- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Simple Cosolvent-Treated PEDOT:PSS Films on Hybrid Solar Cells With Improved Efficiency
摘要： This paper reports the outcomes of the 2014 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource remote sensing studies. In the 2014 edition, participants considered multiresolution and multi-sensor fusion between optical data acquired at 20-cm resolution and long-wave (thermal) infrared hyperspectral data at 1-m resolution. The Contest was proposed as a double-track competition: one aiming at accurate landcover classification and the other seeking innovation in the fusion of thermal hyperspectral and color data. In this paper, the results obtained by the winners of both tracks are presented and discussed.
关键词： multimodal-,multisource-data fusion,thermal imaging,landcover classification,multiresolution-,Hyperspectral,image analysis and data fusion (IADF)
更新于2025-09-23 15:19:57
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Sharpening the VNIR and SWIR Bands of Sentinel-2A Imagery through Modified Selected and Synthesized Band Schemes
摘要： In this work, the bands of a Sentinel-2A image with spatial resolutions of 20 m and 60 m are sharpened to a spatial resolution of 10 m to obtain visible and near-infrared (VNIR) and shortwave infrared (SWIR) spectral bands with a spatial resolution of 10 m. In particular, we propose a two-step sharpening algorithm for Sentinel-2A imagery based on modified, selected, and synthesized band schemes using layer-stacked bands to sharpen Sentinel-2A images. The modified selected and synthesized band schemes proposed in this study extend the existing band schemes for sharpening Sentinel-2A images with spatial resolutions of 20 m and 60 m to improve the pan-sharpening accuracy by changing the combinations of bands used for multiple linear regression analysis through band-layer stacking. The proposed algorithms are applied to the pan-sharpening algorithm based on component substitution (CS) and a multiresolution analysis (MRA), and our results are then compared to the sharpening results when using sharpening algorithms based on existing band schemes. The experimental results show that the sharpening results from the proposed algorithm are improved in terms of the spatial and spectral properties when compared to existing methods. However, the results of the sharpening algorithm when applied to our modified band schemes show differing tendencies. With the modified, selected band scheme, the sharpening result when applying the CS-based algorithm is higher than the result when applying the MRA-based algorithm. However, the quality of the sharpening results when using the MRA-based algorithm with the modified synthesized band scheme is higher than that when using the CS-based algorithm.
关键词： band selection and synthesis,Sentinel-2A sharpening,multiple linear regression,component substitution (CS),multiresolution analysis (MRA)
更新于2025-09-19 17:15:36
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[IEEE 2019 IEEE MTT-S International Wireless Symposium (IWS) - Guangzhou, China (2019.5.19-2019.5.22)] 2019 IEEE MTT-S International Wireless Symposium (IWS) - A Dual-Mode Dual-Band Waveguide Filter Excited by Coaxial Probe
摘要： In this paper, we discuss the scienti?c outcomes of the 2015 data fusion contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource studies. The 2015 edition of the contest proposed a multiresolution and multisensorial challenge involving extremely high-resolution RGB images and a three-dimensional (3-D) LiDAR point cloud. The competition was framed in two parallel tracks, considering 2-D and 3-D products, respectively. In this paper, we discuss the scienti?c results obtained by the winners of the 2-D contest, which studied either the complementarity of RGB and LiDAR with deep neural networks (winning team) or provided a comprehensive benchmarking evaluation of new classi?cation strategies for extremely high-resolution multimodal data (runner-up team). The data and the previously undisclosed ground truth will remain available for the community and can be obtained at http://www.grss-ieee.org/community/technical-committees/data-fusion/2015-ieee-grss-data-fusion-contest/. The 3-D part of the contest is discussed in the Part-B paper [1].
