Non-invasive brain-computer interface technology has been developed for detecting human mental states with high performances. Detection of the pilots' mental states is particularly critical because their abnormal ...
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ISBN:
(纸本)9781665464444
Non-invasive brain-computer interface technology has been developed for detecting human mental states with high performances. Detection of the pilots' mental states is particularly critical because their abnormal mental states could cause catastrophic accidents. In this study, we presented the feasibility of classifying distraction levels (namely, normal state, low distraction, and high distraction) by applying the deep learning method. To the best of our knowledge, this study is the first attempt to classify distraction levels under a flight environment. We proposed a model for classifying distraction levels. A total of ten pilots conducted the experiment in a simulated flight environment. The grand-average accuracy was 0.8437 (+/- 0.0287) for classifying distraction levels across all subjects. Hence, we believe that it will contribute significantly to autonomous driving or flight based on artificial intelligence technology in the future.
The development of computer vision technology in recent days, enhanced the human-computer interface (HCI) systems in a broad spectrum. The recent developments of human computer interfacing such as Augmented reality ap...
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As a cutting-edge development trend in the field of visualization, cloud rendering technology is currently dominated by game engine manufacturers. Cloud rendering technology based on WebGL engine has not yet been full...
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With the rapid development of computer vision technology, athlete posture recognition based on image analysis has become a research hotspot in the field of sports technology. This study proposes a new fusion boundary ...
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ISBN:
(纸本)9798400718144
With the rapid development of computer vision technology, athlete posture recognition based on image analysis has become a research hotspot in the field of sports technology. This study proposes a new fusion boundary filtering algorithm specifically for the posture recognition of volleyball players, aiming to improve the accuracy and real-time performance of posture recognition. Firstly, the preliminary posture information of athletes is extracted through a deep learning framework, and then this information is finely processed using boundary filtering technology to effectively filter out background noise and non-target interference. Compared with traditional posture recognition algorithms, this algorithm improves the recognition accuracy by 15% in complex backgrounds and also has significant advantages in real-time performance. Additionally, this study explores the adaptability of the algorithm in different lighting and multi-person scenarios, validating its potential application in actual sports competitions. Experimental results demonstrate that the fusion boundary filtering algorithm is an effective posture recognition technology for volleyball players, providing a theoretical basis and experimental evidence for further technological development and application.
The improvement of land engineering survey technology based on computer big data is closely related to the technical development. With the rapid development of computer information technology, the application of compu...
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Science and technology is the first driving force for the development of human society. With the continuous improvement of the current information technology industry, computertechnology provides an essential technic...
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Compared with soldering technology, metal particle sinter-joining technology can provide better thermodynamic performance and higher packaging reliability. It is considered one of the most promising technologies for a...
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ISBN:
(纸本)9798350353808
Compared with soldering technology, metal particle sinter-joining technology can provide better thermodynamic performance and higher packaging reliability. It is considered one of the most promising technologies for achieving interconnects with high reliability and heat resistance for wide-band gap semiconductor devices. However, sinter-jointed layers are usually porous structures, and the porosity inevitably affects the sinter-joints' thermal and mechanical properties. Compared with traditional unimodal metal particle pastes, multimodal particle pastes can reduce the sinter-jointed layers' porosity and improve their performance effectively. In order to obtain the optimal ratio of multimodal micro/nanoparticle materials, a Monte Carlo simulation method was developed to achieve their random stacking. The results show that regardless of radius ratios between bimodal spherical particles, their stacking density gets the highest value when the mass of the small particles comprises similar to 30%. When the spherical particles with r1=0.5 and non-spherical (elliptical) particles with the principal axis 2a=10, 2b=8, thickness 2d=1.5 and theta(max)=10 degrees were used, the stacking density gets the highest value when the spherical particles account for similar to 70%. Overall, the computer simulation method for evaluating the stacking density of multimodal spherical or non-spherical particles is provided and proved useful.
With the rapid development of deep learning, Few-Shot Object Detection (FSOD) has achieved remarkable advancements in the domain of few-shot learning. Conventional methods predominantly adopt a two-stage fine-tuning f...
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According to McKinsey & Company, the world's leading consulting firm, which first proposed the era of "Big Data,""Data, which has permeated every industry and business function today, has become...
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As an international common language, English is used by a large number of people and can promote international exchanges and cooperation. Learning English is an upsurge, they hope to improve the oral English to achiev...
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