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1

Lu, Shao-Ping, Sibo Feng, Beerend Ceulemans, Miao Wang, Rui Zhong, and Adrian Munteanu. "Multiview conversion of 2D cartoon images." Communications in Information and Systems 16, no. 4 (2016): 229–54. http://dx.doi.org/10.4310/cis.2016.v16.n4.a2.

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2

Chapiro, Alexandre, Simon Heinzle, Tunç Ozan Aydın, et al. "Optimizing stereo-to-multiview conversion for autostereoscopic displays." Computer Graphics Forum 33, no. 2 (2014): 63–72. http://dx.doi.org/10.1111/cgf.12291.

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3

Gu, Yi, and Kang Li. "Entropy-Based Multiview Data Clustering Analysis in the Era of Industry 4.0." Wireless Communications and Mobile Computing 2021 (April 30, 2021): 1–8. http://dx.doi.org/10.1155/2021/9963133.

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In the era of Industry 4.0, single-view clustering algorithm is difficult to play a role in the face of complex data, i.e., multiview data. In recent years, an extension of the traditional single-view clustering is multiview clustering technology, which is becoming more and more popular. Although the multiview clustering algorithm has better effectiveness than the single-view clustering algorithm, almost all the current multiview clustering algorithms usually have two weaknesses as follows. (1) The current multiview collaborative clustering strategy lacks theoretical support. (2) The weight of
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Kanaan-Izquierdo, Samir, Andrey Ziyatdinov, Maria Araceli Burgueño, and Alexandre Perera-Lluna. "Multiview: a software package for multiview pattern recognition methods." Bioinformatics 35, no. 16 (2018): 2877–79. http://dx.doi.org/10.1093/bioinformatics/bty1039.

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Abstract Summary Multiview datasets are the norm in bioinformatics, often under the label multi-omics. Multiview data are gathered from several experiments, measurements or feature sets available for the same subjects. Recent studies in pattern recognition have shown the advantage of using multiview methods of clustering and dimensionality reduction; however, none of these methods are readily available to the extent of our knowledge. Multiview extensions of four well-known pattern recognition methods are proposed here. Three multiview dimensionality reduction methods: multiview t-distributed s
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Wang, Qingjun, Haiyan Lv, Jun Yue, and Eugene Mitchell. "Supervised multiview learning based on simultaneous learning of multiview intact and single view classifier." Neural Computing and Applications 28, no. 8 (2016): 2293–301. http://dx.doi.org/10.1007/s00521-016-2189-8.

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6

Shin, Hong-Chang, Jinwhan Lee, Gwangsoon Lee, and Namho Hur. "Stereo-To-Multiview Conversion System Using FPGA and GPU Device." Journal of Broadcast Engineering 19, no. 5 (2014): 616–26. http://dx.doi.org/10.5909/jbe.2014.19.5.616.

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7

Kuo, Pin-Chen, Kuan-Lun Lo, Huan-Kai Tseng, Kuan-Ting Lee, Bin-Da Liu, and Jar-Ferr Yang. "Stereoview to Multiview Conversion Architecture for Auto-Stereoscopic 3D Displays." IEEE Transactions on Circuits and Systems for Video Technology 28, no. 11 (2018): 3274–87. http://dx.doi.org/10.1109/tcsvt.2017.2732061.

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8

Pei, Jifang, Weibo Huo, Chenwei Wang, et al. "Multiview Deep Feature Learning Network for SAR Automatic Target Recognition." Remote Sensing 13, no. 8 (2021): 1455. http://dx.doi.org/10.3390/rs13081455.

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Multiview synthetic aperture radar (SAR) images contain much richer information for automatic target recognition (ATR) than a single-view one. It is desirable to establish a reasonable multiview ATR scheme and design effective ATR algorithm to thoroughly learn and extract that classification information, so that superior SAR ATR performance can be achieved. Hence, a general processing framework applicable for a multiview SAR ATR pattern is first given in this paper, which can provide an effective approach to ATR system design. Then, a new ATR method using a multiview deep feature learning netw
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Pei, Jifang, Zhiyong Wang, Xueping Sun, et al. "FEF-Net: A Deep Learning Approach to Multiview SAR Image Target Recognition." Remote Sensing 13, no. 17 (2021): 3493. http://dx.doi.org/10.3390/rs13173493.

