检索结果-内蒙古大学图书馆

arXiv 2018年

作者： Fu, Kun Guo, Zhi Yan, Menglong Sun, Xian Sun, Hao Yang, Xue Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

—Ship detection is of great importance and full of challenges in the field of remote sensing. The complexity of application scenarios, the redundancy of detection region, and the difficulty of dense ship detection are all the main obstacles that limit the successful operation of traditional methods in ship detection. In this paper, we propose a brand new detection model based on multiscale rotational region convolutional neural network to solve the problems above. This model is mainly consist of five consecutive parts: Dense Feature Pyramid Network (DFPN), adaptive region of interest (ROI) Align, rotational bounding box regression, prow direction prediction and rotational nonmaximum suppression (R-NMS). First of all, the low-level location information and high-level semantic information are fully utilized through multiscale feature networks. Then, we design adaptive ROI Align to obtain high quality proposals which remain complete spatial and semantic information. Unlike most previous approaches, the prediction obtained by our method is the minimum bounding rectangle of the object with less redundant regions. Therefore, rotational region detection framework is more suitable to detect the dense object than traditional detection model. Additionally, we can find the berthing and sailing direction of ship through prediction. A detailed evaluation based on SRSS and DOTA dataset for rotation detection shows that our detection method has a competitive performance. Copyright © 2018, The Authors. All rights reserved.

关键词： Remote sensing

来源：评论

学校读者我要写书评

暂无评论

Wider channel attention network for remote sensing image super-resolution

arXiv

引用

arXiv 2018年

作者： Gu, Jun Xu, Guangluan Zhang, Yue Sun, Xian Wen, Ran Wang, Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

Recently, deep convolutional neural networks (CNNs) have obtained promising results in image processing tasks including super-resolution (SR). However, most CNN-based SR methods treat low-resolution (LR) inputs and features equally across channels, rarely notice the loss of information flow caused by the activation function and fail to leverage the representation ability of CNNs. In this letter, we propose a novel single-image super-resolution (SISR) algorithm named Wider Channel Attention Network (WCAN) for remote sensing images. Firstly, the channel attention mechanism is used to adaptively recalibrate the importance of each channel at the middle of the wider attention block (WAB). Secondly, we propose the Local Memory Connection (LMC) to enhance the information flow. Finally, the features within each WAB are fused to take advantage of the network’s representation capability and further improve information and gradient flow. Analytic experiments on a public remote sensing data set (UC Merced) show that our WCAN achieves better accuracy and visual improvements against most state-of-the-art methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Image fusion

来源：评论

学校读者我要写书评

暂无评论

Fault-Tolerant Cooperative Tracking Control of Nonlinear Affine systems Using Integral Sliding Mode Control

Fault-Tolerant Cooperative Tracking Control of Nonlinear Aff...

引用

IEEE International Symposium on Industrial Electronics

作者： Qichao Ma Jiahu Qin Yu Kang Wei Xing Zheng 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 Beiiinz China School of Computing Engineering and Mathematics Western Sydney University Sydney Australia

The cooperative tracking problem for a class of nonlinear affine systems are addressed. Actuator faults and external disturbance/model uncertainty are allowed such that we aim to design distributed controllers that can tolerate them while realize cooperative tracking. A general setup is considered, that is, actuator faults can take such forms as actuator degradation and total failure. Then, to guarantee the feasibility of fault-tolerant control, we assume that the actuator has sufficiently many healthy components which enables us to apply integral sliding mode control (ISMC) to develop the distributed controllers that can fulfill the control target and the external disturbance can simultaneously be successfully rejected. We also provide the simulation results to verify the validity of our theoretical findings.

关键词： Cooperative tracking Fault-tolerant control Nonlinear affine systems Integral sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Deep supervised qantization by self-organizing map 25

Deep supervised qantization by self-organizing map

引用

25th ACM International Conference on Multimedia, MM 2017

作者： Wang, Min Zhou, Wengang Tian, Qi Pu, Junfu Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China China Computer Science Department University of Texas San Antonio United States

ISBN: (纸本)9781450349062

Approximate Nearest Neighbour (ANN) search is an important research topic in multimedia and computer vision fields. In this paper, we propose a new deep supervised quantization method by Self-Organizing Map (SOM) to address this problem. Our method integrates the Convolutional Neural Networks (CNN) and Self-Organizing Map into a unified deep architecture. The overall training objective includes supervised quantization loss and classification loss. With the supervised quantization loss, we minimize the differences on the maps between similar image pairs, and maximize the differences on the maps between dissimilar image pairs. By optimization, the deep architecture can simultaneously extract deep features and quantize the features into the suitable nodes in the Self-Organizing Map. The experiments on several public standard datasets prove the superiority of our approach over the existing ANN search methods. Besides, as a byproduct, our deep architecture can be directly applied to classification task and visualization with little modification, and promising performances are demonstrated on these tasks in the experiments. © 2017 ACM.

