Journal ArticleDOI
A novel CNN based security guaranteed image watermarking generation scenario for smart city applications
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TLDR
A novel algorithm using synergetic neural networks for robustness and security of digital image watermarking is proposed, which obtains an optimal Peak Signal-to-noise ratio (PSNR) and can complete certain image processing operations with improved performance.About:
This article is published in Information Sciences.The article was published on 2019-04-01. It has received 233 citations till now. The article focuses on the topics: Watermark & Digital watermarking.read more
Citations
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Journal ArticleDOI
Blockchain-based authentication and authorization for smart city applications
TL;DR: In this article, the authors proposed a solution for distributed management of identity and authorization policies by leveraging on the blockchain technology to hold a global view of the security policies within the system, and integrating it in the FIWARE platform.
Journal ArticleDOI
Multiple features based approach for automatic fake news detection on social networks using deep learning
TL;DR: This paper introduces automatic fake news detection approach in chrome environment on which it can detect fake news on Facebook, and uses multiple features associated with Facebook account with some news content features to analyze the behavior of the account through deep learning.
Journal ArticleDOI
Blockchain-Assisted Secure Fine-Grained Searchable Encryption for a Cloud-Based Healthcare Cyber-Physical System
TL;DR: In comparison to existing decentralized fine-grained searchable encryption schemes, the proposed scheme has achieved a significant reduction in storage and computational cost for the secret key associated with users.
Journal ArticleDOI
Secure blockchain enabled Cyber–physical systems in healthcare using deep belief network with ResNet model
Gia Nhu Nguyen,Nin Ho Le Viet,Mohamed Elhoseny,Mohamed Elhoseny,K. Shankar,Brij B. Gupta,Brij B. Gupta,Ahmed A. Abd El-Latif +7 more
TL;DR: A secure intrusion, detection with blockchain based data transmission with classification model for CPS in healthcare sector, which achieves privacy and security and uses a multiple share creation (MSC) model for the generation of multiple shares of the captured image.
Journal ArticleDOI
Joint computation offloading and task caching for multi-user and multi-task MEC systems: reinforcement learning-based algorithms
Ibrahim A. Elgendy,Ibrahim A. Elgendy,Weizhe Zhang,Hui He,Brij B. Gupta,Brij B. Gupta,Ahmed A. Abd El-Latif +6 more
TL;DR: This study proposes an offloading model for a multi-user MEC system with multi-task, and an equivalent form of reinforcement learning is created where the state spaces are defined based on all possible solutions and the actions are defined on the basis of movement between the different states.
References
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Proceedings Article
ImageNet Classification with Deep Convolutional Neural Networks
TL;DR: The state-of-the-art performance of CNNs was achieved by Deep Convolutional Neural Networks (DCNNs) as discussed by the authors, which consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax.
Proceedings ArticleDOI
ImageNet: A large-scale hierarchical image database
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Proceedings ArticleDOI
Going deeper with convolutions
Christian Szegedy,Wei Liu,Yangqing Jia,Pierre Sermanet,Scott Reed,Dragomir Anguelov,Dumitru Erhan,Vincent Vanhoucke,Andrew Rabinovich +8 more
TL;DR: Inception as mentioned in this paper is a deep convolutional neural network architecture that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC14).
Journal ArticleDOI
Learning representations by back-propagating errors
TL;DR: Back-propagation repeatedly adjusts the weights of the connections in the network so as to minimize a measure of the difference between the actual output vector of the net and the desired output vector, which helps to represent important features of the task domain.
Proceedings ArticleDOI
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
TL;DR: RCNN as discussed by the authors combines CNNs with bottom-up region proposals to localize and segment objects, and when labeled training data is scarce, supervised pre-training for an auxiliary task, followed by domain-specific fine-tuning, yields a significant performance boost.
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