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Synthetic aperture radar (SAR) is an advanced microwave imaging system of great importance. The recognition of real-world targets from SAR images, i.e., automatic target recognition (ATR), is an attractive but challenging issue. The majority of existing SAR ATR methods are designed for single-view SAR images. However, multiview SAR images contain more abundant classification information than single-view SAR images, which benefits automatic target classification and recognition. This paper proposes an end-to-end deep feature extraction and fusion network (FEF-Net) that can effectively exploit r
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Guo, Peng, Guoqi Xie, and Renfa Li. "Object Detection Using Multiview CCA-Based Graph Spectral Learning." Journal of Circuits, Systems and Computers 29, no. 02 (2019): 2050022. http://dx.doi.org/10.1142/s021812662050022x.

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Recent years have witnessed a surge of interest in semi-supervised learning-based object detection. Object detection is usually accomplished by classification methods. Different from conventional methods, those usually adopt a single feature view or concatenate multiple features into a long feature vector, multiview graph spectral learning can attain simultaneously object classification and weight learning of multiview. However, most existing multiview graph spectral learning (GSL) methods are only concerned with the complementarities between multiple views but not with correlation information
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Solimene, Raffaele, Aniello Buonanno, and Rocco Pierri. "Localization of small PEC spheres by multiview/single-frequency data." Near Surface Geophysics 6, no. 6 (2008): 371–79. http://dx.doi.org/10.3997/1873-0604.2008025.

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12

Rioja, M., R. Dodson, G. Orosz, and H. Imai. "MultiView High Precision VLBI Astrometry at Low Frequencies." Proceedings of the International Astronomical Union 13, S336 (2017): 439–42. http://dx.doi.org/10.1017/s1743921317010560.

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AbstractObservations at low frequencies (<8GHz) are dominated by distinct direction dependent ionospheric propagation errors, which place a very tight limit on the angular separation of a suitable phase referencing calibrator and astrometry. To increase the capability for high precision astrometric measurements an effective calibration strategy of the systematic ionospheric propagation effects that is widely applicable is required. The MultiView technique holds the key to the compensation of atmospheric spatial-structure errors, by using observations of multiple calibrators and two dimensio
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Sahin, Erdem, Suren Vagharshakyan, Robert Bregovic, Gwangsoon Lee, and Atanas Gotchev. "Conversion of sparsely-captured light field into alias-free full-parallax multiview content." Electronic Imaging 2018, no. 4 (2018): 144–1. http://dx.doi.org/10.2352/issn.2470-1173.2018.04.sda-144.

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14

Schaffner, Michael, Frank K. Gurkaynak, Pierre Greisen, Hubert Kaeslin, Luca Benini, and Aljosa Smolic. "Hybrid ASIC/FPGA System for Fully Automatic Stereo-to-Multiview Conversion Using IDW." IEEE Transactions on Circuits and Systems for Video Technology 26, no. 11 (2016): 2093–108. http://dx.doi.org/10.1109/tcsvt.2015.2501640.

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15

Sabah, Ali, Sabrina Tiun, Nor Samsiah Sani, Masri Ayob, and Adil Yaseen Taha. "Enhancing web search result clustering model based on multiview multirepresentation consensus cluster ensemble (mmcc) approach." PLOS ONE 16, no. 1 (2021): e0245264. http://dx.doi.org/10.1371/journal.pone.0245264.

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Existing text clustering methods utilize only one representation at a time (single view), whereas multiple views can represent documents. The multiview multirepresentation method enhances clustering quality. Moreover, existing clustering methods that utilize more than one representation at a time (multiview) use representation with the same nature. Hence, using multiple views that represent data in a different representation with clustering methods is reasonable to create a diverse set of candidate clustering solutions. On this basis, an effective dynamic clustering method must consider combin
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Cayoren, M., I. Akduman, A. Yapar, and L. Crocco. "Shape Reconstruction of Perfectly Conducting Targets From Single-Frequency Multiview Data." IEEE Geoscience and Remote Sensing Letters 5, no. 3 (2008): 383–86. http://dx.doi.org/10.1109/lgrs.2008.916075.

