检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Liang, Lili Sun, Guanglu School of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China Heilongjiang Provincial Key Laboratory of Intelligent Information Processing and Application Harbin150080 China

Video Question Answering (VideoQA) is an important research direction in the field of artificial intelligence, enabling machines to understand video content and perform reasoning and answering based on natural language questions. Although methods based on static relationship reasoning have made certain progress, there are still deficiencies in the accuracy of static relationship recognition and representation, and they have not fully utilized the static relationship information in videos for in-depth reasoning and analysis. Therefore, this paper proposes a reasoning method for intra-type and inter-type message passing based on static relationships. This method constructs a dual graph for intra-type message passing reasoning and builds a heterogeneous graph based on static relationships for inter-type message passing reasoning. The intra-type message passing reasoning model captures the neighborhood information of targets and relationships related to the question in the dual graph, updating the dual graph to obtain intra-type clues for answering the question. The inter-type message passing reasoning model captures the neighborhood information of targets and relationships from different categories related to the question in the heterogeneous graph, updating the heterogeneous graph to obtain inter-type clues for answering the question. Finally, the answers are inferred by combining the intra-type and inter-type clues based on static relationships. Experimental results on the ANetQA and Next-QA datasets demonstrate the effectiveness of this method. © 2025, CC BY.

关键词： Question answering

来源：评论

学校读者我要写书评

暂无评论

Graph Neural Network with Multi-Kernel Learning for Multispectral Point Cloud Classification

Graph Neural Network with Multi-Kernel Learning for Multispe...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Zifeng Zhang Qingwang Wang Mingye Wang Tao Shen Kunming University of Science and Technology Kunming China Yunnan Key Laboratory of Computer Technologies Application Kunming China

Multispectral point clouds provide the data basis for finer land cover classification due to the simultaneous spatial and spectral information. How to jointly utilize spatial-spectral information becomes a hot research direction. Benefiting from the excellent performance of graph neural networks (GNNs) on non-Euclidean data, it is well suited to modelling multispectral point clouds to achieve higher classification accuracy. This paper proposes a novel graph convolutional networks with multi-kernel learning (GCN-MKL) for adaptively constructing a graph of multispectral point cloud for finer classification. Specifically, we use multiple base kernels to map the multispectral point cloud into a high-dimensional feature space and learn a linear combination of base kernels through a multi-kernel learning mechanism embedded in the network. The learned multi-kernel graph can effectively measure the high-dimensional similarity between multispectral points. Experimental results demonstrate that the proposed GCN-MKL outperforms several state-of-the-art methods on a real multispectral point cloud.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Communication Countermeasure Strategy Decision-Making Based on Incomplete Information Game

Communication Countermeasure Strategy Decision-Making Based ...

引用

International Conference on Advanced Communication technology (ICACT)

作者： Jinyue Liu Xiang Gao Haowei Yang Jihao Zhang Yuhan Liu Peng Gong National Key Laboratory of Mechatronic Engineering and Control School of Mechatronical Engineering Beijing Institute of Technology Beijing China Institute of Computer Application Technology Norinco Group Beijing China

ISBN: (数字)9791188428137

ISBN: (纸本)9798331507602

In modern battlefields, the stability of wireless communications is crucial for intelligence transmission, command coordination, and maintaining strategic advantage. However, with the rapid advancement of communication technologies, the electromagnetic environment has become increasingly complex, making intelligent decision-making in communication countermeasures a prominent research focus. However, most existing studies adopt deep learning and reinforcement learning methods, which require extensive data samples and computational resources. To address these limitations, this paper proposes a game-theoretic model for intelligent radio communication countermeasures under incomplete information. It quantitatively evaluates common attack and defense tactcis used in communication countermeasures and explores the mixed-strategy equilibrium of the game when both the attackers and defenders consist of multiple types. Furthermore, simulation-based comparative analyses are conducted to assess the factors influencing the utility of both the attacker and defender. The findings offer theoretical insights and decision-making support for the deployment of communication countermeasure strategies in practical military operations, contributing to significant strategic value.

关键词： Wireless communication Military communication Deep learning Decision making Games Reinforcement learning Communications technology Stability analysis Radio communication countermeasures Electromagnetics

来源：评论

学校读者我要写书评

暂无评论

A framework based on sparse representation model for time series prediction in smart city

引用

Frontiers of computer Science 2021年第1期15卷 99-111页

作者： Zhiyong YU Xiangping ZHENG Fangwan HUANG Wenzhong GUO Lin SUN Zhiwen YU College of Mathematics and Computer Science Fuzhou UniversityFuzhou 350108China Hangzhou Key Laboratory for IoT Technology&Application Zhejiang University City CollegeHangzhou 310015China School of Computer Science Northwestern Polytechnical UniversityXi’an 710072China