关键词： image analysis and data fusion (IADF),multiresolution-,landcover classification,multimodal-data fusion,multisource-,Deep neural networks,extremely high spatial resolution,LiDAR
更新于2025-09-19 17:13:59
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Microscopy and Analysis || Automatic Interpretation of Melanocytic Images in Confocal Laser Scanning Microscopy
摘要： The frequency of melanoma doubles every 20 years. The early detection of malignant changes augments the therapy success. Confocal laser scanning microscopy (CLSM) enables the noninvasive examination of skin tissue. To diminish the need for training and to improve diagnostic accuracy, computer-aided diagnostic systems are required. Two approaches are presented: a multiresolution analysis and an approach based on deep layer convolutional neural networks. For the diagnosis of the CLSM views, architectural structures such as micro-anatomic structures and cell nests are used as guidelines by the dermatologists. Features based on the wavelet transform enable an exploration of architectural structures at different spatial scales. The subjective diagnostic criteria are objectively reproduced. A tree-based machine-learning algorithm captures the decision structure explicitly and the decision steps are used as diagnostic rules. Deep layer neural networks require no a priori domain knowledge. They are capable of learning their own discriminatory features through the direct analysis of image data. However, deep layer neural networks require large amounts of processing power to learn. Therefore, modern neural network training is performed using graphics cards, which typically possess many hundreds of small, modestly powerful cores that calculate massively in parallel. Readers will learn how to apply multiresolution analysis and modern deep learning neural network techniques to medical image analysis problems.
关键词： convolutional neural networks,skin lesions,multiresolution image analysis,computer-aided diagnosis,confocal laser scanning microscopy,machine learning
更新于2025-09-19 17:13:59
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Corrections to a??On the Groundwave Excited by a Vertical Hertzian Dipole Over a Planar Conductor: Second-Order Asymptotic Expansion With Applications to Plasmonicsa??
摘要： We describe a method of oversampling signals defined on a weighted graph by using an oversampled graph Laplacian matrix. The conventional method of using critically sampled graph filter banks has to decompose the original graph into bipartite subgraphs, and a transform has to be performed on each subgraph because of the spectral folding phenomenon caused by downsampling of graph signals. Therefore, the conventional method cannot always utilize all edges of the original graph in a single stage transformation. Our method is based on oversampling of the underlying graph itself, and it can append nodes and edges to the graph somewhat arbitrarily. We use this approach to make one oversampled bipartite graph that includes all edges of the original non-bipartite graph. We apply the oversampled graph with the critically sampled graph filter bank or the oversampled one for decomposing graph signals and show the performances on some experiments.
关键词： multiresolution,Graph filter banks,graph signal processing,graph wavelets,graph oversampling
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) - Valparaiso, Chile (2019.11.13-2019.11.27)] 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) - Series-Resonant DCa??DC Converter for Solar Photovoltaic Non Isolated Applications
摘要： This paper reports the outcomes of the 2014 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource remote sensing studies. In the 2014 edition, participants considered multiresolution and multi-sensor fusion between optical data acquired at 20-cm resolution and long-wave (thermal) infrared hyperspectral data at 1-m resolution. The Contest was proposed as a double-track competition: one aiming at accurate landcover classification and the other seeking innovation in the fusion of thermal hyperspectral and color data. In this paper, the results obtained by the winners of both tracks are presented and discussed.
关键词： multimodal-,multisource-data fusion,thermal imaging,landcover classification,multiresolution-,Hyperspectral,image analysis and data fusion (IADF)
更新于2025-09-19 17:13:59
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Analysis and design of a hybrid optical fiber refractometer for large dynamic range measurements
摘要： In this paper, we report the outcomes of the 2015 data fusion contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society. As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource studies. The 2015 edition of the contest proposed a multiresolution and multisensorial challenge involving extremely high resolution RGB images (with a ground sample distance of 5 cm) and a 3-D light detection and ranging point cloud (with a point cloud density of approximatively 65 pts/m2 ). The competition was framed in two parallel tracks, considering 2-D and 3-D products, respectively. In this Part B, we report the results obtained by the winners of the 3-D contest, which explored challenging tasks of road extraction and ISO containers identi?cation, respectively. The 2-D part of the contest and a detailed presentation of the dataset are discussed in Part A.
