In the past few years,social media and online news platforms have played an essential role in distributing news content *** of the authenticity of news has become a major *** the COVID-19 outbreak,misinformation and f...
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In the past few years,social media and online news platforms have played an essential role in distributing news content *** of the authenticity of news has become a major *** the COVID-19 outbreak,misinformation and fake news were major sources of confusion and insecurity among the general *** the first quarter of the year 2020,around 800 people died due to fake news relevant to *** major goal of this research was to discover the best learning model for achieving high accuracy and performance.A novel case study of the Fake News Classification using ELECTRA model,which achieved 85.11%accuracy score,is thus reported in this *** addition to that,a new novel dataset called COVAX-Reality containing COVID-19 vaccine-related news has been *** the COVAX-Reality dataset,the performance of FNEC is compared to several traditional learning models i.e.,Support Vector Machine(SVM),Naive Bayes(NB),Passive Aggressive Classifier(PAC),Long Short-Term Memory(LSTM),Bi-directional LSTM(Bi-LSTM)and Bi-directional Encoder Representations from Transformers(BERT).For the evaluation of FNEC,standard metrics(Precision,Recall,Accuracy,and F1-Score)were utilized.
Increasing demand of high-speed connectivity has challenged the future technologies (5G/B5G) in terms of large bandwidth, ultralow latency, massive coverage, reliable connectivity and rapid deployment. Free space opti...
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With the emergence of network-centric data,social network graph publishing is conducive to data analysts to mine the value of social networks,analyze the social behavior of individuals or groups,implement personalized...
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With the emergence of network-centric data,social network graph publishing is conducive to data analysts to mine the value of social networks,analyze the social behavior of individuals or groups,implement personalized recommendations,and so ***,published social network graphs are often subject to re-identification attacks from adversaries,which results in the leakage of users’***-anonymity technology is widely used in the field of graph publishing,which is quite effective to resist re-identification ***,the current researches still exist some issues to be solved:the protection of directed graphs is less concerned than that of undirected graphs;the protection of graph structure is often ignored while achieving the protection of nodes’identities;the same protection is performed for different users,which doesn’t meet the different privacy requirements of ***,to address the above issues,a multi-level-degree anonymity(MLDA)scheme on directed social network graphs is proposed in this ***,node sets with different importance are divided by the firefly algorithm and constrained connectedness upper approximation,and they are performed different-degree anonymity protection to meet the different privacy requirements of ***,a new graph anonymity method is proposed,which achieves the addition and removal of edges with the help of fake *** addition,to improve the utility of the anonymized graph,a new edge cost criterion is proposed,which is used to select the most appropriate edge to be ***,to protect the community structure of the original graph as much as possible,fake nodes contained in a same community are merged prior to fake nodes contained in different *** results on real datasets show that the newly proposed MLDA scheme is effective to balance the privacy and utility of the anonymized graph.
Gesture recognition is an important way of human-computer interaction, improving gesture recognition rate is of great significance for human-computer interaction applications. To solve the problems of few categories a...
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Aspect-based sentiment analysis (ABSA) is a natural language processing (NLP) technique to determine the various sentiments of a customer in a single comment regarding different aspects. The increasing online data con...
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With the rapid increase of complexity and volume of 3D building models, industries such as digital games and computer-aided design face considerable challenges. One feasible solution is to generate low-polygon models ...
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In recent years, graph-based E-commerce Fraud detection methods have received more and more attention, but there are still some problems. Firstly, fraudulent users only account for a small part of active users, and th...
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Emotion recognition from facial expressions is an important research area in the field of artificial intelligence. In this study, a novel deep-learning model is proposed for emotion recognition from facial expressions...
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Finger vein biometrics have been extensively studied for the capability to detect aliveness,and the high security as intrinsic ***,vein pattern distortion caused by finger rotation degrades the performance of CNN in 2...
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Finger vein biometrics have been extensively studied for the capability to detect aliveness,and the high security as intrinsic ***,vein pattern distortion caused by finger rotation degrades the performance of CNN in 2D finger vein recognition,especially in a contactless *** address the finger posture variation problem,we propose a 3D finger vein verification system extracting axial rotation invariant *** efficient 3D finger vein reconstruction optimization model is proposed and several accelerating strategies are adopted to achieve real-time 3D reconstruction on an embedded *** main contribution in this paper is that we are the first to propose a novel 3D point-cloud-based endto-end neural network to extract deep axial rotation invariant feature,namely *** the network,the rotation problem is transformed to a permutation problem with the help of specially designed rotation ***,to validate the performance of the proposed network more rigorously and enrich the database resources for the finger vein recognition community,we built the largest publicly available 3D finger vein dataset with different degrees of finger rotation,namely the Large-scale Finger Multi-Biometric Database-3D Pose Varied Finger Vein(SCUT LFMB-3DPVFV)*** results on 3D finger vein datasets show that our 3DFVSNet holds strong robustness against axial rotation compared to other approaches.
The rise in Internet of Things (IoT) devices with inadequate resources resulted in the emergence of the fog-computing, an extension of the cloud computing paradigm. In cloud computing, the network edge contains all fo...
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