Cancer detection is critical for early diagnosis and treatment, and non-invasive imaging methods like microwave imaging have shown promise in this domain. This research presents a CNN-based machine learning model to i...
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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.
The proposed research presents a novel approach to Speech Audio Emotion Recognition, integrating a Multi-Layer Perceptron (MLP) classifier and advanced feature extraction methods. With the growing importance of emotio...
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Exploring the relationship between sample size and the performance of machine learning models in diagnosing cardiovascular diseases (CVD) aids in understanding the optimal data volume required to achieve reliable and ...
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Our research investigates the application of single-class Support Vector Machine (SVM) for anomaly detection, which is critical for predictive maintenance. The study utilizes real-world datasets to validate the effect...
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Pattern-based, password-based, and PIN-based authentication techniques are typically the most common among smartphone users. However, according to prior studies these authentication techniques are susceptible to keylo...
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Before the approach of Information Communication Innovations (ICT), social intelligent essentially happened inside restricted social limits, such as neighborhood geological regions. The later headways in communication...
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Real-time crowd monitoring plays a pivotal role in effectively managing public spaces and ensuring safety. This study investigates the fusion of IoT devices and the YOLO object detection model to accurately count crow...
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In this research provides a solution for optimizing routing path selection in Underwater Wireless Sensor Networks (UWSNs). The algorithm combines Namib Beetle Optimization (NBO) and Moth-Flame Optimization (MFO), inte...
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Invoice processing is a time-consuming and tedious task that can be automated using optical character recognition (OCR) technology. Tesseract is a popular open-source OCR engine that can be used to extract text from s...
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