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< Page ,Total 205 >
Robust point cloud registration based on both hard and soft assignments EI Scopus
期刊论文 | 2019 , 110 , 202-208 | Optics and Laser Technology
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Abstract :

For the registration of partially overlapping point clouds, this paper proposes an effective approach based on both the hard and soft assignments. Given two initially posed clouds, it firstly establishes the forward correspondence for each point in the data shape and calculates the value of a binary variable, which indicates whether this point correspondence is located in the overlapping areas or not. Then, it establishes the bilateral correspondence and computes bidirectional distances for each point in the overlapping areas. Based on the ratio of bidirectional distances, the exponential function is selected and utilized to calculate the probability value, which indicates the reliability of the point correspondence. Subsequently, both the values of hard and soft assignments are embedded into the proposed objective function for registration of partially overlapping point clouds, which then be solved by the proposed variant of ICP algorithm to obtain the optimal rigid transformation. The proposed approach can achieve good registration of point clouds, even when their overlap percentage is low. Experimental results tested on public datasets illustrate its superiority over previous approaches on accuracy and robustness. © 2018 Elsevier Ltd

Keyword :

Bidirectional distances Hard assignment Overlap percentage Point cloud registration Soft assignments

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GB/T 7714 Zhu, Jihua , Jin, Congcong , Jiang, Zutao et al. Robust point cloud registration based on both hard and soft assignments [J]. | Optics and Laser Technology , 2019 , 110 : 202-208 .
MLA Zhu, Jihua et al. "Robust point cloud registration based on both hard and soft assignments" . | Optics and Laser Technology 110 (2019) : 202-208 .
APA Zhu, Jihua , Jin, Congcong , Jiang, Zutao , Xu, Siyu , Xu, Minmin , Pang, Shanmin . Robust point cloud registration based on both hard and soft assignments . | Optics and Laser Technology , 2019 , 110 , 202-208 .
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Maximum correntropy square-root cubature Kalman filter with application to SINS/GPS integrated systems. EI PubMed Scopus
期刊论文 | 2018 , 80 , 195-202 | ISA transactions
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Abstract :

For a nonlinear system, the cubature Kalman filter (CKF) and its square-root version are useful methods to solve the state estimation problems, and both can obtain good performance in Gaussian noises. However, their performances often degrade significantly in the face of non-Gaussian noises, particularly when the measurements are contaminated by some heavy-tailed impulsive noises. By utilizing the maximum correntropy criterion (MCC) to improve the robust performance instead of traditional minimum mean square error (MMSE) criterion, a new square-root nonlinear filter is proposed in this study, named as the maximum correntropy square-root cubature Kalman filter (MCSCKF). The new filter not only retains the advantage of square-root cubature Kalman filter (SCKF), but also exhibits robust performance against heavy-tailed non-Gaussian noises. A judgment condition that avoids numerical problem is also given. The results of two illustrative examples, especially the SINS/GPS integrated systems, demonstrate the desirable performance of the proposed filter.

Keyword :

Square-root cubature Kalman filter (SCKF) Maximum correntropy criterion (MCC) SINS/GPS integrated systems

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GB/T 7714 Liu Xi , Qu Hua , Zhao Jihong et al. Maximum correntropy square-root cubature Kalman filter with application to SINS/GPS integrated systems. [J]. | ISA transactions , 2018 , 80 : 195-202 .
MLA Liu Xi et al. "Maximum correntropy square-root cubature Kalman filter with application to SINS/GPS integrated systems." . | ISA transactions 80 (2018) : 195-202 .
APA Liu Xi , Qu Hua , Zhao Jihong , Yue Pengcheng . Maximum correntropy square-root cubature Kalman filter with application to SINS/GPS integrated systems. . | ISA transactions , 2018 , 80 , 195-202 .
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PSNet: prostate segmentation on MRI based on a convolutional neural network. PubMed Scopus
期刊论文 | 2018 , 5 (2) , 021208 | Journal of medical imaging
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Abstract :

Automatic segmentation of the prostate on magnetic resonance images (MRI) has many applications in prostate cancer diagnosis and therapy. We proposed a deep fully convolutional neural network (CNN) to segment the prostate automatically. Our deep CNN model is trained end-to-end in a single learning stage, which uses prostate MRI and the corresponding ground truths as inputs. The learned CNN model can be used to make an inference for pixel-wise segmentation. Experiments were performed on three data sets, which contain prostate MRI of 140 patients. The proposed CNN model of prostate segmentation (PSNet) obtained a mean Dice similarity coefficient of [Formula: see text] as compared to the manually labeled ground truth. Experimental results show that the proposed model could yield satisfactory segmentation of the prostate on MRI.

