Lane detection technology is the basic module of safe and intelligent driving. It is conducive to lane path planning, determine the reasonable driving range, to ensure driving safety. Current research generally adopts...
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More than a billion people in today’s world are estimated to suffer from some type of disability at some point in their life. Patients with Mobility Impairment face various challenging circumstances every day. Comple...
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Community detection is a crucial task in complex network analysis, and existing game-theoretic-based community detection methods struggle to achieve a balance between local and global competition and cooperation. This...
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Rotation invariance is a crucial requirement for the analysis of 3D point clouds. However, current methods often achieve rotation invariance by employing specific network designs. These networks, though perform well o...
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The aim of this paper is to present the improvement of computersystems for the VLSI, the 4th-year course at the school of Electrical engineering, University of Belgrade. This course consisted of only two parts, Softw...
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Cloud computing is an innovation of the computer model. Although it has unique advantages, it also brings various challenges to people, the most important of which is security. Due to the particularity of certain fiel...
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This paper focuses on the application of four algorithms in data prediction. In the paper, the paper firstly establishes a SVM model and random forest prediction model to judge the performance effect of the model. By ...
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Satellite-Terrestrial Integrated Networks (STINs) integrate satellite networks, the Internet, and mobile wireless networks and are able to provide powerful services to users. In STIN, satellite gateways play an import...
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With the development of artificial intelligence and breakthroughs in deep learning,large-scale foundation models(FMs),such as generative pre-trained transformer(GPT),Sora,etc.,have achieved remarkable results in many ...
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With the development of artificial intelligence and breakthroughs in deep learning,large-scale foundation models(FMs),such as generative pre-trained transformer(GPT),Sora,etc.,have achieved remarkable results in many fields including natural language processing and computer *** application of FMs in autonomous driving holds considerable *** example,they can contribute to enhancing scene understanding and *** pre-training on rich linguistic and visual data,FMs can understand and interpret various elements in a driving scene,and provide cognitive reasoning to give linguistic and action instructions for driving decisions and ***,FMs can augment data based on the understanding of driving scenarios to provide feasible scenes of those rare occurrences in the long tail distribution that are unlikely to be encountered during routine driving and data *** enhancement can subsequently lead to improvement in the accuracy and reliability of autonomous driving *** testament to the potential of FMs'applications lies in world models,exemplified by the DREAMER series,which showcases the ability to comprehend physical laws and *** from massive data under the paradigm of self-supervised learning,world models can generate unseen yet plausible driving environments,facilitating the enhancement in the prediction of road users'behaviors and the off-line training of driving *** this paper,we synthesize the applications and future trends of FMs in autonomous *** utilizing the powerful capabilities of FMs,we strive to tackle the potential issues stemming from the long-tail distribution in autonomous driving,consequently advancing overall safety in this domain.
In this paper,we investigate the end-to-end performance of intelligent reflecting surface(IRS)-assisted wireless communication *** consider a system in which an IRS is deployed on a uniform planar array(UPA)configurat...
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In this paper,we investigate the end-to-end performance of intelligent reflecting surface(IRS)-assisted wireless communication *** consider a system in which an IRS is deployed on a uniform planar array(UPA)configuration,including a large number of reflecting elements,where the transmitters and receivers are only equipped with a single *** objective is to analytically obtain the achievable ergodic rate,outage probability,and bit error rate(BER)of the ***,to maximize the system’s signal-to-noise ratio(SNR),we design the phase shift of each reflecting element and derive the optimal reflection phase of the IRS based on the channel state information(CSI).We also derive the exact expression of the SNR probability density function(p.d.f.)and show that it follows a non-central Chi-square *** the p.d.f.,we then derive the theoretical results of the achievable rate,outage probability,and *** accuracy of the obtained theoretical results is also verified through numerical *** shown that the achievable rate,outage probability,and BER could be improved by increasing the number of reflecting elements and choosing an appropriate SNR ***,we also find that the IRS-assisted communication system achieves better performance than the existing end-to-end wireless communication.
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