关键词： light detection and ranging (LiDAR),very high resolution (VHR) data,object identi?cation,multiresolution-data fusion,multisource-data fusion,multimodal-data fusion,Image analysis and data fusion (IADF),road detection
更新于2025-09-16 10:30:52
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A Markovian Approach to Unsupervised Change Detection with Multiresolution and Multimodality SAR Data
摘要： In the framework of synthetic aperture radar (SAR) systems, current satellite missions make it possible to acquire images at very high and multiple spatial resolutions with short revisit times. This scenario conveys a remarkable potential in applications to, for instance, environmental monitoring and natural disaster recovery. In this context, data fusion and change detection methodologies play major roles. This paper proposes an unsupervised change detection algorithm for the challenging case of multimodal SAR data collected by sensors operating at multiple spatial resolutions. The method is based on Markovian probabilistic graphical models, graph cuts, linear mixtures, generalized Gaussian distributions, Gram–Charlier approximations, maximum likelihood and minimum mean squared error estimation. It bene?ts from the SAR images acquired at multiple spatial resolutions and with possibly different modalities on the considered acquisition times to generate an output change map at the ?nest observed resolution. This is accomplished by modeling the statistics of the data at the various spatial scales through appropriate generalized Gaussian distributions and by iteratively estimating a set of virtual images that are de?ned on the pixel grid at the ?nest resolution and would be collected if all the sensors could work at that resolution. A Markov random ?eld framework is adopted to address the detection problem by de?ning an appropriate multimodal energy function that is minimized using graph cuts.
关键词： Markov random ?elds (MRF),maximum likelihood (ML) estimation,synthetic aperture radar (SAR),Gram–Charlier approximation,multiresolution data fusion,multimodality data fusion,graph cuts,minimum mean squared error (MMSE) estimation,generalized Gaussian
更新于2025-09-10 09:29:36
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[Studies in Computational Intelligence] Recent Advances in Computer Vision Volume 804 (Theories and Applications) || Content-Based Image Retrieval Using Multiresolution Feature Descriptors
摘要： The advent of low-cost cameras and smartphones have made the task of image capturing quite easy nowadays. This has resulted in the collection of large number of unorganized images. Accessing images from large repository of unorganized images is quite challenging. There is a need of such systems which help in proper organization and easy access of images. The field of image retrieval, using text or image, attempts to solve this problem. While text-based retrieval systems are quite popular, they suffer from certain drawbacks. The other type of image retrieval system, which is Content-based Image Retrieval (CBIR) system, uses image features to search for relevant images. This chapter discusses the concept multiresolution feature descriptors for CBIR. For capturing varying level of details, single resolution processing of image proves to be insufficient. The use of multiresolution descriptors prove to be quite efficient in capturing complex foreground and background details in an image. This chapter discusses the important properties and advantages of multiresolution feature descriptors. Furthermore, this chapter proposes a CBIR technique using a novel multiresolution feature descriptor. The proposed method constructs feature vector by capturing shape feature in a localized manner. The experimental results show the effectiveness of the proposed method.
关键词： Content-Based Image Retrieval,CBIR,Feature Descriptors,Multiresolution Feature Descriptors,Image Retrieval
更新于2025-09-04 15:30:14
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Determination of optimum segmentation parameter values for extracting building from remote sensing images
摘要： Lately, with progresses in remote sensing information techniques and the growingly and unprecedented uses of its uses, remote sensing became a science that cannot be dispensed with in most ?elds and ground object extraction has turned out to be more exact. Remote sensing image of high spatial resolution gives more inconspicuous components for instance, shape, color, size. The use of the old pixel-based method of classi?cation images inevitably leads to a signi?cant sacri?cing of image classi?cation accuracy. The use of unconventional methods such as object based image analysis (OBIA) to obtain data from image of high spatial resolution becomes the focus of many researchers. The initial phase of the OBIA technique is segmentation, which is a procedure that partition an image into moderately homogeneous areas named segments. Because the conventional pixel-based method does not suit the classi?cation of remote sensing images with spatial resolution, it has been replaced by a new standard method OBIA. Choosing the parameters of segmentation is a fundamental stage in the image segmentation process, the main purpose of this research is to try to ?nd the best values or near the best values for the parameters of image segmentation. It is expected to obtain an image object that expresses the reality and therefore obtain the accuracy of the classi?cation of the satellite images if the selection of good and appropriate segmentation parameters well done. There are three parameters that have a signi?cant impact on the accuracy of the results of the segmentation must be determined their values with high precision, where they can be arranged from the lowest up, these are compactness, shape scale. Dependence on use of visual analysis alone in determining the values of these parameters is a waste of time. Consequently, in this paper, a set of segmentations was carried out utilizing the Worldview-3 image with different values for the segmentation parameters to de?ne ideal or close ideal segmentation parameters used to extracting building from remote sensing images.
关键词： Multiresolution segmentation,Optimum segmentation parameter,Segmentation quality
更新于2025-09-04 15:30:14