In this paper, we propose an algorithm that equips a drone with a monocular camera and a laser range finder to derive position measurements for smooth mission execution and return to the home position, even in situati...
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As ransomware evolves, traditional OS-based de-tection mechanisms face growing challenges, particularly from advanced attacks exploiting system vulnerabilities and escalating privileges. The continuous evolution of ra...
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This review examines the applications, challenges, and prospects of Faster Region-based Convolutional Neural Networks (Faster R-CNN) in healthcare and disease detection. Through a meta-analysis of Web of Science liter...
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In this paper, we propose a novel approach to median filtering, a widely employed technique for mitigating specific types of noise in images and signals. While median filtering is effective, its computational demands,...
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作者:
Kapse, RishikeshGourshettiwar, Palash
Faculty of Engineering and Technology Dept. of Artificial Intelligence and Data Science Maharashtra Wardha India
Faculty of Engineering and Technology Dept. of Computer Science And Medical Engineering Maharashtra Wardha India
This essay's primary focus is on Google Cloud's use in healthcare and how it affects data management, teamwork, and cost-effectiveness. With a focus on Google Cloud, which improves the processing, storing, and...
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Computed Tomography (CT) scanning offers 3D insights into the human body but involves higher radiation exposure than traditional X-Rays, increasing the relevance of 3D reconstructions from 2D data. In this work, datas...
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Barcode scanning errors in retail environments contribute to inventory discrepancies, financial losses, and inefficiencies in stock management. Traditional optical barcode scanning methods are prone to failures due to...
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Advancements in Natural Language to Structured Query Language (NL2SQL) systems are improving the accessibility of data stored in relational databases, making it easier for non-technical users to retrieve information u...
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The deepfake generation of singing vocals is a concerning issue for artists in the music industry. In this work, we propose a singing voice deepfake detection (SVDD) system, which uses noise-variant encodings of open-...
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While the mainstream research in anomaly detection has mainly followed the one-class classification, practical industrial environments often incur noisy training data due to annotation errors or lack of labels for new...
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