检索结果-内蒙古大学图书馆

Proceedings of the 32nd International Conference on Neural information processing systems

作者： Tianyu He Xu Tan Yingce Xia Di He Tao Qin Zhibo Chen Tie-Yan Liu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Microsoft Research Key Laboratory of Machine Perception MOE School of EECS Peking University

Neural Machine Translation (NMT) has achieved remarkable progress with the quick evolvement of model structures. In this paper, we propose the concept of layer-wise coordination for NMT, which explicitly coordinates the learning of hidden representations of the encoder and decoder together layer by layer, gradually from low level to high level. Specifically, we design a layer-wise attention and mixed attention mechanism, and further share the parameters of each layer between the encoder and decoder to regularize and coordinate the learning. Experiments show that combined with the state-of-the-art Transformer model, layer-wise coordination achieves improvements on three IWSLT and two WMT translation tasks. More specifically, our method achieves 34.43 and 29.01 BLEU score on WMT16 English-Romanian and WMT14 English-German tasks, outperforming the Transformer baseline.

关键词：

来源：评论

学校读者我要写书评

暂无评论

HIGH RESOLUTION SAR IMAGE CLASSIFICATION WITH DEEPER CONVOLUTIONAL NEURAL NETWORK

HIGH RESOLUTION SAR IMAGE CLASSIFICATION WITH DEEPER CONVOLU...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： Yue Zhang Xian Sun Hao Sun Zequn Zhang Wenhui Diao Kun Fu Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing China Institute of Electronic Chinese Academy of Sciences Beijing China

Deeper architectures are proven to be beneficial for the classification performance obviously in computer vision field. Inspired by this, deep CNNs are expected to make progress in the SAR target classification problem as well. However, it is hard to train deeper CNNs for SAR images. Such CNNs have millions of parameters to be determined in the network (for example the VGGNet has more than 130 million parameters), hence large-scale dataset is indispensable when training a deep CNN. But there is no large-scale annotated SAR target dataset, and data acquisition and annotation is much more costly for SAR images. With inadequate data, the network is easy to be overfitting. Several methods based on deep learning have been proposed for SAR image classifications, but they cannot get rid of the aforementioned data limitation of labelled SAR images. To solve this problem, this paper proposes a microarchitecture called CompressUnit (CU). With CU, we design a deeper CNN. Compared with the network with the fewest parameters for SAR image classification in literature so far, our network is 2X deeper with only about 10% of parameters. In this way, we get a deeper network with much fewer parameters. This network is easier to be trained with limited SAR data and is more likely to get rid of overfitting.

关键词： Deeper CNN SAR images CompressUnit

来源：评论

学校读者我要写书评

暂无评论

Approach of SAR images simulations for target interpretations

Approach of SAR images simulations for target interpretation...

引用

IET International Radar Conference 2018, IRC 2018

作者： Zhang, Yueting Ding, Chibiao Lei, Bin Li, Fangfang Qiu, Xiaolan Institute of Electronics Chinese Academy of Sciences Beijing China Key Laboratory of Geo-spatial Information Processing and Application System Technology Chinese Academy of Sciences Zhongguancun Beiyitiao No. 9 Beijing China University of Chinese Academy of Sciences Yuquan Road No. 19 Beijing China

In this work, a novel approach for the simulation of synthetic aperture radar (SAR) images is proposed. Also, this approach aims to interpret the mechanisms of the dominated scattering centres in the SAR image. An attributed model based on typical structures is used to characterise the 3D geometry of the targets. The physical optics and the geometry optics are used to calculate the main scattering mechanisms of the specified typical structures. Also, based on scattering properties and the imaging process, the simulation approach is set up. The experiments based on the Terra-SAR data of an airplane are implemented to test the validity of the simulation. The work presented would be useful for SAR automatic target recognition. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Physical optics

来源：评论

学校读者我要写书评

暂无评论

Networked predictive control based on the round-trip delay 34

Networked predictive control based on the round-trip delay

引用

34th Chinese Control Conference, CCC 2015

作者： Binglin, Wang Yu, Kang Baoqun, Yin Zhen, Xie Department of Automation University of Science and Technology of China Hefei Anhui China School of Electrical Engineering and Automation Hefei University of Technology Hefei Anhui China State Key Laboratory of Fire Science University of Science and Technology of China Key Laboratory of Technology in Geo-Satial Information Processing and Application System Chinese Academy of Science Hefei Anhui China

