Target detection is one of the most important tasks in the field of computer vision to classify and locate targets in images or videos. This paper proposes a new algorithm for extracting feature knowledge. Designed to...
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The use of deep learning techniques for the purpose of improving fault detection in industrial machinery. It is of the utmost importance to have defect detection mechanisms that are both reliable and effective, since ...
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This study looks at how important it is to have a complete understanding of the IOTA coin and its market dynamics. The present study investigates the patterns and correlations present in the bitcoin market by analyzin...
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This paper presents a six-node system comprising two transmitter-receiver pairs, an eavesdropper, and a relay. It evaluates the security of the primary pair while the secondary uses jamming to protect against eavesdro...
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One of the top 10 major causes of death is the bacterial disease tuberculosis (TB), which is brought on by Mycobacterium tuberculosis. Acute pulmonary TB manifests as acute tuberculosis pneumonia (TP). Acute TP and no...
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As the global semiconductor industry moving towards successive generations, the density of Integrated Circuit increased, therefore reliability issues became critically high, among them Negative Bias Temperature Instab...
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The 5th generation of wireless technology with a continuum leap rushing towards the future in the world of communication has a puzzle that enables the autonomous machine to work in site making a louder voice that show...
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Wavefront reconstruction is a powerful technique for accurately restoring all information about an object, with holography being the most effective method for achieving this. In this paper, we propose a reflective hol...
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The optimal tuning of the PIDA (proportional-integral-derivative-accelerated) controller for the vehicle cruise control system (VCCS) by using the modified bat algorithm (MBA), one of the most powerful metaheuristic o...
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This study proposes a blind super-resolution (SR) method with degradation estimation, combining the DASR (Degradation-Aware SR) and CLIP models. Firstly, we employ unsupervised degradation representation learning to a...
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