The boundaries and regions between individual classes in biomedical image classification are hazy and overlapping. These overlapping features make predicting the correct classification result for biomedical imaging da...
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The boundaries and regions between individual classes in biomedical image classification are hazy and overlapping. These overlapping features make predicting the correct classification result for biomedical imaging data a difficult diagnostic task. Thus, in precise classification, it is frequently necessary to obtain all necessary information before making a decision. This paper presents a novel deep-layered design architecture based on Neuro-Fuzzy-Rough intuition to predict hemorrhages using fractured bone images and head CT scans. To deal with data uncertainty, the proposed architecture design employs a parallel pipeline with rough-fuzzy layers. In this case, the rough-fuzzy function functions as a membership function, incorporating the ability to process rough-fuzzy uncertainty information. It not only improves the deep model's overall learning process, but it also reduces feature dimensions. The proposed architecture design improves the model's learning and self-adaptation capabilities. In experiments, the proposed model performed well, with training and testing accuracies of 96.77% and 94.52%, respectively, in detecting hemorrhages using fractured head images. The comparative analysis shows that the model outperforms existing models by an average of 2.6$\pm$0.90% on various performance metrics. IEEE
Video deblurring is a fundamental problem in low-level vision, and many methods have employed designs based on CNNs and transformers. Traditional CNNs often require deeper architectures to achieve a larger receptive f...
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The ever-growing amount of data generated by modern networks poses significant challenges for intrusion detection systems (IDS) in effectively analyzing and classifying security risks. Therefore, it is crucial to iden...
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The process of testing conventional programs is quite easy as compared to the programs using Deep Learning approach. The term Deep learning (DL) is used for a novel programming approach that is highly data centric and...
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In the global marketplace, agriculture plays an important role. However, diseases produced in plants mostly affect the financial system. Pest occurrence and climatic changes are the leading trouble that the banana pla...
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Software bug repositories stores a wealth of information related to the problems that occurred during the software development. Today’s software development is a modular approach, with multiple developers working in ...
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Android devices are popularly available in the commercial market at different price levels for various levels of *** Android stack is more vulnerable compared to other platforms because of its open-source *** are many...
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Android devices are popularly available in the commercial market at different price levels for various levels of *** Android stack is more vulnerable compared to other platforms because of its open-source *** are many android malware detection techniques available to exploit the source code andfind associated components during execution *** obtain a better result we create a hybrid technique merging static and dynamic *** this paper,in thefirst part,we have proposed a technique to check for correlation between features and classify using a supervised learning approach to avoid Mul-ticollinearity problem is one of the drawbacks in the existing *** the proposed work,a novel PCA(Principal Component Analysis)based feature reduction technique is implemented with conditional dependency features by gathering the functionalities of the application which adds novelty for the given *** Android Sensitive Permission is one major key point to be considered while detecting *** select vulnerable columns based on features like sensitive permissions,application program interface calls,services requested through the kernel,and the relationship between the variables henceforth build the model using machine learning classifiers and identify whether the given application is malicious or *** goal of this paper is to check benchmarking datasets collected from various repositories like virus share,Github,and the Canadian institute of cyber security,compare with models ensuring zero-day exploits can be monitored and detected with better accuracy rate.
As cryptocurrencies become more popular as investment vehicles, bitcoin draws interest from businesses, consumers, and computer scientists all across the world. Bitcoin is a computer file stored in digital wallet appl...
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The existing cloud model unable to handle abundant amount of Internet of Things (IoT) services placed by the end users due to its far distant location from end user and centralized nature. The edge and fog computing a...
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Stock market Prediction has been a topic of attention for numerous researchers since its beginning. Often traditional statistical methods get conflict to grab the complex, non-linear patterns in stock market data. Due...
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