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检索条件"机构=CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems"

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A Method for Object Occlusion Handling Based on Multilevel Track Queues

A Method for Object Occlusion Handling Based on Multilevel T...

引用

International Conference on Multimedia and Signal processing (CMSP)

作者： Biao Jin Wenlong Hu Yu Zhang Institute of Electronic Key Laboratory of Technology in Geo-spatial Information Processing and Application System CAS Graduate School Chinese Academy and Sciences Beijing China Institute of Electronic Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy and Sciences Beijing China China Electrical Power Research Institute Beijing China

Multi-object tracking is important in many computer vision applications. The major difficulties are due to inter-object or scene occlusion and data association. In this paper, we present a method to automatically detect and track multiple objects in complicated scenario from a single camera that is stationary. The proposed detecting method can prevent the moving objects updated to the background and can restrain ghosts. The moving objects are modeled fusing the hue and edge features. The system achieves tracking the object using the proposed associated strategy based on multilevel track queues. Experiments show the effectiveness of our approach under different conditions with complete occlusions.

关键词： Tracking Image edge detection Pixel Cameras Videos Computational modeling Algorithm design and analysis

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Layer-wise coordination between encoder and decoder for neural machine translation 18

Layer-wise coordination between encoder and decoder for neur...

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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.

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A new ship detection method for massive data high-resolution remote sensing images

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2012 2nd International Conference on Materials Science and information technology, MSIT 2012

作者： Sun, Hao Li, Yu Liu, Ge Long, Hui Wang, Hongqi Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783037854389

This paper proposes a new method for automatic ship targets detection in remote sensing images. The method uses adaptive segmentation algorithm for getting possible ship targets first, and then calculates Histograms of Oriented Gradient (HOG) feature to extract the structural information of ships, followed by supervised learning algorithm to identify the possible ship targets. Multi-scale sliding-window is used to handle targets with different scales. The experimental results prove that this new method has a good precision and robustness for most of the ship targets and give attention to the efficiency.© (2012) Trans Tech Publications, Switzerland.

关键词： Ships

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A space-based radar nonlinear tracking method for air targets based on VB-PHD filter

A space-based radar nonlinear tracking method for air target...

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Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Linlin Fang Lihua Zhong Bing Han Yuxin Hu Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of Sciences Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Space-based radar has better coverage and is not limited by the curvature of the earth. Aircraft target tracking is particularly important in space-based radar system. However, the long observation distance and strong nonlinear observation increases the challenge of target tracking. Therefore, we proposed a space-based radar nonlinear tracking method for air targets based on variational Bayesian probability hypothesis density (VB-PHD) filter. The relationship between state and observation is established. Then, the VB method is adopted to deal with uncertainty of measurement noise variances. Besides, the cubature filter is introduced to deal with the strongly nonlinear models, and the recursion process is completed by using the third-order spherical radial volume rule. Finally, simulation scenarios with different measurement noise parameters were constructed, and the tracking result comparisons show that it effectively solves nonlinear problems, and tracking precision can be significantly improved.

关键词： Solid modeling Target tracking Uncertainty Spaceborne radar Simulation Noise Measurement uncertainty Radar tracking Bayes methods Noise measurement

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A COOPERATIVE MULTITEMPORAL SEGMENTATION METHOD FOR SAR AND OPTICAL IMAGES CHANGE DETECTION

A COOPERATIVE MULTITEMPORAL SEGMENTATION METHOD FOR SAR AND ...

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IEEE International geoscience and Remote Sensing Symposium

作者： Ling Wan Yuming Xiang Hongjian You Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

This paper proposes an extension version of our previous work MS-CC to achieve optical and SAR images change detection. The proposed method introduces a cooperative multitemporal segmentation, whose merging process considers the heterogeneity of SAR and optical images as parallel information, making sure that the multitemporal information can be fully utilized without interfering with each other. Then, the change detection strategy based on compound classification is carried out on the segmentation results, obtaining the multi-scale change detection maps. Experimental validation is conducted with GoaFen3 and Google Earth data.

关键词： Image segmentation Optical imaging Radar polarimetry Optical sensors Compounds Interference Stacking

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A STUDY ON THE FREQUENCY AND AZIMUTH COHERENCE OF HIGH-RESOLUTION SAR IMAGE

A STUDY ON THE FREQUENCY AND AZIMUTH COHERENCE OF HIGH-RESOL...

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IEEE International geoscience and Remote Sensing Symposium

作者： Wenji Xing Xiaolan Qiu Chibiao Ding The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

High-resolution SAR has large transmitting bandwidth and wide synthetic aperture. How to understand and take advantage of the variation characteristics of SAR scattering characteristics with angle and frequency is a topic that worth studying. This article establishes a coherence matrix of sub-band and sub-aperture SAR images, and analyzes its ability to classify scattering mechanism. Experiments are conducted using the TerraSAR-X high-resolution data of different scenarios, and some meaningful results are got, which may provide some support to the analysis and application of high-resolution SAR data.

