检索结果-内蒙古大学图书馆

6th International Conference on Systems and Informatics, ICSAI 2019

作者： Xi, Runping Han, Tianyi Zhang, Yaqing Han, Qianqian Natl. Engineering Laboratory of Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Provincial Key Laboratory of Speech Image Information Processing School of Computer Science Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9781728152561

Aerial video stitching has been widely used in many fields such as large-scale videos surveillance, disaster monitoring and unmanned aerial vehicle (UAV) navigation. Ghosting and parallax are challenging problems when the video streams are captured by UAV. This paper presents a novel method based on hybrid projective model which combines local warp alignment and global warp projection for better registration accuracy. The geometric alignment model is used for global registration of images and the content-preserving alignment model is used for local refinement. Simultaneously, reference frame is updated adaptively according to the shift of scenery, which is used to eliminate the cumulative error appearing in long video streams. The proposed approach has been tested under multiple datasets in different scenarios, which shows good performance. © 2019 IEEE.

关键词： Security systems

来源：评论

学校读者我要写书评

暂无评论

FDT-MAC: A new multi-channel MAC protocol based on fuzzy decision tree for wireless sensor network 5th

FDT-MAC: A new multi-channel MAC protocol based on fuzzy dec...

引用

5th Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2018

作者： Yang, Hui Ci, Linlin Zhang, Fuquan Yang, Minghua Mao, Yu Niu, Ke School of Computer Science and Technology Beijing Institute of Technology Beijing China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Rocket Military Equipment Research Institute Beijing China Computer School Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9783030037659

The current popular multi-channel Medium Access Control (MAC) layer protocol adopts a strategy of separating control and data channels, in order to improve channel utilization and packet forwarding success rate. However, the randomness of the data access and the high mobility of the nodes will lead to switch channels too frequently, which will still increase the packet transmission latency. Therefore, this paper proposes a fuzzy decision tree for MAC (FDT-MAC) protocol, which constructs the fuzzy decision tree of the nodes sub-tree. FDT-MAC utilizes fuzzy reasoning method to construct the membership function of the node collision factor (NCF) and node relative direction (NRD) factor. So that the node can quickly select the appropriate channel according to the real-time status (Output value) of each channel, reduce the collision probability of the packet, and improve the delivery probability (90%) and throughput of the channel (750 bps). © Springer Nature Switzerland AG 2019.

关键词： Membership functions

来源：评论

学校读者我要写书评

暂无评论

Fruit detection using faster R-CNN based on deep network 2nd

Fruit detection using faster R-CNN based on deep network

引用

2nd International Conference on Smart Vehicular technology, Transportation, Communication and Applications, VTCA 2018

作者： Ma, Linjuan Zhang, Fuquan Xu, Lin School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Key Laboratory of Nondestructive Testing Fuqing Branch of Fujian Normal University Fuzhou350300 China

ISBN: (纸本)9783030045845

Fruit detection is of great significance in the agriculture. Recently, deep neural network has been widely studied in fruit detection. In our paper, we present a new approach of fruit detection, which uses Faster R-CNN based on deep network AlexNet. Our aim is to develop a fast, accurate and convenient model to detect and classify the fruit. Data augmentation is also used to increase the fruit dataset and avoid the overfitting in some degree. We use the fruits-360 dataset to perform the experiments. © Springer Nature Switzerland AG 2019.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

VRAS: A virtual rehearsal assistant system for live performance 2nd

VRAS: A virtual rehearsal assistant system for live performa...