关键词： Self organizing maps

来源：评论

学校读者我要写书评

暂无评论

An improved semi-global matching method with optimized matching aggregation constraint

引用

IOP Conference Series: Earth and Environmental Science 2020年第1期569卷

作者： Xu Huang Yilong Han Kun Hu School of Geospatial Engineering and Science Sun Yat-sen University Rongyuan Road 4 Zhuhai China Wuhan Engineering Science and Information Institute Jiangda Road 30 Wuhan China School of Remote Sensing and Information Engineering Luoyu Road 129 Wuhan China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences No. 19 North 4th Ring Road West 100190 Beijing China

Stereo dense image matching (DIM) is a key technique in generating dense 3D point clouds at low cost, among which semi-global matching (SGM) is one of the best compromise between the matching accuracy and the time cost. Most commercial or open-source DIM software packages therefore adopt SGM as the core algorithm for the 3D point generation, which computes matching results in 2D image space by simply aggregating the matching results of multi-directional 1D paths. However, such aggregations of SGM did not consider the disparity consistency between adjacent pixels in 2D image space, which will finally decrease the matching accuracy. To achieve higher-accuracy while keep the high time efficiency of SGM, this paper proposes an improved SGM with a novel matching aggregation optimization constraint. The core algorithm formulates the matching aggregation as the optimization of a global energy function, and a local solution of the energy function is utilized to impose the disparity consistency between adjacent pixels, which is capable of removing noises in the matching aggregation results and increasing the final matching accuracy at low time cost. Experiments on aerial image dataset show that the proposed method outperformed the traditional SGM method and another improved SGM method. Compared with the traditional SGM, our proposed method can increase the average matching accuracy by at most 11%. Therefore, our proposed method can applied in some smart 3D applications, e.g. 3D change detection, city-scale reconstruction, and global survey mapping.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An interactive system for eficient 3D furniture arrangement

An interactive system for eficient 3D furniture arrangement

引用

2017 Computer Graphics International Conference, CGI 2017

作者： Yan, Meng Chen, Xuejin Zhou, Jie CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Dept 6 P.O. Box 4 Hefei Anhui230026 China

ISBN: (纸本)9781450352284

We present an interactive example-based system for non-expert users to generate 3D indoor scenes intuitively. From a set of examples of an interior scene, we extract furniture layout constraints including pairwise and group relationships, ergonomic factors and user habits. Instead of inserting a single furniture object to a visual pleasing and functional position independently, we take advantages of manipulating a group of functionality-related furniture objects for smart editing. To deal with the arrangement problem which requires jointly optimizing a variety of functional and visual criteria, we introduce an efficient two-step pipeline consisting of rough arrangement and layout refinement. In the rough arrangement step, furniture objects are roughly placed according to pairwise relationships for accelerating the further optimization process. In the layout refinement step, we optimize the rough furniture layout to a semantical and functional layout considering spatial relationships, and ergonomic factors and avoiding collisions. User interactions are also allowed to move a specific object or a structural group while our system automatically refines the entire layout. The experimental results demonstrate that our system for scene generation measurably increases the visual quality and time efficiency compared with the completely manual scene editing or modeling. © 2017 ACM.

关键词： Virtual reality

来源：评论

学校读者我要写书评

暂无评论

DEEP SEMANTIC SEGMENTATION OF AERIAL IMAGERY BASED ON MULTI-MODAL DATA

DEEP SEMANTIC SEGMENTATION OF AERIAL IMAGERY BASED ON MULTI-...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： Kaiqiang Chen Kun Fu Xian Sun Michael Weinmann Stefan Hinz Boris Jutzi Martin Weinmann Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing P.R. China Institute of Computer Science II University of Bonn Bonn Germany Institute of Photogrammetry and Remote Sensing Karlsruhe Institute of Technology Karlsruhe Germany

In this paper, we focus on the use of multi-modal data to achieve a semantic segmentation of aerial imagery. Thereby, the multi-modal data is composed of a true orthophoto, the Digital Surface Model (DSM) and further representations derived from these. Taking data of different modalities separately and in combination as input to a Residual Shuffling Convolutional Neural Network (RSCNN), we analyze their value for the classification task given with a benchmark dataset. The derived results reveal an improvement if different types of geometric features extracted from the DSM are used in addition to the true orthophoto.

关键词： Semantics Image segmentation Feature extraction Labeling Vegetation mapping Buildings Benchmark testing

来源：评论

学校读者我要写书评

暂无评论

An attention-based word-level interaction model: Relation detection for knowledge base question answering

arXiv

引用

arXiv 2018年

作者： Zhang, Hongzhi Xu, Guandong Liang, Xiao Huang, Tinglei Fu, Kun CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software and Advanced Analytics University of Technology Sydney Australia

