Creating pixel-level ground-truth (GT) masks is quite costly for deep learning-based image segmentation. Specialists in areas such as anomaly detection and medical diagnostics face difficulties in producing many GT ma...
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Chiplet-based systems have become prominent in large systems-on-Chips (SoCs) as a means to mitigate increasing design costs. However, the integration of multiple chiplets introduces new challenges in the interconnecti...
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In recent years, there has been a proliferation of Internet of Things (IoT) devices, and so has been the attacks on them. In this paper we will propose a methodology to detect Distributed Denial of Service (DDoS) atta...
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Occurrence of crimes has been on the constant rise despite the emerging discoveries and advancements in the technological field in the past *** of the most tedious tasks is to track a suspect once a crime is *** most ...
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Occurrence of crimes has been on the constant rise despite the emerging discoveries and advancements in the technological field in the past *** of the most tedious tasks is to track a suspect once a crime is *** most of the crimes are committed by individuals who have a history of felonies,it is essential for a monitoring system that does not just detect the person’s face who has committed the crime,but also their ***,a smart criminal detection and identification system that makes use of the OpenCV Deep Neural Network(DNN)model which employs a Single Shot Multibox Detector for detection of face and an auto-encoder model in which the encoder part is used for matching the captured facial images with the criminals has been *** detection and extraction of the face in the image by face cropping,the captured face is then compared with the images in the *** comparison is performed by calculating the similarity value between each pair of images that are obtained by using the Cosine Similarity *** plotting the values in a graph to find the threshold value,we conclude that the confidence rate of the encoder model is 0.75 and above.
Challenged networks (CNs) contain resource-constrained nodes deployed in regions where human intervention is difficult. Opportunistic networks (OppNets) are CNs with no predefined source-to-destination paths. Due to t...
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In recent years, language models have undergone significant advancements with models like GPT-3, showcasing impressive abilities in natural language processing and generation. However, these models often experience fr...
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A Wireless Sensor Network(WSN)is constructed with numerous sensors over geographical *** basic challenge experienced while designing WSN is in increasing the network lifetime and use of low *** sensor nodes are resour...
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A Wireless Sensor Network(WSN)is constructed with numerous sensors over geographical *** basic challenge experienced while designing WSN is in increasing the network lifetime and use of low *** sensor nodes are resource constrained in nature,novel techniques are essential to improve lifetime of nodes in *** energy is considered as an important resource for sensor node which are battery powered *** WSN,energy is consumed mainly while data is being transferred among nodes in the *** research works are carried out focusing on preserving energy of nodes in the network and made network to live ***,this network is threatened by attacks like vampire attack where the network is loaded by fake ***,Dual Encoding Recurrent Neural network(DERNNet)is proposed for classifying the vampire nodes s node in the ***,the Grey Wolf Optimization(GWO)algorithm helps for transferring the data by determining best solutions to optimally select the aggregation points;thereby maximizing battery/lifetime of the network *** proposed method is evaluated with three standard approaches namely Knowledge and Intrusion Detection based Secure Atom Search Routing(KIDSASR),Risk-aware Reputation-based Trust(RaRTrust)model and Activation Function-based Trusted Neighbor Selection(AF-TNS)in terms of various *** existing methods may lead to wastage of energy due to vampire attack,which further reduce the lifetime and increase average energy consumed in the ***,the proposed DERNNet method achieves 31.4%of routing overhead,23%of end-to-end delay,78.6%of energy efficiency,94.8%of throughput,28.2%of average latency,92.4%of packet delivery ratio,85.2%of network lifetime,and 94.3%of classification accuracy.
Balance disorders pose a significant health concern, especially among the elderly, often leading to falls and a reduced quality of life. The TeleRehabilitation of Balance clinical and economic Decision Support System ...
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Federated Learning (FL), an emerging distributed Artificial Intelligence (AI) technique, is susceptible to jamming attacks during the wireless transmission of trained models. In this letter, we introduce a jamming att...
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Traditional Internet protocol networks cannot provide the service of selecting a secure path to transmit various types of data with specific security ***,to solve the“secure path transmission”problem,this paper firs...
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Traditional Internet protocol networks cannot provide the service of selecting a secure path to transmit various types of data with specific security ***,to solve the“secure path transmission”problem,this paper first proposes a search-transmit model for secure network path transmission,i.e.,to find a multi-attribute optimized path that meets the specific security requirements in the search phase,and then transmit the packets along the optimized path in the transmission ***,we propose a solution to the search-transmit *** idea of the solution is to use the particle swarm optimization algorithm to search for a secure path that meets the multi-attribute requirements and then set the source route on the router to control the packet ***,a prototype system based on network function virtualization is developed to evaluate the feasibility and performance of the proposed *** results show that the proposed solution outperforms existing algorithms in terms of performance.
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