检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

68,035 篇 会议
418 篇 期刊文献
205 册 图书

馆藏范围

68,658 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

39,345 篇 工学
- 31,346 篇 计算机科学与技术...
- 26,655 篇 软件工程
- 11,916 篇 信息与通信工程
- 9,712 篇 控制科学与工程
- 7,420 篇 生物工程
- 6,370 篇 电气工程
- 4,603 篇 生物医学工程（可授...
- 3,990 篇 电子科学与技术（可...
- 3,706 篇 机械工程
- 3,631 篇 光学工程
- 3,232 篇 动力工程及工程热...
- 3,159 篇 网络空间安全
- 2,671 篇 安全科学与工程
- 2,657 篇 交通运输工程
- 2,277 篇 化学工程与技术
- 2,077 篇 仪器科学与技术
21,486 篇 理学
- 10,260 篇 数学
- 7,801 篇 生物学
- 5,408 篇 物理学
- 3,621 篇 统计学（可授理学、...
- 2,661 篇 化学
- 2,021 篇 系统科学
12,162 篇 管理学
- 7,022 篇 管理科学与工程(可...
- 5,963 篇 图书情报与档案管...
- 3,672 篇 工商管理
4,417 篇 医学
- 3,716 篇 临床医学
- 3,614 篇 基础医学(可授医学...
- 2,538 篇 药学(可授医学、理...
- 2,022 篇 公共卫生与预防医...
2,804 篇 法学
- 2,250 篇 社会学
1,635 篇 经济学
1,369 篇 农学
1,136 篇 教育学
405 篇 文学
148 篇 军事学
12 篇 艺术学
6 篇 哲学
2 篇 历史学

主题

1,726 篇 deep learning
1,308 篇 machine learning
1,021 篇 internet of thin...
696 篇 support vector m...
686 篇 feature extracti...
675 篇 blockchain
674 篇 computer vision
659 篇 object detection
555 篇 convolutional ne...
522 篇 forecasting
483 篇 training
435 篇 computational mo...
405 篇 artificial intel...
399 篇 covid-19
383 篇 reinforcement le...
337 篇 long short-term ...
317 篇 predictive model...
308 篇 automation
280 篇 big data
279 篇 convolution

机构

506 篇 chitkara univers...
242 篇 school of comput...
201 篇 university of sc...
183 篇 school of automa...
165 篇 computer science...
142 篇 maharishi school...
129 篇 the islamic univ...
115 篇 computer science...
99 篇 karnataka bangal...
92 篇 school of comput...
87 篇 university of el...
86 篇 huazhong univers...
82 篇 department of co...
80 篇 college of compu...
77 篇 school of comput...
77 篇 university of ch...
76 篇 institute of art...
75 篇 school of comput...
75 篇 medical technica...
74 篇 computer technol...

作者

64 篇 shiva mehta
58 篇 vinay kukreja
54 篇 li yang
48 篇 kukreja vinay
45 篇 sharma vikrant
44 篇 sharma neha
42 篇 wang lei
42 篇 deepak gerard
40 篇 calvo d.
40 篇 wang jing
39 篇 li peng
39 篇 zhang lei
39 篇 rakesh kumar
38 篇 ferrara g.
38 篇 ardid m.
38 篇 gagliardini s.
36 篇 zhang tao
35 篇 vishal jain
34 篇 chen a.
34 篇 benoit d.m.

语言

67,100 篇 英文
1,534 篇 其他
386 篇 中文
1 篇 西班牙文

检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68658 条记录，以下是161-170 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Enhancing Fairness in Gaussian Mixture Clustering through Impact Factor

Enhancing Fairness in Gaussian Mixture Clustering through Im...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Yang, Zhijing Qian, Chuan Zheng, Junjie Tang, Yiding Yan, Boyang Zhang, Hui School of Computer Science and Technology Southwest University of Science and Technology China

ISBN: (纸本)9798350368741

Clustering is a common method used in machine learning to group sample points in a dataset. Gaussian Mixture Clustering (GMC) is a clustering method based on maximum likelihood estimation and expectation maximisation (EM) algorithms. Traditional GMC does not consider the fairness between different sensitive groups, leading to biased clustering results. In this paper, we propose a novel Fair Gaussian Mixture Clustering (FGMC) to solve the fairness problem in clustering tasks. We incorporate a fairness optimiser, the impact factor, into the GMC to ensure that the fairness of the clustering is gradually optimised over the iterations. Using FGMC ensures that the clustering results are not overly biased towards a particular group defined by sensitive attributes such as age or race. We evaluated FGMC on a real-world dataset and found that it significantly improved clustering fairness. FGMC is a promising direction for clustering that requires ethical considerations. © 2025 IEEE.

