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International Conference on Radar systems (RADAR 2022)

作者： M. Wang Z. Zhang Y. Wang S. Gao X. Qiu Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing 100190 People's Republic of China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou 215123 People's Republic of China Electrical and Computer Engineering Department George Mason University Fairfax VA 22030 USA

ISBN: (数字)9781839537776

Synthetic aperture radar (SAR) tomography (TomoSAR) has attracted remarkable interest for its ability in achieving threedimensional reconstruction along the elevation direction from multiple observations. In recent years, compressed sensing (CS) technique has been introduced into TomoSAR considering for its super-resolution ability with limited samples. Whereas, the CS-based methods suffer from several drawbacks, including weak noise resistance, high computational complexity and complex parameter fine-tuning. Among the different CS algorithms, iterative soft-thresholding algorithm (ISTA) is widely used as a robust reconstruction approach, however, the parameters in the ISTA are manually chosen, which usually requires a time-consuming fine-tuning process to achieve the best performance. Aiming at efficient TomoSAR imaging, a novel sparse unfolding network named analytic learned ISTA (ALISTA) is proposed towards the TomoSAR imaging problem in this paper, and the key parameters of ISTA are learned from training data via deep learning to avoid complex parameter fine-tuning and significantly relieves the training burden. In addition, experiments verify that it is feasible to use traditional CS algorithms as training labels, which provides a tangible supervised training method to achieve better 3D reconstruction performance even in the absence of labeled data in real applications.

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A no-reference image quality evaluation based on power spectrum

A no-reference image quality evaluation based on power spect...

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3DTV Conference

作者： Yan Zhang Ping An Qiuwen Zhang Liquan Shen Zhaoyang Zhang School of Communication and Information Engineering Shanghai University China Department of Computer Science and Technology Anhui University of Finance and Economics China Key Laboratory of Advanced Displays and System Application Ministry of Education China

ISBN: (纸本)9781612841618

No-reference quality evaluation is more difficult because it does not refer to any image. However, in some cases, like virtual view images, can not find the reference image, no-reference method had to be used. With the free viewpoint video technology development and application, measuring the performance of the multiview video system is essential and virtual view image quality evaluation is one of the key technologies in the system. The characteristic of virtual view image quality evaluation is that most of the virtual view images haven't reference images and can't be assessed using general measures such as PSNR of full-reference. Therefore, this paper proposed a no-reference image quality evaluation method based on image power spectrum. Experimental results show that the proposed method is consistent with PSNR.

关键词： PSNR Image quality Three dimensional displays Transform coding Mathematical model Speckle

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An improved depth map estimation for coding and view synthesis

An improved depth map estimation for coding and view synthes...

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IEEE International Conference on Image Processing

作者： Qiuwen Zhang Ping An Yan Zhang Liquan Shen Zhaoyang Zhang School of Communication and Information Engineering Shanghai University China Key Laboratory of Advanced Displays and System Application Ministry of Education China Department of Computer Science and Technology Anhui University of Finance and Economics China

Inaccuracy depth estimation may influence on depth coding and virtual view rendering in the free-viewpoint television (FTV) system, an improved depth map estimation is proposed to solve the problem for coding and view synthesis. Firstly, check the consistency of initial depth, and the influence of initial miss-matches is minimized by introduction of an additional adaptive matching error selection that penalizes the unreliable matches. Then according to certain criteria, the multi-reference depth maps are merged into one disparity map to improve the quality of disparity map. Finally, a multilateral filtering is used to preserve details in the depth map and simultaneously smooth the depths in occluded areas at object boundary, less texture and discontinuity regions. Experimental results show a significant improvement of the initial input depth maps and coding efficiency, as well as a reduction of view synthesis artifacts.

