The ongoing development of intelligent ammunition has resulted in an expansion of the functions that such ammunition must perform, thereby increasing the demand for internal computing capabilities in both scale and co...
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ISBN:
(数字)9798350369151
ISBN:
(纸本)9798350369168
The ongoing development of intelligent ammunition has resulted in an expansion of the functions that such ammunition must perform, thereby increasing the demand for internal computing capabilities in both scale and complexity. In light of the diverse functional requirements, traditional single-processor architectures are inadequate to address the needs of these varied and complex tasks. Consequently, this article presents an integrated image processing and flight control technology based on an Asynchronous Multi-Processor (AMP) architecture. This approach consolidates two tasks with distinct requirements into a single module, effectively addressing the challenges associated with information exchange between tasks. The feasibility of this method has been validated through simulation testing.
vision-based Alarming rates of heart disease affect both sexes. Early warning of heart disease may be obtained by monitoring a variety of risk factors. This new technology is having a profound effect on healthcare sys...
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vision-based Alarming rates of heart disease affect both sexes. Early warning of heart disease may be obtained by monitoring a variety of risk factors. This new technology is having a profound effect on healthcare systems. As a result of the Internet of Things, we can now remotely monitor patients, gather data, and analyze it to provide superior treatment. However, there is a critical need to provide unique and state-of-the-art secure algorithms for speedy event processing and effective event identification. In this piece, we present a tetrolet ELGamal algorithm (TEA)-based machine learning based logistic Bayesian decision tree (LBDT) for predicting cardiac issues based on existing data saved in the cloud. In addition to providing a safe place to keep sensitive patient data, the cloud may be used as a reliable data source for educational purposes. Comparisons are made between the suggested (LBDT TEA) and other algorithms in terms of encrypting and decrypting times, as well as accuracy, precision, recall, and F-score.
Predictive analytics and automation with the Internet of Things (IoT) is a growing trend in supply chain management. The generation permits cost-efficient operations and organizations to reveal and control their suppl...
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Edge detection is one of the basic challenges in the field of computervision. The results of most existing methods now produce thick edges and background interference. The images generated by the network must be post...
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vision-based applications such as traffic management, public area surveillance, and environmental monitoring require clear and accurate visual data from cameras to provide better services to people. But foggy weather ...
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ISBN:
(数字)9798331519582
ISBN:
(纸本)9798331519599
vision-based applications such as traffic management, public area surveillance, and environmental monitoring require clear and accurate visual data from cameras to provide better services to people. But foggy weather and traffic pollution causes haze, dust, or smog to degrade image quality, and reduce visibility of the target area, and becomes a challenge to the reliability of the automated application in urban areas. They face some additional problems such as color distortion, non-uniform illumination, low light, and dense or nonhomogeneous haze. The learning-based methods outperform traditional image dehazing methods in complex real-world problems and utilize large image datasets, despite their notable performance, learning-based models can have high computation and may require wide-ranging training datasets. This paper discussed prior-based and deep learning-based image dehazing models to test the RESIDE dataset with indoor and outdoor hazy images. Further, objective evaluation metrics have been discussed that are being used to evaluate the quality of state-of-the-art methods. These methodologies help us to set up vision-based applications for smart cities and have shown great potential to enhance image quality affected by haze and low light.
As an important part of artificial intelligence technology, deep learning is widely used in various fields of contemporary society. The security of deep learning directly affects the effectiveness of its application i...
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A new 16-term simple 7D hyperchaotic system with three control parameters is constructed from a 5D hyperchaotic Yang system via nonlinear and linear state feedback strategies. The proposed system belongs to hidden att...
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Information about the wind situation is crucial for en-route air traffic controllers. In this paper, we compare several glyph designs for showing wind direction and speed by the means of an empirical study. The differ...
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ISBN:
(纸本)9789897584886
Information about the wind situation is crucial for en-route air traffic controllers. In this paper, we compare several glyph designs for showing wind direction and speed by the means of an empirical study. The different designs are based on arrows, wind barbs, and text. During the study, we are measuring response times and accuracy. Moreover, we collect evidence of the applicability of those designs in en-route air traffic control by qualitative feedback from air traffic controllers. Our findings suggest, that the often-used wind barbs are less suited for assessing wind speed and direction. Instead, a combination of arrow and text should be favored.
The welding seam tracking precision is one of the key factors to ensure welding qua ntity. However, when the operator manually manipulate the master robot to control the slave ro bot tracking welding seam used the mas...
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Applications in the field of augmented reality or robotics often require joint localisation and 6D pose estimation of multiple objects. However, most algorithms need one network per object class to be trained in order...
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