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17

Vizsnyiczai, Gaszton, András Búzás, Badri Lakshmanrao Aekbote, et al. "Multiview microscopy of single cells through microstructure-based indirect optical manipulation." Biomedical Optics Express 11, no. 2 (2020): 945. http://dx.doi.org/10.1364/boe.379233.

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18

Peng, Jiansheng, Kui Fu, Qingjin Wei, Yong Qin, and Qiwen He. "Improved Multiview Decomposition for Single-Image High-Resolution 3D Object Reconstruction." Wireless Communications and Mobile Computing 2020 (December 26, 2020): 1–14. http://dx.doi.org/10.1155/2020/8871082.

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As a representative technology of artificial intelligence, 3D reconstruction based on deep learning can be integrated into the edge computing framework to form an intelligent edge and then realize the intelligent processing of the edge. Recently, high-resolution representation of 3D objects using multiview decomposition (MVD) architecture is a fast reconstruction method for generating objects with realistic details from a single RGB image. The results of high-resolution 3D object reconstruction are related to two aspects. On the one hand, a low-resolution reconstruction network represents a go
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Alfaqheri, Taha, Akuha Solomon Aondoakaa, Mohammad Rafiq Swash, and Abdul Hamid Sadka. "Low-delay single holoscopic 3D computer-generated image to multiview images." Journal of Real-Time Image Processing 17, no. 6 (2020): 2015–27. http://dx.doi.org/10.1007/s11554-020-00991-y.

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Abstract Due to the nature of holoscopic 3D (H3D) imaging technology, H3D cameras can capture more angular information than their conventional 2D counterparts. This is mainly attributed to the macrolens array which captures the 3D scene with slightly different viewing angles and generates holoscopic elemental images based on fly’s eyes imaging concept. However, this advantage comes at the cost of decreasing the spatial resolution in the reconstructed images. On the other hand, the consumer market is looking to find an efficient multiview capturing solution for the commercially available autost
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Liu, Cuiwei, Zhaokui Li, Xiangbin Shi, and Chong Du. "Learning a Mid-Level Representation for Multiview Action Recognition." Advances in Multimedia 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/3508350.

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Recognizing human actions in videos is an active topic with broad commercial potentials. Most of the existing action recognition methods are supposed to have the same camera view during both training and testing. And thus performances of these single-view approaches may be severely influenced by the camera movement and variation of viewpoints. In this paper, we address the above problem by utilizing videos simultaneously recorded from multiple views. To this end, we propose a learning framework based on multitask random forest to exploit a discriminative mid-level representation for videos fro
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Castro, F. M., M. J. Marín-Jiménez, N. Guil Mata, and R. Muñoz-Salinas. "Fisher Motion Descriptor for Multiview Gait Recognition." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 01 (2017): 1756002. http://dx.doi.org/10.1142/s021800141756002x.

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The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on densely sampled short-term trajectories. We take advantage of state-of-the-art people detectors to define custom spatial configurations of the descriptors around the target person, obtaining a rich representation of the gait motion. The local motion features (described by the Divergence-Curl-Shear descriptor [M. Jain, H. Jegou and P. Bouthemy, Better exploiting motion for bett
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22

Johnston, K. B., S. M. Caballero-Nieves, V. Petit, A. M. Peter, and R. Haber. "Variable star classification using multiview metric learning." Monthly Notices of the Royal Astronomical Society 491, no. 3 (2019): 3805–19. http://dx.doi.org/10.1093/mnras/stz3165.

