1,720,959 research outputs found
Video Matting Using Multi-frame Nonlocal Matting Laplacian
No full textWe present an algorithm for extracting high quality temporally coherent alpha mattes of objects from a video. Our approach extends the conventional image matting approach, i.e. closed-form matting, to video by using multi-frame nonlocal matting Laplacian. Our multi-frame nonlocal matting Laplacian is dened over a nonlocal neighborhood in spatial temporal domain, and it solves the alpha mattes of several video frames all together simultaneously. To speed up computation and to reduce memory requirement for solving the multi-frame nonlocal matting Laplacian, we use the approximate nearest neighbor(ANN) to nd the nonlocal neighborhood and the k-d tree implementation to divide the nonlocal matting Laplacian into several smaller linear systems. Finally, we adopt the nonlocal mean regularization to enhance temporal coherence of the estimated alpha mattes and to correct alpha matte errors at low contrast regions. We demonstrate the eectiveness of our approach on various examples with qualitative comparisons to the results from previous matting algorithms
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
계산 사진학을 위한 학습 기반 영상 복원
No full text학위논문(박사) - 한국과학기술원 : 전산학부, 2019.2,[iv, 83 p. :]The emergence of digital imaging made the photography available for everyone by lowering the cost of imaging devices and eliminating the costs of films and the development processes for them. Along with it, a novel imaging application field, so-called computational photography, was introduced by combining digital imaging and computing. Since it enables to enhance the quality of images and to fix flaws in photographs afterward shooting, computational photography has been playing an essential role in digital imaging.
At the core of computational photography, there is a technical challenge to solve a severely ill- posed optimization problem of inverse light transport. Computational photography algorithms need to overcome the mathematical challenge to achieve high-quality image output. With efforts of addressing the ill-posedness of the inverse optimization problem, many hand-crafted image priors have been commonly used to regulate the range of possible solutions, yielding plausible high-quality images. However, traditional approaches cannot handle the broad spectrum and diversity of real-world images.
In this thesis, I demonstrate three learning-based image reconstruction methods for computational photography, based on priors obtained by learning from image data: compressive hyperspectral imaging, high dynamic range (HDR) imaging, and novel view synthesis. First, for compressive hyperspectral imaging, I introduce a novel spectral prior, which is learned using a deep convolutional autoencoder. Second, for high dynamic range imaging, I adopt joint sparse coding to acquire a prior knowledge on HDR images. Finally, for the novel view synthesis method, I propose a new approach that combines a conventional view synthesis and a learning-based refinement using a convolutional neural network. Qualitative and quantitative comparisons demonstrate that the learned priors are highly effective in addressing each of the three problems, validating that the three proposed methods outperform state-of- the-art techniques with high image quality.한국과학기술원 :전산학부
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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