Smart city driven by Big Data and Internet of Things(loT)has become a most promising trend of the *** one important function of smart city,event alert based on time series prediction is faced with the challenge of how to extract and represent discriminative features of sensing knowledge from the massive sequential data generated by IoT *** this paper,a framework based on sparse representa-tion model(SRM)for time series prediction is proposed as an efficient approach to tackle this *** dividing the over-complete dictionary into upper and lower parts,the main idea of SRM is to obtain the sparse representation of time series based on the upper part firstly,and then realize the prediction of future values based on the lower *** choice of different dictionaries has a significant impact on the performance of *** paper focuses on the study of dictionary construction strategy and summarizes eight variants of *** results demonstrate that SRM can deal with different types of time series prediction flexibly and effectively.

关键词： sparse representation smart city time series prediction dictionary construction

来源：评论

学校读者我要写书评

暂无评论

GCFuzz: An Intelligent Method for Generating IoT Protocols Test Cases Using GAN with CVAE 7th

GCFuzz: An Intelligent Method for Generating IoT Protocols ...

引用

7th International Conference on Attacks and Defenses for Internet-of-Things, ADIoT 2024

作者： Zhong, Ming Zeng, Zisheng Guo, Yijia Zhao, Dandan Zhang, Bo Li, Shenghong Peng, Hao Ding, Zhiguo School of Computer Science and Technology Zhejiang Normal University Zhejiang Jinhua China Key Laboratory of Intelligent Educational Technology and Application in Zhejiang Normal University Jinhua321004 China School of Cyber Science and Engineering Shanghai Jiao Tong University Shanghai China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9783031855924

The importance of Internet of Things (IoT) systems security cannot be ignored, particularly in the realm of communication. IoT protocols serve as standards for communication and interaction among devices in IoT environments. This paper enhances IoT security by identifying and exposing protocol vulnerabilities through fuzzing, a crucial method for discovering security flaws. Traditional generation-based fuzzers require reverse engineering to understand protocol grammar and generate test cases. In this paper, we propose an intelligent method called GCFuzz, which generates high-quality test cases without prior knowledge of the protocol. To understand different classes of protocol grammar, GCFuzz applies Generative Adversarial Networks (GAN) with Conditional Variational Autoencoders (CVAE) to train a generative model on various classes of protocol messages. After training, the model generates fake but credible messages. Additionally, to accurately cluster real protocol messages, we devise a novel clustering method based on a keyword. Results show that, compared to GANFuzz, Peach, BooFuzz, and Sulley, the test cases generated by GCFuzz have stronger targeting and less redundancy, while GCFuzz has higher accurate testing efficiency. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Catrack: Condition-Aware Multi-Object Tracking with Temporally Enhancedappearance Features

SSRN

引用

SSRN 2024年

作者： Cao, Jinli Wang, Yanchao Li, Run Zhang, Dawei Li, Minglu Zheng, Zhonglong School of Computer Science and Technology Zhejiang Normal University China State Key Laboratory of CAD&CG Zhejiang University China Key Laboratory of Intelligent Education Technology Application of Zhejiang Province China Department of Computer Science and Information Technology La Trobe University Australia

Multiple Object Tracking (MOT) is a critical task in computer vision with a wide range of practical applications. However, current methods often use a uniform approach for associating all targets, overlooking the varying conditions of each target. This can lead to performance degradation, especially in crowded scenes with dense targets. To address this issue, we propose a novel Condition-Aware Tracking method (CATrack) to differentiate the appearance feature flow for targets under different conditions. Specifically, we propose three designs for data association and feature update. First, we develop an Adaptive Appearance Association Module (AAAM) that selects suitable track templates based on detection conditions, reducing association errors in long-tail cases like occlusions or motion blur. Second, we design an ambiguous track filtering Selective Update strategy (SU) that filters out potential low-quality embeddings. Thus, the noise accumulation in the maintained track feature will also be reduced. Meanwhile, we propose a confidence-based Adaptive EMA (AEMA) method for the feature state transition. By adaptively adjusting the weights of track and detection embeddings, our AEMA better preserves high-quality target features. By integrating the above modules, CATrack enhances the discriminative capability of appearance features and improves the robustness of appearance-based associations. Extensive experiments on the MOT17 and MOT20 benchmarks validate the effectiveness of the proposed CATrack. Notably, the state-of-the-art results on MOT20 demonstrate the superiority of our method in highly crowded scenarios. © 2024, The Authors. All rights reserved.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

