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检索条件"任意字段=Conference on Image and Signal Processing for Remote Sensing XII"

共 3607 条记录，以下是101-110 订阅

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Classification of remote sensing Scenes Based on Neural Architecture Search Network 4

Classification of Remote Sensing Scenes Based on Neural Arch...

引用

4th IEEE International conference on signal and image processing (ICSIP)

作者： Li, Lingling Tian, Tian Li, Hang China Univ Geosci Sch Comp Sci Wuhan 430074 Peoples R China China Acad Launch Vehicle Technol Beijing 100076 Peoples R China

ISBN: (纸本)9781728136608

remote sensing image scene classification plays an important role in remote sensing image retrieval, land-use identification and urban planning. Deep learning brings great opportunity to the research in this field, but it transfers the difficulty of traditional characteristic engineering to the design of network structure. In this paper, we focus on the automatic design of the network model and propose a remote sensing scene classification method based on Neural Architecture Search Network (NASNet). We further use the transfer learning technology to make the designed network well migrated to the remote sensing scene classification data set. This method can automatically build the appropriate network structure according to the application. We compare the proposed method on a publicly large-scale dataset with several convolutional neural network (CNN) models. The experimental results demonstrate that the proposed method provides state-of-the-art performance compared with the traditional artificial neural network.

关键词： automatic design transfer learning neural architecture search network remote sensing scene classification

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A new independent component analysis (ICA) method and its application to remote sensing images

A new independent component analysis (ICA) method and its ap...

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conference on image and signal processing for remote sensing VII

作者： Zhang, XH Chen, CH SE Massachusetts Univ Dept Elect & Comp Engn N Dartmouth MA 02747 USA

ISBN: (纸本)0819442666

In this paper, a new independent component analysis (ICA) method is proposed that makes use of the higher order statistics. We name it joint cumulant ICA (JC-ICA) algorithm. It can be implemented efficiently by a neural network. Its applications in AVIRIS data and change detection are discussed. The results show the potential usage in image processing problems.

关键词： remote sensing

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AN END-TO-END ADVERSARIAL HASHING METHOD FOR UNSUPERVISED MULTISPECTRAL remote sensing image RETRIEVAL

AN END-TO-END ADVERSARIAL HASHING METHOD FOR UNSUPERVISED MU...

引用

IEEE International conference on image processing (ICIP)

作者： Chen, Xuelei Lu, Cunyue Shanghai Jiao Tong Univ Dept Instrument Sci & Engn Shanghai Peoples R China

ISBN: (纸本)9781728163956

Unlike natural images, remote sensing images are usually multispectral. And the lack of sufficient labeled data puts a limit on supervised learning for remote sensing image retrieval. In this paper, we propose a novel method for unsupervised multispectral remote sensing image retrieval. The proposed method makes use of the unsupervised representation learning ability of GAN. Meanwhile, a new reconstruction loss exploits the latent codes in GAN to make the final output informative and representative. Transfer learning and color histograms are used to generate an estimated similarity matrix to further guide the training. Hash constraints can make the output codes binary and compact. In the testing stage, the hash codes of multispectral images can be computed in an end-to-end manner. Experiments on a multispectral remote sensing image dataset, EuroSAT [1], show the superiority of the proposed method over other state-of-the-art methods.

关键词： image retrieval remote sensing GAN learning to hash unsupervised learning

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AN OVERVIEW OF THE CONTRIBUTIONS OF JOSE MANUEL BIOUCAS-DIAS TO remote sensing image processing

AN OVERVIEW OF THE CONTRIBUTIONS OF JOSE MANUEL BIOUCAS-DIAS...