ISBN: (纸本)9789881563897

Network predictive control is effectively in dealing with time-delay, data dropouts, packets disorders of Network Control system. This paper studies the stochastic stability of a affine nonlinear system within random time delay. The system controller is consist of a control prediction generator (CPG) at the controller side and a network delay compensator (NDC) at the plant side. Different from the previous literatures that model the random delay of the feedback channel and the forward channel as Markov chain respectively, the model in this paper is based on the round-trip delay, which making the predictive control process more concise but without losing generality. Then, this paper gives the necessary and sufficient conditions for stochastic stability of the closed-loop system. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method. © 2015 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Affine system Markov Process Predictive Control Stochastic Stability

来源：评论

学校读者我要写书评

暂无评论

The application of the alternate descent conditional gradient method in tomographic SAR off-grid imaging

The application of the alternate descent conditional gradien...

引用

IET International Radar Conference (IRC 2023)

作者： Mingxiao Shao Cikang Su Zhe Zhang Bingchen Zhang Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing People's Republic of China Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology and Suzhou Aerospace Information Research Institute Suzhou Jiangsu People's Republic of China

ISBN: (数字)9781837240982

Compressed sensing (CS) technology has been applied to topographic synthetic aperture radar (TomoSAR) imaging due to the sparsity of elevation signals. The traditional CS algorithms discretize the elevation into many grids and assume that the scatterers are located on grids, therefore, the accuracy of the traditional CS algorithms is limited by the off-grid effect. Although there are currently methods to address the off-grid effect, such as atomic norm minimization (ANM), its application is limited by the baseline distribution form of TomoSAR, which only applies to uniformly observed scenarios. Alternating Descent Conditional Gradient (ADCG) has been applied in many fields as a gridless imaging algorithm. In this paper, we apply ADCG to TomoSAR imaging for the first time, achieving the reconstruction of non-uniform baseline observation scenes. The effectiveness of ADCG in TomoSAR imaging was verified by comparing it with iterative soft thresholding (IST) and orthogonal matching pursuit (OMP) through simulation experiments.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cascaded Regression Tracking: Towards Online Hard Distractor Discrimination

arXiv

引用

arXiv 2020年

作者： Wang, Ning Zhou, Wengang Tian, Qi Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei China Huawei Noah’s Ark Laboratory

Visual tracking can be easily disturbed by similar surrounding objects. Such objects as hard distractors, even though being the minority among negative samples, increase the risk of target drift and model corruption, which deserve additional attention in online tracking and model update. To enhance the tracking robustness, in this paper, we propose a cascaded regression tracker with two sequential stages. In the first stage, we filter out abundant easily-identified negative candidates via an efficient convolutional regression. In the second stage, a discrete sampling based ridge regression is designed to double-check the remaining ambiguous hard samples, which serves as an alternative of fully-connected layers and benefits from the closed-form solver for efficient learning. During the model update, we utilize the hard negative mining technique and an adaptive ridge regression scheme to improve the discrimination capability of the second-stage regressor. Extensive experiments are conducted on 11 challenging tracking benchmarks including OTB-2013, OTB-2015, VOT2018, VOT2019, UAV123, Temple-Color, NfS, TrackingNet, LaSOT, UAV20L, and OxUvA. The proposed method achieves state-of-the-art performance on prevalent benchmarks, while running in a real-time speed. Copyright © 2020, The Authors. All rights reserved.

关键词： Regression analysis

来源：评论

学校读者我要写书评

暂无评论

Optimal sensor schedule under limited resources for two linear dynamical systems in wireless sensor network

Optimal sensor schedule under limited resources for two line...

引用

Asian Control Conference

作者： Jie Wang Jiahu Qin Qichao Ma Yu Kang Department of Automation University of Science and Technology of China Hefei China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509015740;9781509015733

In this paper, we consider the problem of sensor scheduling under limited resources for two linear dynamical systems. We set up that only two sensor nodes were used to monitor the status of two systems, respectively, and consider the scenario that the sensors are smart enough to have abundant computation capability. At each time, the sensors have to decide whether to transmit its local estimate to the remote control center or not for further processing owing to the limited available energy and low channel bandwidth. The necessary condition for the optimal scheduling of sensors is presented which can significantly reduce the feasible optimal solution space. Based on this necessary condition, we construct an optimal explicit sensor schedule, which is periodic and minimizes the estimation error. Examples and simulations are provided at the end of the paper to support the results.

