, Jianjun Kang, Taishan Lin, Jianzhong Hong, Qing Dong, Jiyang Guo, Di Qu, Xiaobo The Department of Electronic Science Biomedical Intelligent Cloud R&D Center Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance National Institute for Data Science in Health and Medicine Xiamen University Xiamen361102 China The Department of Instrumental and Electrical Engineering Xiamen University Xiamen361005 China Fudan University Xiamen361015 China The Department of Radiology Zhongshan Hospital Xiamen University School of Medicine Xiamen University Xiamen361004 China The China Mobile Group Xiamen361000 China The School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China

Efficient collaboration between engineers and radiologists is important for image reconstruction algorithm development and image quality evaluation in magnetic resonance imaging (MRI). Here, we develop CloudBrain-ReconAI, an online cloud computing platform, for algorithm deployment, fast and blind reader study. This platform supports online image reconstruction using state-of-the-art artificial intelligence and compressed sensing algorithms with applications for fast imaging (Cartesian and non-Cartesian sampling) and high-resolution diffusion imaging. Through visiting the website, radiologists can easily score and mark images. Then, automatic statistical analysis will be provided. CloudBrain-ReconAI is now open accessed at https://***/*** and will be continually improved to serve the MRI research community. Copyright © 2022, The Authors. All rights reserved.

关键词： Cloud platforms

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STS MICCAI 2023 Challenge: Grand challenge on 2D and 3D semi-supervised tooth segmentation

arXiv

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arXiv 2024年

作者： Wang, Yaqi Zhang, Yifan Chen, Xiaodiao Wang, Shuai Qian, Dahong Ye, Fan Xu, Feng Zhang, Hongyuan Zhang, Qianni Wu, Chengyu Li, Yunxiang Cui, Weiwei Luo, Shan Wang, Chengkai Li, Tianhao Liu, Yi Feng, Xiang Zhou, Huiyu Liu, Dongyun Wang, Qixuan Lin, Zhouhao Song, Wei Li, Yuanlin Wang, Bing Wang, Chunshi Chen, Qiupu Li, Mingqian College of Media Engineering Communication University of Zhejiang Hangzhou China State Key Laboratory of Oral Diseases National Clinical Research Center for Oral Diseases West China Hospital of Stomatology Sichuan University Chengdu China Lishui University School of Medicine Hangzhou Geriatric Stomatology Hospital Hangzhou Dental Hospital Group Hangzhou China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China School of Cyberspace Hangzhou Dianzi University Hangzhou China Suzhou Research Institute of Shandong University Suzhou China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China School of Biomedical Engineering Medical School Shenzhen University Shenzhen China School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Department of Mechanical Electrical and Information Engineering Shandong University Weihai China School of Management Hangzhou Dianzi University Hangzhou China Department of Stomatology Sichuan Provincial People's Hospital University of Electronic Science and Technology of China Chengdu China School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Zeta Technology Co. Ltd. No. 1158 Zhangdong Road Pudong New Area Shanghai China China Academy of Information and Communications Technology Beijing China HangZhou Dianzi University Xiasha Higher Education Zone Hangzhou China Southeast University Sipailou Xuanwu District Nanjing China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Shanghai Jiao Tong University Shanghai China School of Computer Science and Technology Changchun University of Science and Technology Changchun China School of Artificial Intelligence Guilin University of Electronic Technology Guilin China University of Science and Technology of China Hefei China Hefei Institutes of Physical Science Chinese Academy of Sciences No. 350 Shushan