引用

2nd International Conference on Smart Vehicular technology, Transportation, Communication and Applications, VTCA 2018

作者： Wu, Yufeng Ding, Gangyi Li, Hongsong Xue, Tong Jiao, Di Huang, Tianyu Zhang, Longfei Zhang, Fuquan Xu, Lin Digital Performance and Simulation Key Laboratory School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Key Laboratory of Nondestructive Testing Fuqing Branch of Fujian Normal University Fuzhou350300 China

ISBN: (纸本)9783030045845

The VR technologies are widely adopted for training purposes by providing the users with educational virtual experience. In this work, we propose an immersive VR system that help the choreographers and the dancers to facilitate their dance rehearsal experience. The system integrates motion capture devices and head-mounted displays (HMDs). The motions of the dancers, their partners, and the choreographers are captured and projected into a virtual dancing scene in an interactive frame rate. The dancers who are wearing the HMDs, are allowed to observe the synthesized virtual performances within a virtual stage space from several selected third-person views. These are the audience’s view, the dancing partner’s view, and the choreographer’s view. Such synthesized external self-images augment dancer’s perception of their dance performance and their understanding of the choreography. Feedbacks from the participants indicate the proposed system is effective and the preliminary experimental results agree with our observations. © Springer Nature Switzerland AG 2019.

关键词： Helmet mounted displays

来源：评论

学校读者我要写书评

暂无评论

Confidence-Regulated Generative Diffusion Models for Reliable AI Agent Migration in Vehicular Metaverses

arXiv

引用

arXiv 2025年

作者： Kang, Yingkai Kang, Jiawen Wen, Jinbo Zhang, Tao Yang, Zhaohui Niyato, Dusit Zhang, Yan School of Automation Guangdong University of Technology Guangzhou510006 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Cyberspace Science and Technology Beijing Jiaotong University Beijing100044 China College of Information Science and Electronic Engineering Zhejiang Provincial Key Lab of information processing communication and networking Zhejiang University Hangzhou310007 China College of Computing and Data Science Nanyang Technological University Singapore Department of Informatics University of Oslo the Simula Research Laboratory Norway

Vehicular metaverses are an emerging paradigm that merges intelligent transportation systems with virtual spaces, leveraging advanced digital twin and Artificial Intelligence (AI) technologies to seamlessly integrate vehicles, users, and digital environments. In this paradigm, vehicular AI agents are endowed with environment perception, decision-making, and action execution capabilities, enabling real-time processing and analysis of multi-modal data to provide users with customized interactive services. Since vehicular AI agents require substantial resources for real-time decision-making, given vehicle mobility and network dynamics conditions, the AI agents are deployed in RoadSide Units (RSUs) with sufficient resources and dynamically migrated among them. However, AI agent migration requires frequent data exchanges, which may expose vehicular metaverses to potential cyber attacks. To this end, we propose a reliable vehicular AI agent migration framework, achieving reliable dynamic migration and efficient resource scheduling through cooperation between vehicles and RSUs. Additionally, we design a trust evaluation model based on the theory of planned behavior to dynamically quantify the reputation of RSUs, thereby better accommodating the personalized trust preferences of users. We then model the vehicular AI agent migration process as a partially observable markov decision process and develop a Confidence-regulated Generative Diffusion Model (CGDM) to efficiently generate AI agent migration decisions. Numerical results demonstrate that the CGDM algorithm significantly outperforms baseline methods in reducing system latency and enhancing robustness against cyber attacks. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

A chunk-based multi-strategy machine translation method 5th

A chunk-based multi-strategy machine translation method

引用

5th Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2018

作者： Wang, Yiou Zhang, Fuquan Beijing Institute of Science and Technology Information Beijing100044 China Digital Performance and Simulation Technology Lab School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China

ISBN: (纸本)9783030037659

In this paper, a chunk-based multi-strategy machine translation method is proposed. Firstly, an English-Chinese bilingual tree-bank is constructed. Then, a translation strategy based on the chunk that combines statistics and rules is used in the translation stage. Through hierarchical sub-chunks, the input sentence is divided into a set of chunk sequence. Each chunk searches the corresponding instance in the corpus. Translation is completed by recursive refinement from chunks to words. Conditional Random Fields model is used to divide chunks. An experimental English-Chinese translation system is deployed, and experimental results show that the system performs better than the Systran system. © Springer Nature Switzerland AG 2019.

关键词： Machine translation

来源：评论

学校读者我要写书评

暂无评论

Image Dehazing Network Based on Dilated Convolution Feature Extraction 12

Image Dehazing Network Based on Dilated Convolution Feature ...