关键词： clustering fairness guassian mixture model impact factor

来源：评论

学校读者我要写书评

暂无评论

CNN based self attention mechanism for cross model receipt generation for food industry 2nd

CNN based self attention mechanism for cross model receipt g...

引用

2nd international conference on Next-Generation Computing and Information Systems, ICNGCIS 2023

作者： Goyal, Priya Gupta, Sachin Maaliw, Renato R. Soni, Mukesh Tuygunovich, Alikulov Azamat Sameen, Aws Zuhair Computer Science and Engineering Manipal University Jaipur India Department of CSE Maharaja Agrasen Institute of Technology India College of Engineering Southern Luzon State University Quezon Lucban Philippines Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science & Technology Tathawade Pune India The Department of Accounting and Audit Karshi engineering economics institute Karshi Uzbekistan College of Medical Techniques Al-Farahidi University Baghdad Iraq

ISBN: (纸本)9781032738659

Diet management requires keeping track of what you eat. The researchers presented a recipe retrieval technique based on food photos that retrieves the related recipes from the taken images and creates nutritional information accordingly, making recording more convenient. The retrieval of recipes is an example of a cross-modal retrieval challenge. Still, as compared to other challenges, the main challenge is that recipes explain a succession of modifications from raw ingredients to completed goods rather than immediately apparent characteristics. As a result, the model must have a thorough understanding of the raw materials processing process. Additionally, the model improves upon the attention mechanisms of prior techniques to mine the semantics of recipes more effectively. The approach enhances the recall rate of the recipe retrieval task by 22% over the baseline strategy, according to experimental data © 2025 The Author(s).

关键词： Nutrition

来源：评论

学校读者我要写书评

暂无评论

Paired Transmission in Networks

Paired Transmission in Networks

引用

international conference on Computational Engineering, ICCE 2023

作者： Sujana G, Jessy Sharon, Jane Olive Anitha, J. Department of Computer Science SRM Institute of Science and Technology Vadapalani Chennai India Department of Computing Technologies SRM Institute of Science and Technology Chennai India Department of Mathematics Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9783031777639

The transmission of a vertex is defined as the sum of the lengths of all shortest paths between the chosen vertex and all other vertices in G. The transmission of a graph G is the sum of the transmissions of all its vertices which is nothing but twice its Wiener index. In location theory, sets of vertices, with the minimum (or maximum) distance in a graph, play a special role because they form target sets for locations of facilities. The framework is made more general by considering the sum of distances to a specified multiset of vertices referred to as profiles. In this paper, we have defined paired transmission of vertices for a network as a special case of profiles, referred to as a paired facility location. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Network theory (graphs)

来源：评论

学校读者我要写书评

暂无评论

Human-Robot Pose Tracking Based on CNN with Color and Geometry Aggregation 16th

Human-Robot Pose Tracking Based on CNN with Color and Geo...

引用

16th international conference on Social Robotics, ICSR + InnoBiz 2024

作者： Xu, Yue Zhang, Yinlong Liu, Shuai Liu, Yuanhao Liang, Wei He, Hongsheng Shenyang University of Technology Shenyang110020 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Computer Science The University of Alabama TuscaloosaAL35487 United States

ISBN: (纸本)9789819611508

Accurately tracking the robotic arm and human joints is crucial to ensure safety during human-robot interaction. However, traditional pose tracking methods often exhibit insufficient performance and robustness in complex environments. The variations in the robotic arm’s environment and posture make it challenging for traditional methods to accurately capture the positions and posture of its joints. Specifically, when addressing challenges such as high similarity, occlusion, background complexity, and joint recognition failures, they often struggle to provide reliable and accurate results. To address these challenges, this paper proposes a human-robot pose tracking algorithm based on a new convolutional neural network model. To enhance detection accuracy, an improved color detection module is introduced to resolve joint misclassification. A geometric perception module is designed to accurately locate joints even under occlusion. Additionally, innovative iEMA and DBB modules are incorporated. The iEMA module employs edge detection technology to dynamically adjust thresholds for correct matching by improving the edge matching process. The DBB module refines the boundary box parameters for precise localization by introducing adaptive bounding box updates in real-time. This algorithm also integrates human pose recognition, enabling real-time pose recognition, thereby facilitating more intelligent and natural human-robot interaction. The algorithm has been rigorously evaluated on a custom-designed robotic arm platform. Experimental results validate the algorithm’s effectiveness and feasibility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Robotic arms

来源：评论

学校读者我要写书评

暂无评论

MSAOT: Enhancing Video Object Segmentation with Memory-Selective Updates and High-Quality Mask Regeneration 24

MSAOT: Enhancing Video Object Segmentation with Memory-Selec...