computer-aided design (CAD) tools are increasingly popular in modern dental practice, particularly for treatment planning or comprehensive prognosis evaluation. In particular, the 2D panoramic X-ray image efficiently detects invisible caries, impacted teeth and supernumerary teeth in children, while the 3D dental cone beam computed tomography (CBCT) is widely used in orthodontics and endodontics due to its low radiation dose. However, there is no open-access 2D public dataset for children's teeth and no open 3D dental CBCT dataset, which limits the development of automatic algorithms for segmenting teeth and analyzing diseases. The Semi-supervised Teeth Segmentation (STS) Challenge, a pioneering event in tooth segmentation, was held as a part of the MICCAI 2023 ToothFairy Workshop on the Alibaba Tianchi platform. This challenge aims to investigate effective semi-supervised tooth segmentation algorithms to advance the field of dentistry. In this challenge, we provide two modalities including the 2D panoramic X-ray images and the 3D CBCT tooth volumes. In Task 1, the goal was to segment tooth regions in panoramic X-ray images of both adult and pediatric teeth. Task 2 involved segmenting tooth sections using CBCT volumes. Limited labelled images with mostly unlabelled ones were provided in this challenge prompt using semi-supervised algorithms for training. In the preliminary round, the challenge received registration and result submission by 434 teams, with 64 advancing to the final round. This paper summarizes the diverse methods employed by the top-ranking teams in the STS MICCAI 2023 Challenge. Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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Generative Adversarial Networks with Joint Distribution Moment Matching

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Journal of the Operations Research Society of China 2019年第4期7卷 579-597页

作者： Yi-Ying Zhang Chao-Min Shen Hao Feng Preston Thomas Fletcher Gui-Xu Zhang Department of Computer Science East China Normal UniversityShanghai 200062China Shanghai Key Laboratory of Multidimensional Information Processing East China Normal UniversityShanghai 200062China Westlake Institute for Brain-Like Science and Technology Hangzhou 310027China Didi Chuxing Science and Technology Co.Ltd. Beijing 100193China Department of Electrical and Computer Engineering University of VirginiaCharlottesvilleVA 22904USA

Generative adversarial networks(GANs)have shown impressive power in the field of machine *** GANs have focused on unsupervised learning *** recent years,conditional GANs that can generate data with labels have been proposed in semi-supervised learning and have achieved better image quality than traditional *** GANs,however,generally only minimize the difference between marginal distributions of real and generated data,neglecting the difference with respect to each class of the *** address this challenge,we propose the GAN with joint distribution moment matching(JDMM-GAN)for matching the joint distribution based on maximum mean discrepancy,which minimizes the differences of both the marginal and conditional *** learning procedure is iteratively conducted by the stochastic gradient descent and *** evaluate JDMM-GAN on several benchmark datasets,including MNIST,CIFAR-10 and the Extended Yale *** with the state-of-the-art GANs,JDMM-GAN generates more realistic images and achieves the best inception score for CIFAR-10 dataset.

关键词： Generative Adversarial Networks Joint Distribution Moment Matching Maximum mean discrepancy

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The (t, k)-diagnosability of shuffle-cubes under PMC model

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International Journal of computer Mathematics: computer Systems Theory 2019年第2期4卷 111-126页

作者： Li, Jin'e Lin, Limei Huang, Yanze Yu, Hui Chen, Riqing Faculty of Computer Science and Information Technology Digital Fujian Institute of Big Data for Agriculture and Forestry Fujian Agriculture and Forestry University Fuzhou China College of Mathematics and Computer Science Fujian Normal University Fuzhou China School of Mathematics and Physics Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China

System-level diagnosis aims to identify faulty processors in a multiprocessor system by analysing the test results among the processors. The (Formula presented.) -diagnosis requires to identify and repair at least k faulty processors in each iteration until that all t faulty processors are found where (Formula presented.). It is one of the most important system-level diagnosis strategies. Meanwhile, shuffle-cube (Formula presented.), a variant of hypercube for multiprocessor systems, has some good combinatorial properties and fault-tolerant properties. In this paper, we propose a (Formula presented.) -diagnosis algorithm for n-dimensional shuffle-cube (Formula presented.), and then we show that (Formula presented.) is (Formula presented.) -diagnosable. Moreover, we prove that the proposed algorithm can identify at most (Formula presented.) faulty nodes under the condition that it can identify at least n faulty nodes in each iteration. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

关键词： aggregate Diagnosability fault diagnosis reliability shuffle-cube

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