RailPC: A large-scale railway point cloud semantic segmentation dataset

引用

CAAI Transactions on Intelligence technology 2024年第6期9卷 1548-1560页

作者： Tengping Jiang Shiwei Li Qinyu Zhang Guangshuai Wang Zequn Zhang Fankun Zeng Peng An Xin Jin Shan Liu Yongjun Wang Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing Normal UniversityNanjingChina Technology Innovation Center for Integrated Applications in Remote Sensing and Navigation Ministry of Natural ResourcesNanjingChina Eastern Institute of Technology(EIT) NingboChina Tianjin Key Laboratory of Rail Transit Navigation Positioning and Spatio-temporal Big Data Technology TianjinChina College of Computer Science and Engineering Northwest Normal UniversityLanzhouChina Mckelvey School of Engineering Washington University in St.LouisSt.LouisMissouriUSA School of Electronic and Information Engineering Ningbo University of TechnologyNingboChina

Semantic segmentation in the context of 3D point clouds for the railway environment holds a significant economic value,but its development is severely hindered by the lack of suitable and specific ***,the models trained on existing urban road point cloud datasets demonstrate poor generalisation on railway data due to a large domain gap caused by non-overlapping special/rare categories,for example,rail track,track bed *** harness the potential of supervised learning methods in the domain of 3D railway semantic segmentation,we introduce RailPC,a new point cloud *** provides a large-scale dataset with rich annotations for semantic segmentation in the railway ***,RailPC contains twice the number of annotated points compared to the largest available mobile laser scanning(MLS)point cloud dataset and is the first railway-specific 3D dataset for semantic *** covers a total of nearly 25 km railway in two different scenes(urban and mountain),with 3 billion points that are finely labelled as 16 most typical classes with respect to railway,and the data acquisition process is completed in China by MLS *** extensive experimentation,we evaluate the performance of advanced scene understanding methods on the annotated dataset and present a synthetic analysis of semantic segmentation *** on our findings,we establish some critical challenges towards railway-scale point cloud semantic *** dataset is available at https://***/NNU-GISA/GISA-RailPC,and we will continuously update it based on community feedback.

关键词： data benchmark MLS point clouds railway scene semantic segmentation

来源：评论

学校读者我要写书评

暂无评论

Reform of Blended-Teaching Mode for Discipline English Based on Mobile Terminal 17th

Reform of Blended-Teaching Mode for Discipline English Based...

引用

17th International Conference on computer Science and Education, ICCSE 2022

作者： Yu, Niefang Peng, Xiaoning Li, Xiaomei Lu, Youmin School of Computer and Artificial Intelligence Huaihua University Hunan Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China

ISBN: (纸本)9789819924455

In the context of the era of big data, the rise of using mobile terminal is also putting forward new requirements for the teaching of Discipline English. Based on some general problems in the teaching practice of this course, we discuss whether adopting the blended-teaching mode can expand the learning space and time, enrich the learning interaction, and improve the learning efficiency in the context of big data based on mobile terminals. And then improve the quality of teaching and enhance application ability for the Discipline English. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Traffic Signal Light Recognition Based on Transformer 12th

Traffic Signal Light Recognition Based on Transformer

引用

12th International Conference on computer Engineering and Networks, CENet 2022

作者： Ou, Yangze Sun, Yaqi Yu, Xiaozhong Yun, Liuqing College of Computer Science and Technology Hengyang Normal University Hunan Hengyang421008 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hunan Hengyang421008 China

ISBN: (纸本)9789811969003

With more and more developed technology, unmanned driving technology has gradually entered people’s vision. Many cars are now equipped with self-parking technology, which allows the vehicle to enter the garage through a pre-set path without manual operation. At the same time, the traffic light identification mentioned in this paper can also be used for driverless cars, and can also be combined with manual driving to reduce the probability of traffic accidents caused by running red lights. This design is based on Transformer and Resnet convolutional neural network, using feature extraction technology. First of all, the data set used in this algorithm is self-made COCO data set. Then, the corresponding training is carried out to obtain the corresponding model of traffic signal light recognition. Finally, the trained model is used to predict the relevant traffic signal light. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

A Study on Random Differentiation Methods for Homework Based on Fuzzy Test 17th

A Study on Random Differentiation Methods for Homework Based...

引用

17th International Conference on computer Science and Education, ICCSE 2022

作者： Liu, Yiwen Shi, Yuanquan Peng, Xiaoning Mi, Chunqiao Yang, Yujun School of Computer and Artificial Intelligence Huaihua University Hunan Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China

ISBN: (纸本)9789819924455

A fuzzy test-based method for random differentiation of homework is proposed to address the problems of low update frequency, serious plagiarism and weakened barriers in university coursework. In order to generate fuzzy homework questions, a semi-automatic framework for fuzzy test-based homework is designed and the four key steps are described in formal language, including pre-processing, variable construction, variable screening and difficulty assessment. The effectiveness of the method is illustrated through a comparison of student teaching data, questionnaire feedback and faculty interviews in a pilot course on principles of computer composition. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Formal languages

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：