1,720,954 research outputs found
Deep Learning-Based Video Prediction
Get PDFThe task of video prediction is to generate unseen future video frames based on the past ones. It is an emerging, yet challenging task due to its inherent uncertainty and complex spatiotemporal dynamics. The ability to predict and anticipate future events from video prediction has applications in various prediction systems like self-driving cars, weather forecasting, traffic flow prediction, video compression etc. Due to the success of deep learning in the computer vision field, several deep learning Artificial Intelligence (AI) architectures such as convolutional neural networks (CNNs), long short-term memory (LSTMs), convolutional LSTMS (ConvLSTMs) and transformers have been explored to improve prediction accuracy. The internal representation, mainly the spatial correlations and temporal dynamics of the video, is learned and used to predict the next frames in deep learning-based video prediction. Several state-of-the-art deep learning methods have achieved superior video prediction accuracy at the expense of huge computational cost. In the light of recent wide popularity of Green AI which aims for efficient environment friendly solutions alongside accuracy, this research concentrates on efficient methods for video prediction. Such methods are suitable for memory-constrained and computation resource-limited platforms, such as mobile and embedded devices. We focus on CNN/LSTM methods and transformer-based architectures with fewer parameters for our lightweight efficient environment-friendly video prediction techniques. We conducted experimental studies on popular video prediction datasets and compared to existing methods, our proposed methods achieved competitive frame prediction accuracy with significantly reduced model size, trainable parameters, and computational complexity
Video forgery detection
No full textDigital image and videos cannot be taken as authentic evidences, since their
integrity is no longer trustworthy. Because of the uniqueness and peculiarities of
video signals with respect to images, there are wider ranges of possible alterations
that can be applied on video signals. So detection of video forgery has become a
critical requirement to ensure integrity of video data. We examined currently
available image and video forgery detection methods and introduced our own
methods. This thesis presents our efforts to understand and improve video forgery
detection methods. Firstly, a supervised image splicing detection method, which
makes use of statistical moment features, is extended to find forgery in videos. Its
limitations are discussed and a subset of those features is used for our next section
of unsupervised methods. An unsupervised video forgery detection method based
on suitable subset of statistical moment features and normalized cross correlation
factor is proposed. The location of duplicated block is also found using the
algorithm. Its advantages, limitations and comparisons with existing methods is
also given. Finally, a semi-supervised video forgery detection method, which is
based on feature similarity index, is also proposed. The index, primarily made for
image quality assessment, is used for finding duplication among the frames in a
video sequence. Experimental results for the three methods are discussed. Detailed
literature review and the possible future work on the related research area are also
discussed in the thesis.Master of Engineering (SCE
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
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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