1,720,977 research outputs found
Weakly-Supervised Contrastive Learning in Path Manifold for Monte Carlo Image Reconstruction
No full textImage-space auxiliary features such as surface normal have significantly contributed to the recent success of Monte Carlo (MC) reconstruction networks. However, path-space features, another essential piece of light propagation, have not yet been sufficiently explored. Due to the curse of dimensionality, information flow between a regression loss and high-dimensional path-space features is sparse, leading to difficult training and inefficient usage of path-space features in a typical reconstruction framework. This paper introduces a contrastive manifold learning framework to utilize path-space features effectively. The proposed framework employs weakly-supervised learning that converts reference pixel colors to dense pseudo labels for light paths. A convolutional path-embedding network then induces a low-dimensional manifold of paths by iteratively clustering intra-class embeddings, while discriminating inter-class embeddings using gradient descent. The proposed framework facilitates path-space exploration of reconstruction networks by extracting low-dimensional yet meaningful embeddings within the features. We apply our framework to the recent image- and sample-space models and demonstrate considerable improvements, especially on the sample space.
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“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
Full text linkWe 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
Full text linkWe 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
렌더링 노이즈 제거를 위한 심층학습 기반 광선 클러스터링 방법
No full text학위논문(석사) - 한국과학기술원 : 전산학부, 2021.8,[iv, 31 p. :]Monte Carlo (MC) path tracing has been widely used to synthesize realistic images. However, it takes extensive time to render a high-quality image since it requires to sample numerous light paths for each pixel. Hence, MC image reconstruction methods have been actively studied to remove rendering noises and recover clean images. This study proposes a light path clustering framework to further improve MC image reconstruction. Though image-space features (e.g., surface normal, depth, texture maps) have significantly contributed to MC denoising, direct utilization of high-dimensional light paths has not yet been sufficiently explored. This paper proposes a contrastive manifold learning framework that reduces the dimensionality of path space for MC reconstruction models to exploit path-space features effectively. Conventional contrastive approaches utilize discrete data labels to discriminate and cluster the data. Yet, discrete and exact labeling for light paths remains ill-defined due to the continuity and complexity of path space. We circumvent this issue by weakly-supervised learningwe use reference pixel colors for continuous pseudo labeling. We apply our framework to the recent reconstruction models and demonstrate considerable improvements. This thesis is written on the basis of the journal published papers in which the current candidate participated as a first author [12].한국과학기술원 :전산학부
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
Depression and increased risk of nonalcoholic fatty liver disease in individuals with obesity
Full text linkAims: the longitudinal relationship between depression and the risk of nonalcoholic fatty liver disease (NAFLD) is uncertain. We examined: a) the association between depressive symptoms and incident hepatic steatosis (HS), both with and without liver fibrosis; and b) the influence of obesity on this association.
Methods: cohort of 142,005 Korean adults with neither HS nor excessive alcohol consumption at baseline were followed for up to 8.9 years. The validated Center for Epidemiologic Studies-Depression score (CES-D) was assessed at baseline, and subjects were categorized as non-depressed (a CES-D <8, reference) or depression (CES-D ≥16). HS was diagnosed by ultrasonography. Liver fibrosis was assessed by the fibrosis-4 index (FIB-4). Parametric proportional hazards models were used to estimate the adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs).
Results: during a median follow-up of 4.0 years, 27,810 people with incident HS and 134 with incident HS plus high FIB-4 were identified. Compared with the non-depressed category, the aHR (95% CIs) for incident HS was 1.24 (1.15-1.34) for CES-D ≥16 among obese individuals, and 1.00 (0.95-1.05) for CES-D ≥16 among non-obese individuals (P for interaction with obesity <0.001). The aHR (95% CIs) for developing HS plus high FIB-4 was 3.41 (1.33-8.74) for CES-D≥16 among obese individuals, and 1.22 (0.60-2.47) for CES-D≥16 among non-obese individuals (P for interaction =0.201).
Conclusions: depression was associated with an increased risk of incident HS and HS plus high probability of advanced fibrosis, especially among obese individuals
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