Facial beauty analysis is an important topic in human *** may be used as a guidance for face beautification applications such as cosmetic *** neural networks(DNNs)have recently been adopted for facial beauty analysis ...
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Facial beauty analysis is an important topic in human *** may be used as a guidance for face beautification applications such as cosmetic *** neural networks(DNNs)have recently been adopted for facial beauty analysis and have achieved remarkable ***,most existing DNN-based models regard facial beauty analysis as a normal classification *** ignore important prior knowledge in traditional machine learning models which illustrate the significant contribution of the geometric features in facial beauty *** be specific,landmarks of the whole face and facial organs are introduced to extract geometric features to make the *** by this,we introduce a novel dual-branch network for facial beauty analysis:one branch takes the Swin Transformer as the backbone to model the full face and global patterns,and another branch focuses on the masked facial organs with the residual network to model the local patterns of certain facial ***,the designed multi-scale feature fusion module can further facilitate our network to learn complementary semantic information between the two *** model optimisation,we propose a hybrid loss function,where especially geometric regulation is introduced by regressing the facial landmarks and it can force the extracted features to convey facial geometric *** performed on the SCUT-FBP5500 dataset and the SCUT-FBP dataset demonstrate that our model outperforms the state-of-the-art convolutional neural networks models,which proves the effectiveness of the proposed geometric regularisation and dual-branch structure with the hybrid *** the best of our knowledge,this is the first study to introduce a Vision Transformer into the facial beauty analysis task.
Model performance has been significantly enhanced by channel attention. The average pooling procedure creates skewness, lowering the performance of the network architecture. In the channel attention approach, average ...
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Collaborative inference(co-inference) accelerates deep neural network inference via extracting representations at the device and making predictions at the edge server, which however might disclose the sensitive inform...
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Collaborative inference(co-inference) accelerates deep neural network inference via extracting representations at the device and making predictions at the edge server, which however might disclose the sensitive information about private attributes of users(e.g.,race). Although many privacy-preserving mechanisms on co-inference have been proposed to eliminate privacy concerns, privacy leakage of sensitive attributes might still happen during inference. In this paper, we explore privacy leakage against the privacy-preserving co-inference by decoding the uploaded representations into a vulnerable form. We propose a novel attack framework named AttrL eaks, which consists of the shadow model of feature extractor(FE), the susceptibility reconstruction decoder,and the private attribute classifier. Based on our observation that values in inner layers of FE(internal representation) are more sensitive to attack, the shadow model is proposed to simulate the FE of the victim in the blackbox scenario and generates the internal ***, the susceptibility reconstruction decoder is designed to transform the uploaded representations of the victim into the vulnerable form, which enables the malicious classifier to easily predict the private attributes. Extensive experimental results demonstrate that AttrLeaks outperforms the state of the art in terms of attack success rate.
Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms,as well as promoting the safe deployment of large language *** data is the ...
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Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms,as well as promoting the safe deployment of large language *** data is the basis for developing detectors;however,the available offense-related dataset in Chinese is severely limited in terms of data scale and coverage when compared to English *** significantly affects the accuracy of Chinese offensive language detectors in practical applications,especially when dealing with hard cases or out-of-domain *** alleviate the limitations posed by available datasets,we introduce AugCOLD(Augmented Chinese Offensive Language Dataset),a large-scale unsupervised dataset containing 1 million samples gathered by data crawling and model ***,we employ a multiteacher distillation framework to enhance detection performance with unsupervised *** is,we build multiple teachers with publicly accessible datasets and use them to assign soft labels to *** soft labels serve as a bridge for knowledge to be distilled from both AugCOLD and multiteacher to the student network,i.e.,the final offensive *** conduct experiments on multiple public test sets and our well-designed hard tests,demonstrating that our proposal can effectively improve the generalization and robustness of the offensive language detector.
Purpose–A cross-domain intelligent software-defined network(SDN)routing method based on a proposed multiagent deep reinforcement learning(MDRL)method is ***/methodology/approach–First,the network is divided into mul...
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Purpose–A cross-domain intelligent software-defined network(SDN)routing method based on a proposed multiagent deep reinforcement learning(MDRL)method is ***/methodology/approach–First,the network is divided into multiple subdomains managed by multiple local controllers,and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement ***,a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers,and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real ***,after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers,a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real ***–Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first(OSPF)routing methods Originality/value–Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds,coupled with the shortcomings of traditional interdomain routing methods,such as cumbersome configuration and inflexible acquisition of network state *** drawbacks make it difficult to obtain global state information about the network,and the optimal routing decision cannot be made in real time,affecting network *** paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL ***,the network
Effectively identifying and preventing the threat of Byzantine nodes to the security of distributed systems is a challenge in applying consortium ***,this paper proposes a new consortium chain generation model,deeply ...