引用

12th International Congress on Image and Signal processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

作者： Feng, Ting Li, Zuoyong Wang, Chuansheng Chen, Xinwei Wu, Jiawei College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China School of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China

ISBN: (纸本)9781728148526

Hazy weather brings a lot of inconvenience to peoples lives, such as transportation. Therefore, image dehazing is still an important focus point. To achieve image dehazing, we proposed a Deep Dilated Residual Haze Network (DDRHNet) based on self-encoder and self-decoder. The proposed mode is an end-to-end supervised method, which directly estimates image dehazing result instead of estimating the atmospheric light and the transmission in the unsupervised and classical atmospheric scattering model. The DDRHNet method obtains image dehazed result by finding the difference between the input hazy image and the output of haze-free image. Experimental results on an open image dehazing dataset called SOTS demonstrate the superiority of the proposed DDRHNet network. © 2019 IEEE.

关键词： Demulsification

来源：评论

学校读者我要写书评

暂无评论

Correction to: Enhancing cyber defense strategies with discrete multi-dimensional Z-numbers: a multi-attribute decision-making approach

引用

Complex & Intelligent Systems 2025年第7期11卷 1-1页

作者： Yao, Aiting Huang, Chen Zhang, Weiqi Dong, Chengzu Lu, Meiqu Mao, Junjun Liu, Xiao Li, Xuejun Anhui Provincial International Joint Research Center for Advanced Technology in Medical Imaging School of Computer Science and Technology Anhui University Hefei China AI Techplus Pty Ltd Organization Melbourne Australia School of Information Technology Deakin University Geelong Australia School of Data Science Lingnan University Hongkong China School of Artificial Intelligence Guangxi Minzu University Nanning China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei China

来源：评论

学校读者我要写书评

暂无评论

Research on stage creative scene model generation based on series key algorithms 2nd

Research on stage creative scene model generation based on s...

引用

2nd International Conference on Smart Vehicular technology, Transportation, Communication and Applications, VTCA 2018

作者： Zhang, Fuquan Ding, Gangyi Ma, Linjuan Zhu, Yumeng Li, Zuoyong Xu, Lin Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Digital Performance and Simulation Technology Laboratory School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Key Laboratory of Nondestructive Testing Fuqing Branch of Fujian Normal University Fuzhou350300 China

ISBN: (纸本)9783030045845

This paper proposes a method to construct a stage scene systematically. We propose how to build key algorithms for each element of the stage based on this method. The scene generation model is constructed to generate the creative stage scene we need based on the combination of these algorithms. We will start with 3D model adversarial generation, style migration generation, scene construction layout, scheme evaluation and scheme selection and so on. Then we will elaborate GANs algorithm, style transfer network, spatial combination and other algorithms. © Springer Nature Switzerland AG 2019.

关键词： 3D modeling

来源：评论

学校读者我要写书评

暂无评论

Robust Face Recognition via Multi-scale Contextual information Ensemble Learning

Robust Face Recognition via Multi-scale Contextual Informati...

引用

Chinese Automation Congress (CAC)

作者： Wan Zhang Guangwei Gao Fei Wu Songsong Wu College of Automation & College of Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

The study of robust face recognition has always gained much attention and has been widely applied to many social and public safety protection fields. Image patch based methods have achieved much more attractive performance. Especially, multi-scale patch based methods take the impact of different scales of the image patch into consideration. However, these methods ignore a fact that different parts of the face image contain different contextual semantic information which may be useful for the recognition task. To this end, in this study, we presented a robust face recognition approach by fully utilizing the multi-scale contextual information. Different from previous patch based methods, in our method, we select several patches around the test patch with a certain step in each window. Then the concatenated patch set is linearly represented over the corresponding patch sets on the training samples. By this consideration, the contextual topology can provide complementary contributions to the recognition, especially when the test faces have occlusions. Also, the multi-scale ensemble learning scheme is exploited to further enhance the recognition performance. Our extensive experiments have validated the superiority of our proposed approach over some state-of-the-art patch based robust face recognition approaches.

关键词： Face recognition Training Image recognition Telecommunications Nuclear magnetic resonance Indexes Dictionaries

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：