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ABSTRACT Comprehensive observations of variable stars can include time domain photometry in a multitude of filters, spectroscopy, estimates of colour (e.g. U-B), etc. When the objective is to classify variable stars, traditional machine learning techniques distill these various representations (or views) into a single feature vector and attempt to discriminate among desired categories. In this work, we propose an alternative approach that inherently leverages multiple views of the same variable star. Our multiview metric learning framework enables robust characterization of star categories by
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Chandler, Talon, Shalin Mehta, Hari Shroff, Rudolf Oldenbourg, and Patrick J. La Rivière. "Single-fluorophore orientation determination with multiview polarized illumination: modeling and microscope design." Optics Express 25, no. 25 (2017): 31309. http://dx.doi.org/10.1364/oe.25.031309.

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24

Jin, Yi, Jiuwen Cao, Qiuqi Ruan, and Xueqiao Wang. "Cross-Modality 2D-3D Face Recognition via Multiview Smooth Discriminant Analysis Based on ELM." Journal of Electrical and Computer Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/584241.

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In recent years, 3D face recognition has attracted increasing attention from worldwide researchers. Rather than homogeneous face data, more and more applications require flexible input face data nowadays. In this paper, we propose a new approach for cross-modality 2D-3D face recognition (FR), which is called Multiview Smooth Discriminant Analysis (MSDA) based on Extreme Learning Machines (ELM). Adding the Laplacian penalty constrain for the multiview feature learning, the proposed MSDA is first proposed to extract the cross-modality 2D-3D face features. The MSDA aims at finding a multiview lea
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Kim, Joohyung, Janghun Hyeon, and Nakju Doh. "Generative multiview inpainting for object removal in large indoor spaces." International Journal of Advanced Robotic Systems 18, no. 2 (2021): 172988142199654. http://dx.doi.org/10.1177/1729881421996544.

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As interest in image-based rendering increases, the need for multiview inpainting is emerging. Despite of rapid progresses in single-image inpainting based on deep learning approaches, they have no constraint in obtaining color consistency over multiple inpainted images. We target object removal in large-scale indoor spaces and propose a novel pipeline of multiview inpainting to achieve color consistency and boundary consistency in multiple images. The first step of the pipeline is to create color prior information on masks by coloring point clouds from multiple images and projecting the color
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Wang, Ziqiang, Xia Sun, Lijun Sun, and Yuchun Huang. "Multiview Discriminative Geometry Preserving Projection for Image Classification." Scientific World Journal 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/924090.

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In many image classification applications, it is common to extract multiple visual features from different views to describe an image. Since different visual features have their own specific statistical properties and discriminative powers for image classification, the conventional solution for multiple view data is to concatenate these feature vectors as a new feature vector. However, this simple concatenation strategy not only ignores the complementary nature of different views, but also ends up with “curse of dimensionality.” To address this problem, we propose a novel multiview subspace le
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Preble, Stefan, Liang Cao, Ali Elshaari, Abdelsalam Aboketaf, and Donald Adams. "Single photon adiabatic wavelength conversion." Applied Physics Letters 101, no. 17 (2012): 171110. http://dx.doi.org/10.1063/1.4764068.

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28

Wan, Yong, Xiaoyu Zhang, Yongshou Dai, and Xiaolei Shi. "Research on a Method for Simulating Multiview Ocean Wave Synchronization Data by Networked SAR Satellites." Journal of Marine Science and Engineering 7, no. 6 (2019): 180. http://dx.doi.org/10.3390/jmse7060180.

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It is expected that the problem of the azimuth cutoff wavelength in single-satellite synthetic aperture radar (SAR) observations can be solved by means of the cooperative observation of networked SAR satellites. Multiview SAR wave synchronization data are required in the process. However, most of the current orbiting satellites are geosynchronous orbit satellites; the simultaneous observation by multiple SARs in the same sea area cannot be achieved, and multiview synchronization data cannot be obtained. Therefore, this paper studies the simulation of the multiview SAR wave synchronization data
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Saito, Toyohiro, Yuto Kobayashi, Keita Takahashi, and Toshiaki Fujii. "Displaying Real-World Light Fields With Stacked Multiplicative Layers: Requirement and Data Conversion for Input Multiview Images." Journal of Display Technology 12, no. 11 (2016): 1290–300. http://dx.doi.org/10.1109/jdt.2016.2594804.