Keyword :

deep learning magnetic resonance imaging convolutional neural network prostate segmentation

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GB/T 7714 Tian Zhiqiang , Liu Lizhi , Zhang Zhenfeng et al. PSNet: prostate segmentation on MRI based on a convolutional neural network. [J]. | Journal of medical imaging , 2018 , 5 (2) : 021208 .
MLA Tian Zhiqiang et al. "PSNet: prostate segmentation on MRI based on a convolutional neural network." . | Journal of medical imaging 5 . 2 (2018) : 021208 .
APA Tian Zhiqiang , Liu Lizhi , Zhang Zhenfeng , Fei Baowei . PSNet: prostate segmentation on MRI based on a convolutional neural network. . | Journal of medical imaging , 2018 , 5 (2) , 021208 .
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Hierarchical and Parallel Pipelined Heterogeneous SoC for Embedded Vision Processing EI SCIE Scopus
期刊论文 | 2018 , 28 (6) , 1434-1444 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
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Abstract :

Object recognition is widely used in vision computing for various applications. Traditional CPU and application specific integrated circuit for vision computing cannot provide high performance and enough flexibility, which limit the use of vision systems. In this paper, a hierarchical and parallel pipelined heterogeneous chip for object recognition is proposed to achieve high flexibility, high performance, and area efficiency. In addition, a reformulation of 3D position estimation is proposed. The method uses single precision to achieve the short computing time and accuracy requirement. The hardware resource is small. Application-specific components, such as connected component information extractor and information extraction accelerator, are designed for high performance. Reconfiguration processors and application-specific instruction set processor are introduced to improve flexibility. These components are connected to hierarchical parallel buses. The chip is fabricated in 180-nm CMOS technology and occupies 72.25 mm(2) with 1.09M bits on-chip memory. It delivers 204 GOPS + 665M FLOPS operations. The results show that this hierarchical and parallel pipelined heterogeneous chip is suitable for embedded vision systems.

Keyword :

3D position estimation application-specific instruction set processor (ASIP) system on chip (SoC) reconfigurable embedded vision system

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GB/T 7714 Zhang, Bin , Zhao, Chen , Mei, Kuizhi et al. Hierarchical and Parallel Pipelined Heterogeneous SoC for Embedded Vision Processing [J]. | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY , 2018 , 28 (6) : 1434-1444 .
MLA Zhang, Bin et al. "Hierarchical and Parallel Pipelined Heterogeneous SoC for Embedded Vision Processing" . | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 28 . 6 (2018) : 1434-1444 .
APA Zhang, Bin , Zhao, Chen , Mei, Kuizhi , Zhao, Jizhong , Zheng, Nanning . Hierarchical and Parallel Pipelined Heterogeneous SoC for Embedded Vision Processing . | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY , 2018 , 28 (6) , 1434-1444 .
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Joint Hypergraph Learning for Tag-Based Image Retrieval EI SCIE Scopus
期刊论文 | 2018 , 27 (9) , 4437-4451 | IEEE TRANSACTIONS ON IMAGE PROCESSING
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Abstract :

As the image sharing websites like Flickr become more and more popular, extensive scholars concentrate on tag-based image retrieval. It is one of the important ways to find images contributed by social users. In this research field, tag information and diverse visual features have been investigated. However, most existing methods use these visual features separately or sequentially. In this paper, we propose a global and local visual features fusion approach to learn the relevance of images by hypergraph approach. A hypergraph is constructed first by utilizing global, local visual features, and tag information. Then, we propose a pseudo-relevance feedback mechanism to obtain the pseudo-positive images. Finally, with the hypergraph and pseudo relevance feedback, we adopt the hypergraph learning algorithm to calculate the relevance score of each image to the query. Experimental results demonstrate the effectiveness of the proposed approach.

