1,720,972 research outputs found
Deep Convolutional Neural Network for Object Forgery Detection in Video
No full textMaster of Engineering- ECTalking of today’s digital revolution, where visual data is playing an imperative role, accessing,
processing, and sharing of most of the information is typically attained with the help of video.
These video sequences have shown their significance in various fields like news broadcasting,
legal trials in court rooms, and many more but the doctoring of authentic visual content has
made it uncertain to use as an evidence. Doctored video generation with a fast-growing rate
done by easily accessible editing software like Adobe Photoshop, filmora, etc. have proved to
be a major problem in maintaining its authenticity. The extent of forging is so vast that video
spoofs reach our electronic-mail in-boxes, WhatsApp, Facebook or any other social media
every minute and this fakery is totally indistinguishable that hence raise a demand for a new
versatile field to perceive any alteration. Video forgery detection aims at restoring the trust and
validating the authenticity by uncovering the counterfeits. But the traditional approaches used
so far to detect forgeries have faced difficulties like less accurate detection rate and more false
negatives. Nowadays, deep neural networks have been recognized as an effective technique in
eradicating such troubles by learning significant features. The increasing attempt of video
modification has drawn greater attention towards Deep Convolutional Neural Networks
(DCNN) for achieving better counterfeits recognition.The proposed work is about “Deep Convolutional Neural Network for Object Forgery
Detection in Video” that aims to detect forgery without requiring additional pre-embedded
information of the frame. The proposed DCNN consists of various neurons where weights and
biases are defined for individual neuron which helps the network to learn the data properly.
Unlike other pre-existing learning-techniques, the proposed algorithm classifies the forged
frames on the basis of correlation among them and the observed abnormalities using DCNN.
The decoders used for batch normalization of input improves the training swiftness. It leads to
an inordinate evidence in recognizing and discovering the fake regions. Simulation results are
obtained on MATLAB 2018a with NVIDIA Cuda Graphics with REWIND and GRIP dataset
which is rich in video inter-frame forgery effects. The outcomes so obtained with an average
accuracy of 99% shows the superiority of the proposed algorithm as compared to existing one.
The robustness of proposed algorithm is also tested on You Tube compressed video sequences.
Recurrent Neural Networks can be combined with DCNN to achieve comparatively remarkable
results in future.TIE
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
Machine Learning Based Saliency Algorithm For Image Forgery Classification And Localization
No full textkoamabayili/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
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