Human verification and activity analysis(HVAA)are primarily employed to observe,track,and monitor human motion patterns using redgreen-blue(RGB)images and *** human interaction using RGB images is one of the most comp...
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Human verification and activity analysis(HVAA)are primarily employed to observe,track,and monitor human motion patterns using redgreen-blue(RGB)images and *** human interaction using RGB images is one of the most complex machine learning tasks in recent *** models rely on various parameters,such as the detection rate,position,and direction of human body components in RGB *** paper presents robust human activity analysis for event recognition via the extraction of contextual intelligence-based *** use human interaction image sequences as input data,we first perform a few denoising ***,human-to-human analyses are employed to deliver more precise *** phase follows feature engineering techniques,including diverse feature ***,we used the graph mining method for feature optimization and AdaBoost for *** tested our proposed HVAA model on two benchmark *** testing of the proposed HVAA system exhibited a mean accuracy of 92.15%for the Sport Videos in theWild(SVW)*** second benchmark dataset,UT-interaction,had a mean accuracy of 92.83%.Therefore,these results demonstrated a better recognition rate and outperformed other novel techniques in body part tracking and event *** proposed HVAA system can be utilized in numerous real-world applications including,healthcare,surveillance,task monitoring,atomic actions,gesture and posture analysis.
Federated Learning (FL) is vulnerable to backdoor attacks through data poisoning if the data is not scrutinized, as malicious participants can inject backdoor triggers in normal samples, leading to poisoned updates. D...
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Two compact substrate-integrated waveguide (SIW) filters with hybrid coupling of eighth-mode substrate integrated waveg-uide (EMSIW) resonators and microstrip are proposed in this paper. Hybrid coupled filters were ac...
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To address the problem of low repair efficiency of single- and double-disk of localized horizontal array code, this paper retains the original advantages of horizontal array code, transforms it on the basis of RDP 2D ...
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In recent years, the method of using graph neural networks (GNN) to learn users’ social influence has been widely applied to social recommendation and has shown effectiveness, but several important challenges have no...
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With the rapid development of the Internet technology,millimeter wave(mmWave)will be used as a supplement to 5G low frequency bands to meet the extremely high system capacity requirements of 5G in hot *** 5G mmWave co...
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With the rapid development of the Internet technology,millimeter wave(mmWave)will be used as a supplement to 5G low frequency bands to meet the extremely high system capacity requirements of 5G in hot *** 5G mmWave communication can adapt to the needs of 5G network and carry a large amount of transmitted data,transmission stability has become one of the key technical issues of 5G network mmWave communication due to problems such as strong attenuation and poor penetration of *** order to improve the efficiency of the mmWave multi-hop transmission,we propose a 5G mmWave multi-hop transmission method based on network coding,which can adapt to the current wireless network environment,improve spectrum efficiency and increase network *** on MATLAB simulation experiments,it is verified that the proposed method can greatly improve the transmission efficiency and reduce the signal loss under the premise of ensuring the accurate signal transmission.
Samples collected from most industrial processes have two challenges: one is contaminated by the non-Gaussian noise, and the other is gradually *** feature can obviously reduce the accuracy and generalization of model...
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Samples collected from most industrial processes have two challenges: one is contaminated by the non-Gaussian noise, and the other is gradually *** feature can obviously reduce the accuracy and generalization of models. To handle these challenges, a novel method, named the robust online extreme learning machine(RO-ELM), is proposed in this paper, in which the least mean p-power criterion is employed as the cost function which is to boost the robustness of the ELM, and the forgetting mechanism is introduced to discard the obsolescence samples. To investigate the performance of the ROELM, experiments on artificial and real-world datasets with the non-Gaussian noise are performed, and the datasets are from regression or classification problems. Results show that the RO-ELM is more robust than the ELM, the online sequential ELM(OS-ELM) and the OSELM with forgetting mechanism(FOS-ELM). The accuracy and generalization of the RO-ELM models are better than those of other models for online learning.
Facial Emotion recognition (FER) is a significant research domain in computer vision. FER is considered a challenging task due to emotion-related differences such as heterogeneity of human faces, differences in images...
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In the real-time scheduling theory,schedulability and synchronization analyses are used to evaluate scheduling algorithms and real-time locking protocols,respectively,and the empirical synthesis experiment is one of t...
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In the real-time scheduling theory,schedulability and synchronization analyses are used to evaluate scheduling algorithms and real-time locking protocols,respectively,and the empirical synthesis experiment is one of the major methods to compare the performance of such ***,since many sophisticated techniques have been adopted to improve the analytical accuracy,the implementation of such analyses and experiments is often *** paper proposes a schedulability experiment toolkit for multiprocessor real-time systems(SET-MRTS),which provides a framework with infrastructures to implement the schedulability and synchronization analyses and the deployment of empirical synthesis ***,with well-designed peripheral components for the input and output,experiments can be conducted easily and flexibly on *** demonstration further proves the effectiveness of SET-MRTS in both functionality and availability.
Facial emotion detection is a technique for identifying human emotions from facial expressions. Autism Spectrum Disorder is an advanced neurobehavioral disorder, autism is a vast field with many problems, including hy...
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