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Effectively identifying and preventing the threat of Byzantine nodes to the security of distributed systems is a challenge in applying consortium ***,this paper proposes a new consortium chain generation model,deeply analyzes the vulnerability of the consortium chain consensus based on the behavior of the nodes,and points out the effects of Byzantine node proportion and node state verification on the consensus process and system ***,the normalized verification node aggregation index that represents the consensus ability of the consortium organization and the trust evaluation function of the verification node set is *** either of the two is lower than the threshold,the consortium institution or the verification node set members are dynamically *** this basis,an innovative consortium chain generation mechanism based on the Asynchronous Binary Byzantine Consensus Mechanism(ABBCM)is *** on the extended consortium chain consensus mechanism,a certain consensus value set can be combined into multiple proposals,which can realize crossdomain asynchronous message passing between multi-consortium chains without reducing the system’s *** addition,experiments are carried out under four classical Byzantine Attack(BA)behaviors,BA1 to *** results show that the proposed method can obtain better delay than the classical random Byzantine consensus algorithm Coin,effectively improving the consensus efficiency based on asynchronous message passing in the consortium chain and thus meeting the throughput of most Internet of Things(IoT)applications.
Internet of Vehicles (IoV) integrates with various heterogeneous nodes, such as connected vehicles, roadside units, etc., which establishes a distributed network. Vehicles are managed nodes providing all the services ...
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In smart phones,vehicles and wearable devices,GPS sensors are ubiquitous and collect a lot of valuable spatial data from the real *** a set of weighted points and a rectangle r in the space,a maximizing range sum(MaxR...
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In smart phones,vehicles and wearable devices,GPS sensors are ubiquitous and collect a lot of valuable spatial data from the real *** a set of weighted points and a rectangle r in the space,a maximizing range sum(MaxRS)query is to find the position of r,so as to maximize the total weight of the points covered by r(i.e.,the range sum).It has a wide spectrum of applications in spatial crowdsourcing,facility location and traffic *** of the existing research focuses on the Euclidean space;however,in real life,the user’s moving route is constrained by the road network,and the existing MaxRS query algorithms in the road network are *** this paper,we propose a novel GPU-accelerated algorithm,namely,GAM,to tackle MaxRS queries in road networks in two phases *** phase 1,we partition the entire road network into many small cells by a grid and theoretically prove the correctness of parallel query results by grid shifting,and then we propose an effective multi-grained pruning technique,by which the majority of cells can be pruned without further *** phase 2,we design a GPU-friendly storage structure,cell-based road network(CRN),and a two-level parallel framework to compute the final result in the remaining ***,we conduct extensive experiments on two real-world road networks,and the experimental results demonstrate that GAM is on average one order faster than state-of-the-art competitors,and the maximum speedup can achieve about 55 times.
Sharing of the electronic medical records among different hospitals raises serious concern of the leakage of individual privacy for the adoption of the semi trustworthiness of the medical cloud *** tracking and revoca...
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Sharing of the electronic medical records among different hospitals raises serious concern of the leakage of individual privacy for the adoption of the semi trustworthiness of the medical cloud *** tracking and revocation of malicious users have become urgent *** solve these problems,this paper proposed a traceable and directly revocable medical data sharing *** the scheme,a unique identity parameter(ID),which was generated and embedded in the private key generation phase by the medical service provider(MSP),is used to identify legal authorized user and trace malicious *** when attributes satisfy the access policy and user’s ID is not in the revocation list can the user calculate the decryption *** user can be tracked and directly revoked by using the revocation *** the assumption of decision bilinear Diffie-Hellman(DBDH),this paper has proved that the scheme is able to achieve security against chosen-plaintext attack(CPA).The performance analysis demonstrates that the sizes of the public key and private key are shorter,and the time overhead is less than other schemes in the public-private key generation,data encryption and data decryption stages.
With the development of high-performance computing and the expansion of large-scale multiprocessor sys-tems,it is significant to study the reliability of *** fault diagnosis is of practical value to the reliabilityana...
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With the development of high-performance computing and the expansion of large-scale multiprocessor sys-tems,it is significant to study the reliability of *** fault diagnosis is of practical value to the reliabilityanalysis of multiprocessor *** this paper,we design a linear time diagnosis algorithm with the multiprocessor sys-tem whose threshold is set to 3,where the probability that any node is correctly diagnosed in the discrete state can be ***,we give the probabilities that all nodes of a d-regular and d-connected graph can be correctly diag-nosed in the continuous state under the Weibull fault distribution and the Chi-square fault *** prove thatthey approach to 1,which implies that our diagnosis algorithm can correctly diagnose almost all nodes of the graph.
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