关键词： Estimation Image coding Rendering (computer graphics) Transform coding Three dimensional displays Filtering

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Patch reordering: A novel way to achieve rotation and translation invariance in convolutional neural networks

arXiv

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arXiv 2019年

作者： Shen, Xu Tian, Xinmei Sun, Shaoyan Tao, Dacheng CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230027 China Centre for Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia

Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance on many visual recognition tasks. However, the combination of convolution and pooling operations only shows invariance to small local location changes in meaningful objects in input. Sometimes, such networks are trained using data augmentation to encode this invariance into the parameters, which restricts the capacity of the model to learn the content of these objects. A more efficient use of the parameter budget is to encode rotation or translation invariance into the model architecture, which relieves the model from the need to learn them. To enable the model to focus on learning the content of objects other than their locations, we propose to conduct patch ranking of the feature maps before feeding them into the next layer. When patch ranking is combined with convolution and pooling operations, we obtain consistent representations despite the location of meaningful objects in input. We show that the patch ranking module improves the performance of the CNN on many benchmark tasks, including MNIST digit recognition, large-scale image recognition, and image retrieval. The code is available at https://***//jasonustc/caffe-multigpu/tree/TICNN. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

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Geography＇s ＂World view＂： The ontological issues of geography

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Journal of Geographical Sciences 2017年第12期27卷 1541-1555页

作者： LIU Kai TANG Maolin LIU Rongzeng QIN Yaochen School of Resources and Environment Science Henan University of Economics and Law Zhengzhou 450002 China School of Geographical Sciences & Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing Normal University Nanjing 210023 China Ministry of Education Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions Henan University Kaifeng 475001 Henan China

Contemporary science philosophy suggests that discussing ontological problems is of fundamental significance broadly within certain specific disciplines. Natural and social science research are inseparable from philosophical guidance; for instance, the philosophy of geography is the ideological basis for geography. The traditional philosophy of geography is methodology- oriented, which primarily emphasizes the ＂logical structure of geography explanations,＂ and ig- nores the discussion of its ontology. This study, in the context of the philosophy of science, ex- plores the relationships between methodology, ontology, and the philosophy of geography, defines the connotations of geographical ontology, analyzes the links and differences between philoso- phical ontology and scientific ontology of geography, clarifies the nature of geographical ontology, and summaries its theoretical values. The ontology of geography incorporates the philosophically ontological beliefs of geographers and geographical schools and the ontological commitment of the theory of geography. As different geographers hold different philosophical viewpoints, their ontological beliefs are different; one geographical theory asserts an ontological commitment of ＂what is there,＂ which determines the nature and types of objectives the theory references. The ontological beliefs of geographers determine their epistemology, methodology, and axiology, and the ontological commitment of a geographical theory is the premise and basis of that theory.

关键词： geography philosophy of science ontology pluralism methodology theoretical value

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ROAD EXTRACTION FROM REMOTE SENSING IMAGES BY MULTIPLE FEATURE PYRAMID NETWORK

ROAD EXTRACTION FROM REMOTE SENSING IMAGES BY MULTIPLE FEATU...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Xun Gao Xian Sun Menglong Yan Hao Sun Kun Fu Yue Zhang Zhipeng Ge School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Road extraction from high-resolution remote sensing images has been applied in many domains, but it is still full of challenges. We focus on the problem of slender roads, proposing a new multiple feature pyramid network (MFPN), which is composed of an effective feature pyramid and the tailored pyramid pooling module based on PSPNet. These two designs can address the sparsity of roads in remote sensing images via using multi-level semantic features. Experiments on remote sensing images from Quick Bird show that our MFPN model achieves competitive performance, especially for slender roads.

关键词： Roads Feature extraction Remote sensing Convolution Semantics Image segmentation Data mining

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Improved multi-view depth estimation for view synthesis in 3D video coding

Improved multi-view depth estimation for view synthesis in 3...