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30

Bérubé-Lauzière, Yves, Matteo Crotti, Simon Boucher, Seyedrohollah Ettehadi, Julien Pichette, and Ivan Rech. "Prospects on Time-Domain Diffuse Optical Tomography Based on Time-Correlated Single Photon Counting for Small Animal Imaging." Journal of Spectroscopy 2016 (2016): 1–23. http://dx.doi.org/10.1155/2016/1947613.

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This paper discusses instrumentation based on multiview parallel high temporal resolution (<50 ps) time-domain (TD) measurements for diffuse optical tomography (DOT) and a prospective view on the steps to undertake as regards such instrumentation to make TD-DOT a viable technology for small animal molecular imaging. TD measurements provide information-richest data, and we briefly review the interaction of light with biological tissues to provide an understanding of this. This data richness is yet to be exploited to its full potential to increase the spatial resolution of DOT imaging and to
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Pimont, François, Maxime Soma, and Jean-Luc Dupuy. "Accounting for Wood, Foliage Properties, and Laser Effective Footprint in Estimations of Leaf Area Density from Multiview-LiDAR Data." Remote Sensing 11, no. 13 (2019): 1580. http://dx.doi.org/10.3390/rs11131580.

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The spatial distribution of Leaf Area Density (LAD) in a tree canopy has fundamental functions in ecosystems. It can be measured through a variety of methods, including voxel-based methods applied to LiDAR point clouds. A theoretical study recently compared the numerical errors of these methods and showed that the bias-corrected Maximum Likelihood Estimator was the most efficient. However, it ignored (i) wood volumes, (ii) vegetation sub-grid clumping, (iii) the instrument effective footprint, and (iv) was limited to a single viewpoint. In practice, retrieving LAD is not straightforward, becau
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Sase, I., T. Okinaga, M. Hoshi, G. W. Feigenson, and K. Kinosita. "Regulatory mechanisms of the acrosome reaction revealed by multiview microscopy of single starfish sperm." Journal of Cell Biology 131, no. 4 (1995): 963–73. http://dx.doi.org/10.1083/jcb.131.4.963.

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The acrosome reaction in many animals is a coupled reaction involving an exocytotic step and a dramatic change in cell shape. It has been proposed that these morphological changes are regulated by intracellular ions such as Ca2+ and H+. We report here simultaneous visualization, under a multiview microscope, of intracellular free Ca2+ concentration ([Ca2+]i), intracellular pH (pHi), and morphological changes in a single starfish sperm (Asterina pectinifera). [Ca2+]i and pHi were monitored with the fluorescent probes indo-1 and SNARF-1, respectively. The acrosome reaction was induced with ionom
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Guo, Jingwei, and Lihong Xu. "Automatic Segmentation for Plant Leaves via Multiview Stereo Reconstruction." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/9845815.

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This paper presented a new method for automatic plant point cloud acquisition and leaves segmentation. Quasi-dense point cloud of the plant is obtained from multiview stereo reconstruction based on surface expansion. In order to overcome the negative effects from complex natural light changes and to obtain a more accurate plant point cloud, the Adaptive Normalized Cross-Correlation algorithm is used in calculating the matching cost between two images, which is robust to radiometric factors and can reduce the fattening effect around boundaries. In the stage of segmentation for each single leaf,
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Liang, T. J., Y. C. Kuo, and J. F. Chen. "Single-stage photovoltaic energy conversion system." IEE Proceedings - Electric Power Applications 148, no. 4 (2001): 339. http://dx.doi.org/10.1049/ip-epa:20010436.

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Li, Yuanhang, Xinzhu Sang, Shujun Xing, Yanxin Guan, Shenwu Yang, and Binbin Yan. "Real-time volume data three-dimensional display with a modified single-pass multiview rendering method." Optical Engineering 59, no. 10 (2020): 1. http://dx.doi.org/10.1117/1.oe.59.10.102412.

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36

Lee, Harim, Y. J. Moon, Hyeonock Na, Soojeong Jang, and Jae-Ok Lee. "Are 3-D coronal mass ejection parameters from single-view observations consistent with multiview ones?" Journal of Geophysical Research: Space Physics 120, no. 12 (2015): 10,237–10,249. http://dx.doi.org/10.1002/2015ja021118.