Relation detection plays a crucial role in Knowledge Base Question Answering (KBQA) because of the high variance of relation expression in the question. Traditional deep learning methods follow an encoding-comparing paradigm, where the question and the candidate relation are represented as vectors to compare their semantic similarity. Max- or average- pooling operation, which compresses the sequence of words into fixed-dimensional vectors, becomes the bottleneck of information. In this paper, we propose to learn attention-based word-level interactions between questions and relations to alleviate the bottleneck issue. Similar to the traditional models, the question and relation are firstly represented as sequences of vectors. Then, instead of merging the sequence into a single vector with pooling operation, soft alignments between words from the question and the relation are learned. The aligned words are subsequently compared with the convolutional neural network (CNN) and the comparison results are merged finally. Through performing the comparison on low-level representations, the attention-based word-level interaction model (ABWIM) relieves the information loss issue caused by merging the sequence into a fixed-dimensional vector before the comparison. The experimental results of relation detection on both SimpleQuestions and WebQuestions datasets show that ABWIM achieves state-of-the-art accuracy, demonstrating its effectiveness. Copyright © 2018, The Authors. All rights reserved.

关键词： Knowledge based systems

来源：评论

学校读者我要写书评

暂无评论

Passive Super-Low Frequency electromagnetic prospecting technique

引用

Frontiers of Earth Science 2017年第2期11卷 248-267页

作者： Nan WANG Shanshan ZHAO Jian HUI Qiming QIN Institute of Remote Sensing and GIS School of Earth and Space Sciences Peking University Beijing 100871 China Key Laboratory of Technology in Geospatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China

The Super-Low Frequency （SLF） electromag- netic prospecting technique, adopted as a non-imaging remote sensing tool for depth sounding, is systematically proposed for subsurface geological survey. In this paper, we propose and theoretically illustrate natural source magnetic amplitudes as SLF responses for the first step. In order to directly calculate multi-dimensional theoretical SLF responses, modeling algorithms were developed and evaluated using the finite difference method. The theore- tical results of three-dimensional （3-D） models show that the average normalized SLF magnetic amplitude responses were numerically stable and appropriate for practical interpretation. To explore the depth resolution, three-layer models were configured. The modeling results prove that the SLF technique is more sensitive to conductive objective layers than high resistive ones, with the SLF responses of conductive objective layers obviously show- ing uprising amplitudes in the low frequency range. Afterwards, we proposed an improved Frequency-Depth transformation based on Bostick inversion to realize the depth sounding by empirically adjusting two parameters. The SLF technique has already been successfully applied in geothermal exploration and coalbed methane （CBM） reservoir interpretation, which demonstrates that the proposed methodology is effective in revealing low resistive distributions. Furthermore, it siginificantly contributes to reservoir identification with electromagnetic radiation anomaly extraction. Meanwhile, the SLF inter- pretation results are in accordance with dynamic production status of CBM reservoirs, which means it could provide an economical, convenient and promising method for exploring and monitoring subsurface geo-objects.

关键词： Super-Low Frequency （SLF） three-dimen-sional modeling frequency-depth transformation geother-mal exploration coalbed methane （CBM） electromagneticradiation （EMR）

来源：评论

学校读者我要写书评

暂无评论

Digitizing the thermal and hydrological parameters of land surface in subtropical China using AMSR-E brightness temperatures

引用

International Journal of Digital Earth 2017年第7期10卷 687-700页

作者： Yongxian Su Xiuzhi Chen Hua Su Liyang Liu Jishan Liao Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangzhouPeople’s Republic of China Jiangsu Key Laboratory of Agricultural Meteorology College of Applied MeteorologyNanjing University of Information Science and TechnologyNanjingPeople’s Republic of China Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems South China Botanical GardenChinese Academy of SciencesGuangzhouPeople’s Republic of China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National Engineering Research Centre of Geo-spatial Information TechnologyFuzhou UniversityFuzhouPeople’s Republic of China

Digitizing the land surface temperature(T_(s))and surface soil moisture(m _(v))is essential for developing the intelligent Digital ***,we developed a two parameter physical-based passive microwave remote sensing model for jointly retrieving T_(s) and m_(v) using the dual-polarized T_(b) of Aqua satellite advanced microwave scanning radiometer(AMSR-E)C-band(6.9 GHz)based on the simplified radiative transfer *** using in situ T_(s) and m_(v) in southern China showed the average root mean square errors(RMSE)of T s and m_(v) retrievals reach 2.42 K(R^(2)=0.61,n=351)and 0.025 g cm^(−3)(R^(2)=0.68,n=663),*** results were also validated using global in situ T_(s)(n=2362)and m_(v)(n=1657)of International Soil Moisture *** corresponding RMSE are 3.44 k(R 2=0.86)and 0.039 g cm^(−3)(R^(2)=0.83),*** monthly variations of model-derived Ts and mv are highly consistent with those of the Moderate Resolution Imaging Spectroradiometer T_(s)(R^(2)=0.57;RMSE=2.91 k)and ECV_SM m_(v)(R^(2)=0.51;RMSE=0.045 g cm^(−3)),***,this paper indicates an effective way to jointly modeling T_(s) and m_(v) using passive microwave remote sensing.

关键词： Surface soil moisture land surface temperature physical-based radiative transfer model AMSR-E brightness temperatures

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：