关键词： Coherence Entropy Azimuth Radar polarimetry Synthetic aperture radar Image resolution

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Unambiguous parameter estimation of radial velocity approach for airborne SAR-GMTI

Unambiguous parameter estimation of radial velocity approach...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Ruipeng Xu Dandan Zhang Lijia Huang Donghui Hu Chibiao Ding Key Laboratory of Geo-spatial Information Processing and Application System Technology Institute of Electronics Chinese Academy of Sciences Beijing China

The ambiguous Doppler centroid causes incorrect estimation result of the radial velocity. For moving targets with fast radial velocity, an unambiguous estimation approach of the radial velocity is introduced for the airborne SAR system in this paper. First, two channels carried different wavelength can be constructed by range multilook processing (RMLP). Second, the instantaneous frequency curve of the moving target is obtained by polynomial fitting for each channel, where the linear term denotes the baseband Doppler centroid. Considering the fact that the difference of the estimated baseband Doppler centroid in two channels is equal to the difference of the absolute Doppler centroid, the unambiguous radial velocity can be estimated using it. Third, the range walk and the Doppler shift which are produced by the fast radial velocity can be eliminated by compensating a phase in the range-frequency and azimuth-time domain. As a result, the moving target will be reimaged and relocated after azimuth compression. The proposed approach will be applied to both single — and multi-channel SAR system. The simulation results validate the effectiveness of the proposed method.

关键词： Doppler effect Estimation Baseband Azimuth Accuracy Fitting Polynomials

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Improving Wetland Mapping by Using Multi-Source Data Sets

Improving Wetland Mapping by Using Multi-Source Data Sets

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International Symposium on Image and Data Fusion (ISIDF)

作者： Luyan Ji Kang Jiang Xiurui Geng Hairong Tang Kai Yu Yongchao Zhao Key Laboratory of Technology in Geo-spatial information Processing and Application System Institute of Electronics Chinese Academy of Science Beijing China

To conserve and manage wetland resources, it is important to map wetlands and monitor their changes. However, wetland mapping is difficult because of spectral confusion with other landcover classes and spectral variability among different types of wetlands. This paper demonstrated a multi-source based approach for improving the accuracy of wetland mapping. According to the formation of wetland, variables derived from multi-source image date, and other ancillary GIS layers were first integrated to create the possible region for wetland (PRW). And then classification was conducted within the PRW to map wetlands. PRW could greatly reduce the amount of other land cover classes that participated in the classification, therefore reducing both the difficulty of wetland mapping and the commission error rate. In this study, we chose the test area in Dongzhai Harbor, Hainan Island, China, where the main wetland type is mangrove. The mapping was based on LANDSAT TM/ETM+ imagery combined with DEM data, and the ancillary GIS data included available water, soil and vegetation layers. The thematic accuracy of the mapping was assessed using high-resolution images from Google Earth and local wetlands databases. Classification of the 2001 Landsat ETM+ scene alone resulted in consumer's accuracy of 65% and Kappa coefficients of 0.69, whereas the multi-source based approach with the same training samples resulted in an accuracy of 86% and 0.80. The developed method is portable, relatively easy to implement, and should be applicable in other landcover classes and over larger extents.

关键词： Remote sensing Accuracy Satellites Earth Training Monitoring Databases

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ON THE USE OF CNN FOR AUTOMATED QUALITY ASSESSMENT OF GF-3 POLARIMETRIC DATA

ON THE USE OF CNN FOR AUTOMATED QUALITY ASSESSMENT OF GF-3 P...

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IEEE International geoscience and Remote Sensing Symposium

作者： Songtao Shangguan Xiaolan Qiu Bin Lei The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

With the needs of quality assessment for massive GF-3 polarimetric data, a method based on common distribution targets has been proposed by Sha Jiang. However, it needs manually selection of those woodlands, and cannot be performed automatically. In this paper, an automated GF-3 full-polarization SAR data quality assessment method is conducted using a classic Convolution Neural Network (VGG-16). The network is pre-trained by Radarsat-2 PolSAR data and then trained by selected typical GF-3 scenes. It is supposed to learn the features of the targets, which satisfies the azimuthal symmetry and backscatter reciprocity and fulfills the quality assessment work. Several typical GF-3 strips data are used to test the method. Experiments show that the network can predict the plots of targets from a new scene under the interference of polarimetric distortion and noise. And, the quality assessment results by the network are consistent with the manual assessment results, which shows the effectiveness of the method.

关键词： Quality assessment Distortion Data integrity Strips Manuals Forestry Radar polarimetry

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Interpreting the Latent Space of GANs via Correlation Analysis for Controllable Concept Manipulation

Interpreting the Latent Space of GANs via Correlation Analys...

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International Conference on Pattern Recognition

作者： Ziqiang Li Rentuo Tao Hongjing Niu Mingdao Yue Bin Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems University of Science and Technology of China Hefei Anhui China College of Mechanical and Electrical Engineering Suzhou University Suzhou Anhui China

Generative adversarial nets (GANs) have been successfully applied in many fields like image generation, inpainting, super-resolution, and drug discovery, etc. By now, the inner process of GANs is far from being understood. To get a deeper insight into the intrinsic mechanism of GANs, in this paper, a method for interpreting the latent space of GANs by analyzing the correlation between latent variables and the corresponding semantic contents in generated images is proposed. Unlike previous methods that focus on dissecting models via feature visualization, the emphasis of this work is put on the variables in latent space, i.e. how the latent variables affect the quantitative analysis of generated results. Given a pre-trained GAN model with weights fixed, the latent variables are intervened to analyze their effect on the semantic content in generated images. A set of controlling latent variables can be derived for specific content generation, and the controllable semantic content manipulation is achieved. The proposed method is testified on the datasets Fashion-MNIST and UT Zappos50K, experiment results show its effectiveness.

关键词： Drugs Visualization Analytical models Correlation Statistical analysis Image synthesis Semantics

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