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Ge, Shuguang, Xuesong Wang, Yuhu Cheng, and Jian Liu. "Cancer Subtype Recognition Based on Laplacian Rank Constrained Multiview Clustering." Genes 12, no. 4 (2021): 526. http://dx.doi.org/10.3390/genes12040526.

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Integrating multigenomic data to recognize cancer subtype is an important task in bioinformatics. In recent years, some multiview clustering algorithms have been proposed and applied to identify cancer subtype. However, these clustering algorithms ignore that each data contributes differently to the clustering results during the fusion process, and they require additional clustering steps to generate the final labels. In this paper, a new one-step method for cancer subtype recognition based on graph learning framework is designed, called Laplacian Rank Constrained Multiview Clustering (LRCMC).
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Roth, Lukas, Moritz Camenzind, Helge Aasen, et al. "Repeated Multiview Imaging for Estimating Seedling Tiller Counts of Wheat Genotypes Using Drones." Plant Phenomics 2020 (September 7, 2020): 1–20. http://dx.doi.org/10.34133/2020/3729715.

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Early generation breeding nurseries with thousands of genotypes in single-row plots are well suited to capitalize on high throughput phenotyping. Nevertheless, methods to monitor the intrinsically hard-to-phenotype early development of wheat are yet rare. We aimed to develop proxy measures for the rate of plant emergence, the number of tillers, and the beginning of stem elongation using drone-based imagery. We used RGB images (ground sampling distance of 3 mm pixel-1) acquired by repeated flights (≥ 2 flights per week) to quantify temporal changes of visible leaf area. To exploit the informati
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Zhu, Tiantian, Zhengqiu Weng, Lei Fu, and Linqi Ruan. "A Web Shell Detection Method Based on Multiview Feature Fusion." Applied Sciences 10, no. 18 (2020): 6274. http://dx.doi.org/10.3390/app10186274.

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Web shell is a malicious script file that can harm web servers. Web shell is often used by intruders to perform a series of malicious operations on website servers, such as privilege escalation and sensitive information leakage. Existing web shell detection methods have some shortcomings, such as viewing a single network traffic behavior, using simple signature comparisons, and adopting easily bypassed regex matches. In view of the above deficiencies, a web shell detection method based on multiview feature fusion is proposed based on the PHP language web shell. Firstly, lexical features, synta
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Kim, Kwang-Seop, Jung-Min Kwon, and Bong-Hwan Kwon. "Single-Switch Single Power-Conversion PFC Converter Using Regenerative Snubber." IEEE Transactions on Industrial Electronics 65, no. 7 (2018): 5436–44. http://dx.doi.org/10.1109/tie.2017.2774765.

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Hao, Yaojun, Peng Zhang, and Fuzhi Zhang. "Multiview Ensemble Method for Detecting Shilling Attacks in Collaborative Recommender Systems." Security and Communication Networks 2018 (October 11, 2018): 1–33. http://dx.doi.org/10.1155/2018/8174603.

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Faced with the evolving attacks in collaborative recommender systems, the conventional shilling detection methods rely mainly on one kind of user-generated information (i.e., single view) such as rating values, rating time, and item popularity. However, these methods often suffer from poor precision when detecting different attacks due to ignoring other potentially relevant information. To address this limitation, in this paper we propose a multiview ensemble method to detect shilling attacks in collaborative recommender systems. Firstly, we extract 17 user features by considering the temporal
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Senthilnathan, R., R. Anand, Roshan Suresh Kumar, and Shreyansh Keseri. "A Mechatronics Approach for Design of Multiview Image Acquisition Setup for Scene Reconstruction with Single Camera." Applied Mechanics and Materials 852 (September 2016): 776–81. http://dx.doi.org/10.4028/www.scientific.net/amm.852.776.

