AI tool has become so useful and important for companies that it can either drive customers to a company or a company to a sale. This Recommendations Engine have become a crucial part of how to present the right recom...
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This study explores the application of machine learning (ML) to improve Indian payment systems, with a focus on AI-driven developments for tasks including fraud detection, transaction validation, and consumer behaviou...
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The 6G mobile communication system aims to provide vast connectivity, ultra-reliable low-latency communication (URLLC), and high Information rates to support advanced applications like IoT, augmented reality, and auto...
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Foreground segmentation is an important part of computer vision and has many useful applications, such as tracking objects and detecting anomalies. However, deep learning models often struggle with the difficult task ...
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Foreground segmentation is an important part of computer vision and has many useful applications, such as tracking objects and detecting anomalies. However, deep learning models often struggle with the difficult task of preserving small details when extracting features, which is crucial for accurately segmenting edges. To overcome this challenge, we have developed a new segmentation network with a cascading architecture. This innovative approach gradually incorporates finer details into higher-level features, continuously improving the segmentation results. We have thoroughly evaluated our method using the challenging CDnet2014 dataset, and it has shown exceptional performance with an impressive F-measure of 0.9868. This research demonstrates the potential of cascading networks to greatly improve foreground segmentation in computer vision applications, and it is completely original work.
The shortage of medical specialists across the globe poses a significant challenge, and there is a need for innovative solutions to address this gap. Biomedical imagery is a precious asset in the healthcare and life s...
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This paper introduces an automated grading system for mangoes, enhancing efficiency and accuracy compared to human-based methods. The system uses the Lion Assisted Firefly Algorithm (LA-FF) to extract the best feature...
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This study explores the effectiveness of integrating inquiry-based and gamified learning approaches in a flipped classroom environment to enhance problem-solving capabilities, social competence, and real-world applica...
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User identification is explored through EEG-based biometric analysis using different auditory stimuli, using the distinctiveness and security of EEG signals for reliable biometric authentication. The impact on system ...
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An Electrocardiogram (ECG) contributes significantly to early diagnosis and classification of heart diseases, arrhythmia which means irregular heart rate. Regrettably, the process became difficult due to asymmetric an...
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Harvesting mechanical energy from low-frequency, multidirectional daily vibrations have been considered as an excellent candidate to replace the conventional batteries in many fields. In order to achieve effectively h...
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