Keyword :

visual feature hypergraph pseudo relevance feedback Tag-based image retrieval feature fusion

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GB/T 7714 Wang, Yaxiong , Zhu, Li , Qian, Xueming et al. Joint Hypergraph Learning for Tag-Based Image Retrieval [J]. | IEEE TRANSACTIONS ON IMAGE PROCESSING , 2018 , 27 (9) : 4437-4451 .
MLA Wang, Yaxiong et al. "Joint Hypergraph Learning for Tag-Based Image Retrieval" . | IEEE TRANSACTIONS ON IMAGE PROCESSING 27 . 9 (2018) : 4437-4451 .
APA Wang, Yaxiong , Zhu, Li , Qian, Xueming , Han, Junwei . Joint Hypergraph Learning for Tag-Based Image Retrieval . | IEEE TRANSACTIONS ON IMAGE PROCESSING , 2018 , 27 (9) , 4437-4451 .
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Hardware Implementation of Reconfigurable Separable Convolution EI CPCI-S Scopus
会议论文 | 2018 , 232-237 | 17th IEEE-Computer-Society Annual Symposium on VLSI (ISVLSI)
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Abstract :

Convolution operations occupy large amounts of computation resource in convolutional neural networks (CNNs). Separable convolution can greatly reduce computational complexity. Unfortunately, most trained kernels in CNNs are not separable. In this paper, least squares approach is applied to decompose a non-separable 2D kernel into two 1D kernels. A reconfigurable convolutional architecture is proposed to convert a 2D convolution into 1D convolution in convolutional layers. Moreover, a denoising CNN is mapped to the proposed convolution architecture. Experimental results show that the hardware architecture can restore a 1280x 720 image in 0.83s, which achieves an 8.4x speed-up over GPU implementation. Verification experiments demonstrate that our approach and hardware architecture can drastically reduce the computational complexity in convolution operations without sacrificing the performance.

Keyword :

hardware implementation reconfigurable architecture separable convolution convolutional neural networks

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GB/T 7714 Rao, Lei , Zhang, Bin , Zhao, Jizhong . Hardware Implementation of Reconfigurable Separable Convolution [C] . 2018 : 232-237 .
MLA Rao, Lei et al. "Hardware Implementation of Reconfigurable Separable Convolution" . (2018) : 232-237 .
APA Rao, Lei , Zhang, Bin , Zhao, Jizhong . Hardware Implementation of Reconfigurable Separable Convolution . (2018) : 232-237 .
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A high energy physical metadata directory structure based on RAMCloud EI Scopus
会议论文 | 2018 , 2018-January , 301-304 | 14th Web Information Systems and Applications Conference, WISA 2017
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Abstract :

In recent years, with the large-scale growth of the high-energy physics experimental data, the performance of metadata retrieval based on disk storage has been gradually reduced, which can not meet the retrieval performance requirements of EB-level high-energy physics experimental metadata. To solve this problem, a method of converting traditional directory structure storage into RAMCloud storage is proposed. The core idea of this method is to use Key-Value non-relational database to re-design the traditional directory tree, separate directory structure and directory node content, and add a secondary index for parent directory, which can give full play to Key-Value retrieval and memory storage advantages, improve search efficiency. Through the implementation of the test, showed that the method has a better performance. Compared to the storage based on Mysql, the retrieval time drops significantly in the case of increased data. © 2017 IEEE.

Keyword :

Directory structure Directory trees Kay-Value Non-Relational Databases RAMCloud Retrieval performance Retrieval time Search efficiency

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GB/T 7714 Hou, Zhiqi , Hou, Di , Qi, Yong . A high energy physical metadata directory structure based on RAMCloud [C] . 2018 : 301-304 .
MLA Hou, Zhiqi et al. "A high energy physical metadata directory structure based on RAMCloud" . (2018) : 301-304 .
APA Hou, Zhiqi , Hou, Di , Qi, Yong . A high energy physical metadata directory structure based on RAMCloud . (2018) : 301-304 .
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Design and practice of arduino experiments for "e&I" oriented education EI Scopus
会议论文 | 2018 , 21-26 | 2018 ACM Turing Celebration Conference - China, TURC 2018
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Abstract :

The Internet is playing an essential role in current society and economy. Chinese government recently kicked off a reform endeavor of massive Entrepreneurship and Innovation (E&I) over the Internet. In conjunction with the "Internet +" based development in both the society and economy, it is necessary to strengthen the students' ability of E&I in undergraduate education. In this paper, we present a new design and practice of Arduino experiments in an undergraduate computer course, which implements the E&I oriented education reform. We conduct a survey among the students and the results show the effectiveness of our experimental designs. © 2018 Association for Computing Machinery.

