This study presents an innovative approach that utilizes neural network-based techniques to address the Ordered Escape Routing (OER) *** OER problem holds a crucial position in integrated circuit design, requiring mul...
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The creation of binary and multi-classification models with the goal of accurately detecting and categorizing motor defects is important to study. This work explores how autoencoders can be used to apply self-supervis...
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With advancements in technology, the prevalence of image manipulation for deceptive purposes has increased. Detecting forgeries can pose a challenge, and current methods have limitations. However, computer programs ca...
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Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based *** thi...
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Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based *** this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and *** Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data *** this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare *** experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)*** experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.
Semantic segmentation is an important sub-task for many ***,pixel-level ground-truth labeling is costly,and there is a tendency to overfit to training data,thereby limiting the generalization *** domain adaptation can...
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Semantic segmentation is an important sub-task for many ***,pixel-level ground-truth labeling is costly,and there is a tendency to overfit to training data,thereby limiting the generalization *** domain adaptation can potentially address these problems by allowing systems trained on labelled datasets from the source domain(including less expensive synthetic domain)to be adapted to a novel target *** conventional approach involves automatic extraction and alignment of the representations of source and target domains *** limitation of this approach is that it tends to neglect the differences between classes:representations of certain classes can be more easily extracted and aligned between the source and target domains than others,limiting the adaptation over all ***,we address:this problem by introducing a Class-Conditional Domain Adaptation(CCDA)*** incorporates a class-conditional multi-scale discriminator and class-conditional losses for both segmentation and ***,they measure the segmentation,shift the domain in a classconditional manner,and equalize the loss over *** results demonstrate that the performance of our CCDA method matches,and in some cases,surpasses that of state-of-the-art methods.
Global trading is undergoing significant changes, necessitating modifications to the trading strategies. This study presents a newly developed cloud-based trading strategy that uses Amazon Web Services (AWS), machine ...
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Does an iOS app preserve a user's privacy? With the presence of 1.76 million apps on the App Store, Apple Inc. hosts the second largest online store than its counterfeit Android. iOS apps have gained enormous popu...
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Since packets are dropped when there is an insufficient connection between each of the sensor nodes in the network, a sensor node in a sensor network is unable to efficiently aggregate the data packets. Since each are...
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Over the last decade, deep learning has become one of the fastest-growing fields in computer science. It finds applications in several sectors, such as Healthcare, Agriculture, Financial Services, and Crime Investigat...
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Medicinal plants have been highly significant to the medical field in curing diseases, healing wounds, and treating the ill since ancient times. The production and supply of these medicinal plants, however, pose authe...
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