Urban environments face significant challenges due to deteriorating road pavements, affecting all transportation modes' safety and comfort. Traditional methods of road assessment are costly and infrequent, but adv...
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Shipping container based modular architectures provide design flexibility in data centers with building blocks to expand the network as and when needed. In this paper, high capacity Modular Data Center (MDC) network a...
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Advances in digitization and resource-sharing business models have created new opportunities for manufacturing companies, enhancing competitiveness and resilience. However, these benefits bring computational challenge...
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Aviation plays a crucial role in global transportation, providing an essential service for passengers and cargo and contributing significantly to economic growth and international connectivity. However, the increasing...
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Increased digitization leads to huge number of threats increasing along with it at faster pace. Deep fake videos and images generation may not require any computational device memory hardware or particular knowledge. ...
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ISBN:
(数字)9798331518578
ISBN:
(纸本)9798331518585
Increased digitization leads to huge number of threats increasing along with it at faster pace. Deep fake videos and images generation may not require any computational device memory hardware or particular knowledge. But the process of detecting the deep fake video and images is challenging. Many methods have been evolved in recent times for solving these challenges but the computational costis very high for the highly efficient model. Thus, the proposed deep fake network model architecture involves highly efficient technique for accurate detection of deep fake video and imageswhich is comprised of linear stack of Max pooling and convolution layers. Activation function and Lime Gradient Boosting Machine (Light GBM) are used for the detection of deep fake videos. The develop model has high level of accuracy when compared with other models such as Efficient net and Xception and the study has been validated for the performance based on deep fake detection challenge data set. The study achieved 94.56% accuracy and 92.34% precision using this data set. Additionally, the study analyses the facial manipulations in the real-world images and videos accurately using advanced computational intelligence.
Machine vision is the computer application of vision that enables machines to comprehend their surroundings. The use of machine vision systems in robots allows for more sophisticated and potent operation in real-world...
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ISBN:
(数字)9798331510886
ISBN:
(纸本)9798331510893
Machine vision is the computer application of vision that enables machines to comprehend their surroundings. The use of machine vision systems in robots allows for more sophisticated and potent operation in real-world applications, such as environmental exploration. In addition to the seafloor of the Unmanned Underwater Vehicle (UUV), a binocular machine active vision system has been used to recreate incomplete or unknown navigation maps. Four processing steps make up the system: frame capture, pre-processing, matching, and depth recovery, which is used to calculate the distance between the object and the system, stored in a relative depth matrix, and, lastly, updating the navigation map.
This research investigates the use of machine learning methods to forecast students' academic performance in a school setting. Students' data with behavioral, academic, and demographic details were used in imp...
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Secure Multiparty Computation (SMC) facilitates secure collaboration among multiple parties while safeguarding the privacy of their confidential data. This paper introduces a two-party quantum SMC protocol designed fo...
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The increasing demand in the VLSI technology is also proportionately increasing the threats to these ICs. Hardware Trojan is one such threat that once inserted into the chip can cause malfunctioning of the chip or deg...
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