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IEEE International Geoscience and remote sensing Symposium (IGARSS)

作者： Plazas, Antonio Li, Jun Figueiredo, Mario A. T. Univ Extremadura Hyperspectral Comp Lab Caceres Spain Sun Yat Sen Univ Sch Geog & Planning Guangzhou Peoples R China Univ Lisbon Inst Telecomunicacoes Lisbon Portugal Univ Lisbon Inst Super Tecn Lisbon Portugal

ISBN: (纸本)9781665403696

Jose Manuel Bioucas-Dias was an outstanding expert in many different IEEE-related areas, including inverse problems in imaging, signal and image processing, pattern recognition, optimization, and remote sensing. He authored or co-authored more than 250 publications, including more than 100 journal papers (66 of which published in IEEE journals) and over 200 peer-reviewed international conference papers and book chapters. His contributions have been extremely influential in many different fields, namely phase estimation and unwrapping, convex optimization and Bayesian inference for imaging inverse problems, with a special emphasis on remote sensing, including synthetic aperture radar (SAR), hyperspectral unmixing, fusion, superresolution, classification, and segmentation. In this paper, we provide an overview of his outstanding contributions to remote sensing image processing.

关键词： remote sensing pattern recognition optimization signal and image processing inverse problems

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Gaussian process classification using image deformation

Gaussian process classification using image deformation

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32nd IEEE International conference on Acoustics, Speech and signal processing

作者： Williams, David P. Signal Innovat Grp Res Triangle Pk NC USA

ISBN: (纸本)1424407281

An image deformation algorithm is integrated with a Gaussian process classifier for application to remote-sensing tasks in which data is in the form of imagery. To combine these disparate techniques, we introduce a novel kernel covariance function for the Gaussian process that allows us to incorporate the result of the image deformation algorithm into a rigorous Bayesian classification framework. The resulting classifier is completely non-parametric in the sense that no parameters or hyperparameters must be learned. The promise of the proposed algorithm is demonstrated on a data set of real, measured land mine data.

关键词： classification image deformation Gaussian processes remote sensing automatic target recognition

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remote sensing image Super-resolution: Challenges and Approaches

Remote Sensing Image Super-resolution: Challenges and Approa...

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IEEE International conference on Digital signal processing (DSP)

作者： Yang, Daiqin Li, Zimeng Xia, Yatong Chen, Zhenzhong Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Peoples R China

ISBN: (纸本)9781479980581

remote sensing has a growing relevance in the modern society with the development of image processing of satellite imagery. However, due to the limitations of the current imaging sensors and the complex atmospheric conditions, we are facing great challenges in the remote sensing applications due to the limited spatial, spectral, radiometric and temporal resolutions. Therefore, super-resolution techniques have attracted much attention by which the low quality low resolution remote sensing images are enhanced. In this paper, we discuss the challenges in remote sensing image super-resolution and thereafter review the relevant approaches. More specifically, the different categories of remote sensing techniques, i.e., the learning-based, interpolation based, frequency domain based, and probability based methods, are reviewed and discussed. Furthermore, the super-resolution applications are discussed and insightful comments on future research directions are provided.

关键词： Super resolution remote sensing observation model

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FILTERING AND EDGE DETECTION OF remote sensing imageS BY HERMITE INTEGRATION

FILTERING AND EDGE DETECTION OF REMOTE SENSING IMAGES BY HER...

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conference on image and signal processing for remote sensing

作者： SHEN, J SHEN, W Univ. de Bordeaux III Talence Fr

ISBN: (纸本)0819416452

image smoothing and edge detection by use of Gaussian filters are much used in remote sensing image processing. In the present paper, we propose Hermite integration method to realize Gaussian filters and their derivatives by use of orthogonal polynomial theory and interpolation. We analyze at first 1-D cases and show that the output of a Gaussian filter can be calculated by the weighted sum of the input signal sampled at the positions corresponding to the Hermite polynomial roots, which gives a much better algebraic precision and a less important complexity than the classical mask convolution method. The digital implementation is then presented. The Hermite integration method is then generalized to the calculation of Gaussian-filtered derivatives and to multidimensional cases, such as 2-D image processing in remote sensing. Our method shows the following advantages: (1) Better algebraic precision. (2) Constant and reduced computational complexity independent of the filter window size. (3) processing completely in parallel. (4) The possibility to detect edges with subpixel precision. The method is implemented and tested for artificial data and real remote sensing images and is compared with the classical mask convolution method, the experimental results are reported as well.