引用

13th international conference on Computing and Pattern Recognition, ICCPR 2024

作者： Du, Yinglong Luo, Yifei Zhao, Xu Yu, Tao Zhu, Guibo Wang, Jinqiao Foundation Model Research Center Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400717482

Video Object Segmentation (VOS) is an important computer vision task that involves tracking and segmenting objects across video frames. The mainstream VOS method typically employs long and short-term memory to aid the model in retaining the object's feature representation. However, current state-of-the-art methods do not adequately address the issue of information loss and contamination when updating long-term memory. To address these issues, we propose an innovative method MSAOT, including an object tracker with a memory-selective update strategy and high-quality mask regeneration for post-process. This thereby assists in subsequent sequence predictions and enhances model accuracy. MSAOT employs an object tracker with the mutual similarity evaluation for long-term memory management and leverages HQ-SAM for high-quality mask generation. Extensive experiments show that our method's long-term memory successfully preserves information from all stages of the video sequence, particularly during the mid to late phases of prediction. The richness of the stored memory information is instrumental in improving the model's performance. The experimental results on the VOT2020 benchmark highlight that MSAOT outperforms the current state-of-the-art by a notable margin of 1.1% in Expected Average Overlap (EAO). © 2024 Copyright held by the owner/author(s).

关键词： Memory management

来源：评论

学校读者我要写书评

暂无评论

Steel Defect Detection Algorithm Based on Multiobjective ENAS Sharing Strategy 24

Steel Defect Detection Algorithm Based on Multiobjective ENA...

引用

2nd international conference on Frontiers of Intelligent Manufacturing and automation, CFIMA 2024

作者： Zhao, Tianchen Dong, Zhiming Wang, Xianpeng National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang China Ministry of Education Shenyang China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang China Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Northeastern University Shenyang China

ISBN: (纸本)9798400710681

When employing the network architecture search approach for designing a steel surface defect detector, there are issues with conflicting evaluation metrics and limited computational resources. To address this challenge, we propose a multiobjective evolutionary sharing strategy-based network architecture search method (MESNAS). MESNAS defines network architecture search as a bi-level multiobjective optimization problem combined with a weight sharing acceleration strategy designed to quickly and simultaneously optimize the accuracy and complexity of classification models. A refined search space suitable for different image classification and detection tasks is designed. Using the MOEA/D algorithm, which incorporates a variable-length encoding scheme, the search space is co-utilized and explored through targeted improvements to the crossover and mutation operators in the offspring generation process. The optimal network architecture obtained from the search is tested on the concrete surface defect classification task, and the steel continuous casting slab surface defect detection task. The experimental results show that the proposed algorithm has good model performance and portability in image classification as well as defect detection tasks with different data complexities and different categories. © 2024 Copyright held by the owner/author(s).

关键词： Continuous casting

来源：评论

学校读者我要写书评

暂无评论

The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models 31

The Dark Side of Function Calling: Pathways to Jailbreaking ...

引用

31st international conference on Computational Linguistics, COLING 2025

作者： Wu, Zihui Gao, Haichang He, Jianping Wang, Ping School of Computer Science and Technology Xidian University China

ISBN: (纸本)9798891761964

Large language models (LLMs) have demonstrated remarkable capabilities, but their power comes with significant security considerations. While extensive research has been conducted on the safety of LLMs in chat mode, the security implications of their function calling feature have been largely overlooked. This paper uncovers a critical vulnerability in the function calling process of LLMs, introducing a novel "jailbreak function" attack method that exploits alignment discrepancies, user coercion, and the absence of rigorous safety filters. Our empirical study, conducted on six state-of-the-art LLMs including GPT-4o, Claude-3.5-Sonnet, and Gemini-1.5-pro, reveals an alarming average success rate of over 90% for this attack. We provide a comprehensive analysis of why function calls are susceptible to such attacks and propose defensive strategies, including the use of defensive prompts. Our findings highlight the urgent need for enhanced security measures in the function calling capabilities of LLMs, contributing to the field of AI safety by identifying a previously unexplored risk, designing an effective attack method, and suggesting practical defensive measures. Our code is available at https://***/wooozihui/jailbreakfunction. © 2025 Association for Computational Linguistics.

