1,720,988 research outputs found
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
Heart rate estimation from facial videos using nonlinear mode decomposition and improved consistency check
No full textRemote photoplethysmography (rPPG) is a non-contact and noninvasive way of measuring human physiological signals such as the heart rate using the subtle color changes of skin regions. Since the face of a person is generally visible, facial videos can be used for estimating the heart rate remotely. The rigid and non-rigid motions of the face and illumination variations are the main challenges that affect the accuracy of heart rate estimation. In this paper, we present a new method for estimating the heart rate of a person from the skin region of the facial video using nonlinear mode decomposition (NMD), which is a recently proposed blind source separation method and has been shown to be more robust to noise. We also propose a new method (history-based consistency check-HBCC) for selecting the best heart rate candidate after decomposition by minimizing a temporal cost function. Experiments on two datasets show that the proposed method (rPPG-NMD) achieves promising results as compared to several the state-of-the-art methods for rPPG-based heart rate estimation
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
Performance comparison of deep learning based face identification methods for video under adverse conditions
No full textFace identification is an important problem in computer vision, which has many application areas. Recently, a number of deep-learning-based face identification and verification methods have been proposed in the literature, which demonstrate remarkable results on large image and video databases. Although the databases used for training and testing deep-learning architectures contain illumination, head pose, and expression variations, they do not reflect the difficult distortions (such as blur and low resolution), which may be encountered when using data from various sources (e.g. surveillance cameras). In this work, our goal is to systematically compare the performance of recent deep-learning-based methods for face identification using video under challenging conditions. We evaluate three deep learning architectures OpenFace, VGGFace2, and ArcFace. The experimental results indicate that even the most successful deep-learning-based face identification methods show poor performance under challenging distortions on the images such as noise, blur and contrast variations. © 2019 IEEE
An Overview of Non-contact Photoplethysmography
Get PDFPhotoplethysmography (PPG) is a method which is used to extract physiological parameters such as heart pulse rate, respirotary rate, and their variation with respect to time by optically measuring the blood volume change in the tissue. Photoplethysmography methods can be categorized into two groups: contact and non-contact. An example of contact photoplethysmography is the fingertip pulse oximetre which is widely used in medical centers. In non-contact photoplethysmography, with the use of special or commonly used cameras, these parameters are extracted from the color changes especially around the face caused by heart beat. In this survey, we aimed to provide information about the important studies in the literature, as well as to introduce the areas for improvement
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
Hybrid face recognition under adverse conditions using appearance-based and dynamic features of smile expression
No full textAlthough recent deep-learning-based face recognition methods give remarkable accuracies on large databases, their performance has been shown to degrade under adverse conditions (e.g. severe illumination and contrast variations; blur and noise). Under such conditions, soft-biometric features such as facial dynamics are expected to increase the performance if they are used together with appearance-based features. We propose a novel hybrid face recognition, which uses appearance-based features extracted using deep convolutional networks and statistical facial dynamics features extracted from facial landmark positions during smile expression. We evaluated the performances of three different state-of-the-art pre-trained deep convolutional neural networks (DCNNs) under a variety of severe image distortions with different parameters. The experimental results show that, although the face recognition performance using only DCNN-based features drops significantly under adverse conditions, the utilization of facial dynamics features together with DCNN-based features can compensate for the performance loss and increase the accuracy significantly. We believe the proposed system can be useful when face recognition is performed using videos obtained from systems, which may contain blurry and noisy images with a wide range of illumination variations
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