关键词： remote sensing

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DEEP LEARNING IN VERY HIGH RESOLUTION remote sensing image INFORMATION MINING. COMMUNICATION CONCEPT

DEEP LEARNING IN VERY HIGH RESOLUTION REMOTE SENSING IMAGE I...

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20th European signal processing conference (EUSIPCO)

作者： Vaduva, Corina Gavat, Inge Datcu, Mihai Univ Politehn Bucuresti Bucharest Romania

ISBN: (纸本)9781467310680

This paper presents the image information mining based on a communication channel concept. The feature extraction algorithms encode the image, while an analysis of topic discovery will decode and send its content to the user in the shape of a semantic map. We consider this approach for a real meaning based semantic annotation of very high resolution remote sensing images. The scene content is described using a multi-level hierarchical information representation. Feature hierarchies are discovered considering that higher levels are formed by combining features from lower level. Such a level to level mapping defines our methodology as a deep learning process. The whole analysis can be divided in two major learning steps. The first one regards the Bayesian inference to extract objects and assign basic semantic to the image. The second step models the spatial interactions between the scene objects based on Latent Dirichlet Allocation, performing a high level semantic annotation. We used a WorldView2 image to exemplify the processing results.

关键词： Information theory deep learning semantic annotation

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Object Recognition of High Resolution remote sensing image Based on PSWT

Object Recognition of High Resolution Remote Sensing Image B...

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International Symposium on image Analysis and signal processing

作者： Yu Haiyang Gan Fuping Henan Polytech Univ Dept Engn Sch Surveying & Land Informat Jiaozuo Peoples R China Ctr Land & Resources China Aero Geophys Survey & Remote Sensing Beijing Peoples R China

ISBN: (纸本)9781424439867

High resolution image provides an important new data source for object recognition. A method based on pyramid-structured wavelet transform (PSWT) for object recognition on high-resolution remote sensing image is put forward. First, the model image and the search image are decomposed to pyramid-structure by wavelet transform. A novel match metric is computed using direction vectors constructed by the high-frequency information of wavelet coefficients. This metric is robust to occlusion, clutter, illumination changes. And the matching can be implemented until the highest level of decomposing to track said instances of the model in the lowest one. The tests confirm that the proposed algorithm is efficient and reliable.

关键词： Object recognition High-resolution remote sensing imagery wavelet transform Similarity measures algorithm

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Urban Change Detection and Analysis of Symbiosis University Nagpur, India Based on remote sensing Techniques 3

Urban Change Detection and Analysis of Symbiosis University ...

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3rd International conference on signal processing and Communication (ICPSC)

作者： Gaidhane, Pritesh D. Dorge, Prabhakar D. Balamwar, Sanjay V. Yeshwantrao Chavan Coll Engn Dept Elect & Telecommun Engn Nagpur Maharashtra India Applicat Ctr Dept Maharashtra Remote Sensing Nagpur Maharashtra India

ISBN: (纸本)9781665428644

remote sensing is basically the method of detection of the physical parameters of a specific area along with that it also monitors the area by measuring the radiation parameters from satellite. The cameras are designed to gather remotely sensed images, which are used to sense things of the earth's surface. Like the cameras on the satellites and the airplanes takes pictures of the different area, allowing us to get every minute detail about it. Now, change detection is the process to identify the changes or differences in various parts of land characteristics at different intervals. This process can be carried by manual observation or by the use of remote sensing software. Because of the rapid urbanization there has been a significant impact on resources and urban environment. But with the use of high quality multi-spatial and multi-temporal remote sensing data, it is quite easy to possibly observe the changes in the urban environment. Therefore, the given study aims to quantify changes in the urban area of Symbiosis University Nagpur, Maharashtra India using Land satellite image. These changes of urbanization are detected by satellite images of Land-Sat MSS in march-2016, march-2018 and may-2020 using a geographic information system (GIS). The change of urbanization in Symbiosis University is for building, road, garden and ground are 17.35%, 20.71%, 1.65% and 0.89% respectively and the total change is 43.51%. From this change we will receive the taxes as per its ongoing construction and it will be easy for government.

关键词： Mobility patterns K-means GIS-image resolution digital image processing remote sensing image classification image thresholding mapping of images etc.

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