关键词： Linguistics

来源：评论

学校读者我要写书评

暂无评论

EEG-based emotion recognition: Leveraging CNNs for precision 2nd

EEG-based emotion recognition: Leveraging CNNs for precision

引用

2nd international conference on Next-Generation Computing and Information Systems, ICNGCIS 2023

作者： Kotwal, Ayushi Gupta, Vishal Verma, Meetali Manhas, Jatinder Sharma, Vinod Department of Computer Science & IT University of Jammu J&K Jammu India Model Institute of Engineering and Technology J&K Jammu India

ISBN: (纸本)9781032738659

Understanding human emotions is essential in recognizing cognitive and emotional functions. A lot of effort has been paid to emotion recognition as a crucial component of psychological study and interaction between humans and computers. Since its non-invasive design and great temporal resolution, electroencephalogram (EEG) signals have become a promising tool for emotion classification. The proposed methodology of emotion classification covers preprocessing of EEG data, extracting significant characteristics, and designing a CNN architecture. CNNs has the tendency to automatically learn key features, perform excellent in tasks identical to the recognition of emotions using EEG signals. They are effectively suited for dealing with the spatial and hierarchical nature of EEG data. The effectiveness and viability of the proposed approach are demonstrated by the experimental findings. The CNN model demonstrates its promise for real-time emotion identification applications by achieving excellent accuracy in its classification. The proposed structure provides fresh perspectives on human affective states and emotion classification. The approach undertaken for the study can be extended with its applications spanning from human-computer interaction systems to mental health evaluation. © 2025 The Author(s).

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Community Security Multi-channel Monitoring System Based on FFMPEG Framework 24

Community Security Multi-channel Monitoring System Based on ...

引用

8th international conference on Electronic Information technology and computer Engineering, EITCE 2024

作者： Lai, Yewen Jian, Mao Computer Engineering College JiMei University Fujian Xiamen China

ISBN: (纸本)9798400710094

Community digital monitoring has been widely used. However, the professional monitoring equipment of different manufacturers has relatively high costs, and most of them are incompatible with each other. The operation of the monitoring system is relatively complex. Therefore, this paper builds a community security multi-channel monitoring system based on the FFMPEG and Qt frameworks, which is compatible with ordinary cameras, mobile phones and other video capture devices. The system divides the process of processing monitoring videos into three steps: obtaining pictures, format transcoding, and data transmission. In the implementation of the system, the FFMPEG algorithm and its framework are used for decoding and transcoding. It includes three core modules: First, the real-time monitoring module, which displays the real-time pictures collected by various devices and stores them;second, the historical monitoring content playback module, which queries and displays the videos or photos saved locally;third, the log module, which records the main operation behaviors of users. In the design and implementation of the system, the concepts of"data flow-oriented" and"device independence" are proposed, and based on this, the compatibility of different video capture devices is realized, thereby reducing the monitoring configuration cost to a certain extent. © 2024 Copyright held by the owner/author(s).

关键词： Community Security

来源：评论

学校读者我要写书评

暂无评论

HyperDiff: Masked Diffusion Model with High-efficient Transformer for Hyperspectral Image Cross-Scene Classification

HyperDiff: Masked Diffusion Model with High-efficient Transf...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhang, Pei Wang, Dong Wu, Chanyue Yang, Jing Kang, Lei Bai, Zongwen Li, Ying Shen, Qiang School of Computer Science Northwestern Polytechnical University Xi'an China Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data Yan'an University Yan'an China School of Automation and Software Engineering Shanxi University Taiyuan China Qingdao Topscomm Communication Co. Ltd. Qingdao China Department of Computer Science Aberystwyth University Aberystwyth United Kingdom

ISBN: (纸本)9798350368741

Hyperspectral Image (HSI) cross-scene classification is a challenging task in remote sensing, particularly when real-time processing of Target Domain (TD) HSI is required, and data cannot be reused for training. While deep learning methods have shown promising results, the generalization ability of HSI representations remains limited, mainly due to class label imbalance. This paper introduces a dual-stage learning framework based on transfer learning to enhance classification accuracy in the TD. The framework includes a self-supervised learning stage and a supervised fine-tuning stage. The self-supervised stage focuses on learning robust representations by leveraging inherent structures within HSI data, while the fine-tuning stage uses training labels to extract semantic information. A masked diffusion model predicts masked tokens from unmasked ones, capturing both high-level structures and fine details in HSI data. An efficient spatiospectral Transformer, which removes self-attention from the decoder, is proposed to enhance the self-supervised process. This design allows mask tokens to obtain information from visible tokens without interacting with each other, reducing sequence length and computational costs. By decoding each mask token conditionally independently, only a subset of masked tokens is processed. Extensive experiments on two public HSI datasets demonstrate that the proposed method outperforms state-of-the-art techniques. © 2025 IEEE.

关键词： Cross-scene classification Diffusion model Hyperspectral image Transformer

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 13 14 15 16 17 18 19 20 21 22 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：