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3DTV Conference

ISBN: (纸本)9781612841618

Multi-view depth estimation is an important part in the virtual view synthesis and depth map coding within the 3DV/FTV applications. However, existing depth estimation methods generally have difficulty to generate good depth results around object edges or in areas with less texture. To solve this problem, we propose an improved algorithm to obtain a smooth and accurate depth map for view synthesis in 3D video coding. The proposed method aims to preserve details in the depth map and simultaneously smooth depths in object boundary occluded area, less texture and discontinuity regions, to avoid blurring in the synthesized views. Experimental results show a significant improvement of the initial input depth maps and coding efficiency, as well as a reduction of view synthesis artifacts.

关键词： Estimation Pixel Three dimensional displays Encoding Rendering (computer graphics) Image coding Transform coding

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A3Net: Adversarial-and-attention network for machine reading comprehension

arXiv

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arXiv 2018年

作者： Wang, Jiuniu Fu, Xingyu Xu, Guangluan Wu, Yirong Chen, Ziyan Wei, Yang Jin, Li Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics CAS Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

In this paper, we introduce Adversarial-and-attention Network (A3Net) for Machine Reading Comprehension. This model extends existing approaches from two perspectives. First, adversarial training is applied to several target variables within the model, rather than only to the inputs or embeddings. We control the norm of adversarial perturbations according to the norm of original target variables, so that we can jointly add perturbations to several target variables during training. As an effective regularization method, adversarial training improves robustness and generalization of our model. Second, we propose a multi-layer attention network utilizing three kinds of high-efficiency attention mechanisms. Multi-layer attention conducts interaction between question and passage within each layer, which contributes to reasonable representation and understanding of the model. Combining these two contributions, we enhance the diversity of dataset and the information extracting ability of the model at the same time. Meanwhile, we construct A3Net for the WebQA dataset. Results show that our model outperforms the state-of-the-art models (improving Fuzzy Score from 73.50% to 77.0%). Copyright © 2018, The Authors. All rights reserved.

关键词： Network layers

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Efficient rendering distortion estimation for depth map compression

Efficient rendering distortion estimation for depth map comp...

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IEEE International Conference on Image Processing

作者： Qiuwen Zhang Ping An Yan Zhang Zhaoyang Zhang School of Communication and Information Engineering Shanghai University China Key Laboratory of Advanced Displays and System Application Ministry of Education China Department of Computer Science and Technology Anhui University of Finance and Economics China

A depth map represents three-dimensional (3D) scene information and is used to synthesize virtual views in 3D video. Since the quality of synthesized virtual views highly depends on the quality of depth map, efficient depth compression is crucial to realize the 3D video system. However compressing depth map using existing video coding techniques yields unacceptable distortions while rendering virtual views. To solve this problem, we propose an efficient depth map compression method for the view rendering, a novel distortion metric base on view rendering distortions instead of distortion of depth map itself. First, we derive relationships between distortions in coded depth map and rendered view. Then, a region based video characteristics distortion model is proposed for precisely estimation distortion in view synthesis. Finally, experimental results have shown that 1.8 dB coding gain in terms of PSNR and subjective quality improvement of synthesized views are achieved by the proposed method.

关键词： Image coding Rendering (computer graphics) Three dimensional displays Cameras Geometry Encoding Estimation

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GEOLOCATION OF HJ-1C SATELLITE IMAGE USING ONE GCP

GEOLOCATION OF HJ-1C SATELLITE IMAGE USING ONE GCP

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IEEE International Geoscience and Remote Sensing Symposium

作者： Jiayin Liu Xiaolan Qiu Yuxin Hu Wen Hong Institute of Electronics Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Key Laboratory of Technology on Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Beijing China

HJ-1C satellite was launched in November 2012 as the first civil spaceborne SAR system of S band in China. Since the image geolocation is essential for the quantificational study of the system specifications of HJ-1C, the paper focuses on the geolocation of HJ-1C SAR image, including the systematic position accuracy of HJ-1C satellite image, and the higher position accuracy with GCPs (ground control point). In addition, a novel equivalent-range-doppler method is presented in this paper to geolocate HJ-1C satellite image using only one GCP.

关键词： Mathematical model Satellites Equations Synthetic aperture radar Accuracy Geology Spaceborne radar

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