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Conventional design approach is being actively replaced by concurrent design approach in the context of interdisciplinary systems. The proposed research work intends to develop a single moving camera based stereo vision system for scene reconstruction with the intrinsic advantage of multi-directional fields of view. The conventional stereo vision setup uses two stationary passive cameras to capture images of a scene from different vantage points. The proposed system imparts varying mechanical degrees of freedom motion for both the object and the camera which aids in acquiring sequence of image
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Bouchard, Jonathan, Arnaud Samson, William Lemaire, et al. "A Low-Cost Time-Correlated Single Photon Counting System for Multiview Time-Domain Diffuse Optical Tomography." IEEE Transactions on Instrumentation and Measurement 66, no. 10 (2017): 2505–15. http://dx.doi.org/10.1109/tim.2017.2666458.

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44

Wang, H. H., J. Y. Huang, S. H. Chu, Y. J. Chiang, K. L. Liu, and P. C. Lai. "Sirolimus Conversion Experience in a Single Center." Transplantation Proceedings 40, no. 7 (2008): 2209–10. http://dx.doi.org/10.1016/j.transproceed.2008.07.052.

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Watanabe, Wataru, Tomoko Shimada, Sachihiro Matsunaga, et al. "Single-organelle tracking by two-photon conversion." Optics Express 15, no. 5 (2007): 2490. http://dx.doi.org/10.1364/oe.15.002490.

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46

Flack, H. D., E. Blanc, and D. Schwarzenbach. "DIFRAC, single-crystal diffractometer output-conversion software." Journal of Applied Crystallography 25, no. 3 (1992): 455–59. http://dx.doi.org/10.1107/s0021889892000384.

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47

Tao, Wang, and Liu Yang. "Multiview Community Discovery Algorithm via Nonnegative Factorization Matrix in Heterogeneous Networks." Mathematical Problems in Engineering 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/8596893.

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With the rapid development of the Internet and communication technologies, a large number of multimode or multidimensional networks widely emerge in real-world applications. Traditional community detection methods usually focus on homogeneous networks and simply treat different modes of nodes and connections in the same way, thus ignoring the inherent complexity and diversity of heterogeneous networks. It is challenging to effectively integrate the multiple modes of network information to discover the hidden community structure underlying heterogeneous interactions. In our work, a joint nonneg
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Itoh, R., K. Ishizaka, H. Oishi, and H. Okada. "Single-switch single-phase rectifier for step-down AC-DC conversion." Electronics Letters 37, no. 5 (2001): 276. http://dx.doi.org/10.1049/el:20010219.

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49

Xiao, Yang, Zhiguo Cao, Wen Zhuo, Liang Ye, and Lei Zhu. "mCLOUD: A Multiview Visual Feature Extraction Mechanism for Ground-Based Cloud Image Categorization." Journal of Atmospheric and Oceanic Technology 33, no. 4 (2016): 789–801. http://dx.doi.org/10.1175/jtech-d-15-0015.1.

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AbstractIn this paper, a novel Multiview CLOUD (mCLOUD) visual feature extraction mechanism is proposed for the task of categorizing clouds based on ground-based images. To completely characterize the different types of clouds, mCLOUD first extracts the raw visual descriptors from the views of texture, structure, and color simultaneously, in a densely sampled way—specifically, the scale invariant feature transform (SIFT), the census transform histogram (CENTRIST), and the statistical color features are extracted, respectively. To obtain a more descriptive cloud representation, the feature enco
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Tay, Chee Wei, Liang Shen, Mikael Hartman, Shridhar Ganpathi Iyer, Krishnakumar Madhavan, and Stephen Kin Yong Chang. "SILC for SILC: Single Institution Learning Curve for Single-Incision Laparoscopic Cholecystectomy." Minimally Invasive Surgery 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/381628.

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Objectives. We report the single-incision laparoscopic cholecystectomy (SILC) learning experience of 2 hepatobiliary surgeons and the factors that could influence the learning curve of SILC.Methods. Patients who underwent SILC by Surgeons A and B were studied retrospectively. Operating time, conversion rate, reason for conversion, identity of first assistants, and their experience with previous laparoscopic cholecystectomy (LC) were analysed. CUSUM analysis is used to identify learning curve.Results. Hundred and nineteen SILC cases were performed by Surgeons A and B, respectively. Eight cases
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