Keyword :

Arduino Chinese Government Design and practices Education reforms Undergraduate education

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GB/T 7714 Zhang, Xiaobin , Wu, Ning , Saleem, Sajid et al. Design and practice of arduino experiments for "e&I" oriented education [C] . 2018 : 21-26 .
MLA Zhang, Xiaobin et al. "Design and practice of arduino experiments for "e&I" oriented education" . (2018) : 21-26 .
APA Zhang, Xiaobin , Wu, Ning , Saleem, Sajid , Cui, Shuning , Wang, Zhi . Design and practice of arduino experiments for "e&I" oriented education . (2018) : 21-26 .
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Robust and high capacity watermarking for image based on DWT-SVD and CNN EI Scopus
会议论文 | 2018 , 1233-1237 | 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018
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Abstract :

Digital watermarking technology is of great importance to protect the copyright of the owners and authenticate the security of the media. As digital images are vulnerable to some common attacks during transmission, it is very necessary to design a watermarking algorithm which can resist all kinds of common attacks. Nowadays, most of the watermarking algorithms published rely much on the locations of the pixels for watermark embedding, which results in less robustness. And some algorithms took some measures to increase the ability to resist attacks, but the measures taken limited the algorithm in watermark embedding capacity. In this paper, a robust watermarking algorithm based on convolution neural network (CNN) is proposed. We introduce discrete wavelet transform (DWT) technology and singular value decomposition (SVD) technology, to achieve the embedding process of watermark. The network is established in the spatial domain based on the pixels' relationships of watermark, host image and watermarked image. After that, The pixels of the watermarked image are lightly modified with the network. In addition, some attacks are taken to the watermarked image. Simulation shows that proposed algorithm has good performance, the watermark extracted can be clearly identified. © 2018 IEEE.

Keyword :

Convolution neural network Convolutional neural network Digital image watermarking Digital watermarking technologies Robust watermarking Watermark embedding Watermarked images Watermarking algorithms

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GB/T 7714 Zheng, Wenbo , Mo, Shaocong , Jin, Xin et al. Robust and high capacity watermarking for image based on DWT-SVD and CNN [C] . 2018 : 1233-1237 .
MLA Zheng, Wenbo et al. "Robust and high capacity watermarking for image based on DWT-SVD and CNN" . (2018) : 1233-1237 .
APA Zheng, Wenbo , Mo, Shaocong , Jin, Xin , Qu, Yili , Deng, Fei , Shuai, Jia et al. Robust and high capacity watermarking for image based on DWT-SVD and CNN . (2018) : 1233-1237 .
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Image super-resolution reconstruction algorithm based on Bayesian theory EI Scopus
会议论文 | 2018 , 1934-1938 | 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018
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Abstract :

The Bayesian theory provides a new solution to image super-resolution reconstruction. In view of the poor robustness to noise and motion estimation in the vast majority of superresolution reconstruction algorithms. In this paper, we propose an image super-resolution reconstruction algorithm based on Bayesian representation. In the proposed algorithm, uncharted super-resolution images, motion parameters and unknown model parameters are utilized for modeling in a hierarchical Bayesian framework. We adopt degenerate distribution to derive the estimation of analytic solutions and applied the solutions to the super-resolution reconstruction which also enables the proposed algorithm robust to noises. The experimental results show that the proposed image super-resolution reconstruction algorithm based on Bayesian representation can achieve higher (or similar) performance than the state of-the-art methods. © 2018 IEEE.

Keyword :

Bayesian Hierarchical bayesian Hyper-parameter Image super-resolution reconstruction Similarity Sparse images State-of-the-art methods Super resolution reconstruction

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GB/T 7714 Zheng, Wenbo , Deng, Fei , Mo, Shaocong et al. Image super-resolution reconstruction algorithm based on Bayesian theory [C] . 2018 : 1934-1938 .
MLA Zheng, Wenbo et al. "Image super-resolution reconstruction algorithm based on Bayesian theory" . (2018) : 1934-1938 .
APA Zheng, Wenbo , Deng, Fei , Mo, Shaocong , Jin, Xin , Qu, Yili , Zhou, Jiangwei et al. Image super-resolution reconstruction algorithm based on Bayesian theory . (2018) : 1934-1938 .
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