关键词： Bandwidth Kalman filters Wireless sensor networks Covariance matrices Estimation error Scheduling

来源：评论

学校读者我要写书评

暂无评论

Research on Characteristics of Cylinder Tanks in SAR Image

Research on Characteristics of Cylinder Tanks in SAR Image

引用

2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)

作者： Yueting Zhang Hongzhen Chen Kan Tang Wenchang Xiong Chibiao Ding Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of SciencesBeijing China The National Key Laboratory of Microwave Imaging Technology Beijing China Institute of Electronics Chinese Academy of Science

Cylinder tanks appear as arcs in SAR image. It is found the radius of some arcs is bigger than the radius of the tank. To analysis this phenomenon, combining the scattering theory and the principle of SAR, a novel prediction model about the SAR image of cylinder tanks, including the tanks with fixed top and floating top, is proposed. Analysis on details of the SAR image of the tanks is provided by the prediction model. Several experiments are implemented.

关键词： Cylinder tanks SAR image geometry extraction.

来源：评论

学校读者我要写书评

暂无评论

Pattern Analysis and Placement Optimization of the Four-horn Monopulse for Terahertz Communication

Pattern Analysis and Placement Optimization of the Four-horn...

引用

2023 Cross Strait Radio Science and Wireless technology Conference, CSRSWTC 2023

作者： Lu, Yong-Han Zhu, Zhong-Bo Ma, Jing Shi, Bin Zhang, Yu-Ting Peng, Lin Guilin University of Electronic Technology Key Laboratory of Microwave and Optical Wave Application Technology Guangxi Guilin541004 China National Key Laboratory of Science and Technology on Space Microwave Xi'an710100 China Beijing Simulation Center Science and Technology on Special System Simulation Laboratory Beijing100854 China School of Optoelectronic Engineering Guangxi Key Laboratory of Optoelectronic Information Processing Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9798350358971

The mobile node communication in terahertz monopulse system requires narrow beam to align with the mobile target precisely. In this paper, the radiation pattern of four-horn monopulse antenna is analyzed by use of the geometric optics (GO) and aperture field integration method (AFIM), and an efficient placement optimization to reduce the beamwidth of four-horn monopulse is presented. The optimization combines the genetic algorithm (GA) with GO-AFIM. The GA is employed to seek the optimal positions of the four horns, and the GO and AFIM are introduced into the fitness function of GA to evaluate the individual fitness. The optimization result has narrowed the beamwidth and enhanced gain of radiation pattern. Compared with the simulation in full wave software, the proposed method costs less time in pattern analysis and performs more efficiently in placement optimization. © 2023 IEEE.

关键词： aperture field integration method (AFIM) geometric optics (GO) placement optimization terahertz monopulse

来源：评论

学校读者我要写书评

暂无评论

Optimization Algorithms for Predictive Control Approach to Networked Bilinear systems

引用

自动化学报 2017年第7期43卷 1234-1240页

作者： Binglin Wang Yu Kang Jiahu Qin Yanmei Li Department of Automation University of Science and Technology of China Hefei 230027 China State Key Laboratory of Fire Science Department of Automation Institute of Advanced Technology University of Science and Technology of China Hefei 230027 China and also with the Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chi- nese Academy of Sciences Beijing 100190 China Physics and Electronic Engineering Anqing Normal University Anqing 246011 China

This paper is concerned with the networked predictive control of discrete-time bilinear *** deal with the network-induced communication delay that exists in both forward channel（controller to actuator）and feedback channel（sensor to controller）,a bilinear networked predictive control scheme is *** a non-convex optimization problem of solving the predictive control sequence is presented,for which two gradually-optimized algorithms are proposed based on the special structure of bilinear system dynamics *** numerical simulation indicates that the resulting predictive control sequence can compensate for the network-induced issues actively,which proves the effectiveness of the proposed predictive control strategy.

关键词：离散双线性系统预测控制策略逐步优化算法网络化系统动力学模型控制序列反馈通道通信延迟

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：