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

6,674 篇 会议
329 册 图书
119 篇 期刊文献

馆藏范围

7,121 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

4,757 篇 工学
- 3,945 篇 计算机科学与技术...
- 2,010 篇 软件工程
- 805 篇 电气工程
- 764 篇 信息与通信工程
- 588 篇 控制科学与工程
- 394 篇 生物工程
- 380 篇 生物医学工程（可授...
- 293 篇 机械工程
- 293 篇 光学工程
- 212 篇 仪器科学与技术
- 180 篇 电子科学与技术（可...
- 138 篇 化学工程与技术
- 127 篇 材料科学与工程（可...
- 119 篇 网络空间安全
- 107 篇 安全科学与工程
- 91 篇 动力工程及工程热...
1,614 篇 理学
- 803 篇 数学
- 487 篇 物理学
- 486 篇 生物学
- 272 篇 统计学（可授理学、...
- 189 篇 化学
- 141 篇 系统科学
834 篇 管理学
- 455 篇 管理科学与工程(可...
- 422 篇 图书情报与档案管...
- 173 篇 工商管理
678 篇 医学
- 603 篇 临床医学
- 254 篇 基础医学(可授医学...
- 145 篇 药学(可授医学、理...
- 100 篇 公共卫生与预防医...
121 篇 法学
- 114 篇 社会学
90 篇 教育学
56 篇 农学
51 篇 经济学
43 篇 艺术学
12 篇 文学
3 篇 军事学
1 篇 哲学

主题

927 篇 pattern recognit...
801 篇 artificial intel...
446 篇 machine learning
291 篇 feature extracti...
237 篇 deep learning
204 篇 accuracy
185 篇 support vector m...
134 篇 data mining
128 篇 training
126 篇 neural networks
126 篇 face recognition
103 篇 local binary pat...
103 篇 computer imaging...
102 篇 computer vision
88 篇 real-time system...
88 篇 image processing...
86 篇 convolutional ne...
85 篇 information syst...
83 篇 pattern matching
83 篇 computational mo...

机构

39 篇 chitkara univers...
33 篇 maharishi school...
27 篇 school of comput...
27 篇 indian stat inst...
25 篇 centre of interd...
25 篇 the islamic univ...
23 篇 department of ar...
23 篇 concordia univ c...
22 篇 national univers...
20 篇 school of comput...
19 篇 univ chinese aca...
18 篇 univ waterloo de...
17 篇 vishwakarma inst...
17 篇 school of comput...
16 篇 national laborat...
15 篇 school of artifi...
15 篇 institute of aut...
14 篇 lovely professio...
14 篇 uttaranchal inst...
14 篇 college of pharm...

作者

54 篇 suen ching y.
24 篇 suen cy
22 篇 kamel mohamed s.
18 篇 lu bao-liang
18 篇 karray fakhri
17 篇 de-shuang huang
17 篇 abraham ajith
14 篇 maji pradipta
13 篇 dash yajnaseni
12 篇 c.y. suen
10 篇 liu cheng-lin
10 篇 venkatesh svetha
10 篇 wong alexander
10 篇 chauhan rahul
10 篇 natarajan s.
10 篇 zheng wei-long
10 篇 liu wei
10 篇 vinay a.
9 篇 zhang lei
9 篇 gill kanwarparta...

语言

6,808 篇 英文
286 篇 其他
58 篇 中文
1 篇 土耳其文

检索条件"任意字段=3rd International Conference on Pattern Recognition and Machine Intelligence"

共 7122 条记录，以下是341-350 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：

Sentiment Analysis of Movie Reviews: Optimizing Predictions through TF-IDF Vectorization 3

Sentiment Analysis of Movie Reviews: Optimizing Predictions ...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Irfan, Mohd Venkatesam, Anne Sreyas Shanmugasundaram, Hariharan Gourisaria, Mahendra Kumar Chowdhury, Subrata Patra, Sudhansu Shekhar Department of Artificial Intelligence and Data Science Vardhaman College of Engineering Telangana Hyderabad India Deemed to be University Bhubaneswar India Andhra Pradesh Chittoor India

ISBN: (纸本)9798331527549

Sentiment analysis model is aimed to accurately interpret movie reviews, addressing challenges like sarcasm and noisy data. By integrating multiple machine learning classifiers Naive Bayes, Random Forest, K-Nearest Neighbors, Logistic Regression, Decision Tree, and XGBoost—the model enhances sentiment prediction accuracy. The Term Frequency-Inverse Document Frequency (TF-IDF) method is used to extract features from a dataset of 50,000 movie reviews. Performance is evaluated using accuracy, precision, recall, and F1-score, with Logistic Regression achieving the best results, including an highest accuracy of 84.33% and an F1-score of 0.847. In comparison to traditional methods, this multiclassifier approach offers a deeper understanding of movie reviews and its influence on audience decisions. The study demonstrates the potential of using these machine learning techniques to provide real-time, scalable sentiment analysis, which is crucial for filmmakers and marketers seeking insights into audience satisfaction and box office performance. © 2025 IEEE.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

Spectral Feature Selection Via Low Rank Decomposition and Local Preservation 3

Spectral Feature Selection Via Low Rank Decomposition and Lo...

引用

3rd international conference on Neural Networks, Information and Communication Engineering, NNICE 2023

作者： Jiang, Luxi Chen, Xiuhong College of Artificial Intelligence and Computer Science Jiangnan University Wuxi Jiangsu Province China

ISBN: (纸本)9798350335972

Feature selection is an important step in data mining and pattern recognition tasks. In unsupervised cases, feature selection becomes more difficult due to the lack of labels in the samples. Therefore, this paper proposes a spectral feature selection (JLrdLP) algorithm that combines low rank decomposition and local preservation. First, the model predicts pseudo-labels using spectral clustering, which jointly learns the cluster labels and feature selection matrix, enabling the algorithm to select more discriminative features. In order to realize the selection of data features, the feature selection matrix is guaranteed to be sparse by L_2,1 -norm minimization constraint;the projection matrix is decomposed into the product of two low-rank matrices to reveal the global correlation of data features;The idea is to preserve the local geometry of the data when transforming the original data into a low-dimensional space. Finally, the experimental results on multiple real datasets show that the above has better robustness, thus improving the effect of the classification. © 2023 IEEE.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence Integration in e-Government: Insights from the Korean Case 3

Artificial Intelligence Integration in e-Government: Insight...

引用

3rd IEEE international conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Yun, Chang Hee Teoh, Ai Ping Khaw, Tze Yin Penang Malaysia

ISBN: (纸本)9798350380989

The integration of artificial intelligence (AI) into e-Government framework, exemplified by Korea's approach, marks a paradigmatic shift in global governmental operations. AI, evolving from its initial theoretical foundations to advanced applications in areas like machine learning, predictive analytics, and natural language processing with large language models, is significantly transforming e-Government infrastructures. This transformation, with Korea among the leading nations, led to a study evaluating the potential impact of AI integration in the Korean e-Government system. Employing a robust crosssectional quantitative methodology, the study tested seven hypotheses to examine Korean officials' perspectives on AIenhanced e-Government system acceptance, considering variables such as social influence, trust, and attitude. Methods namely Partial Least Squares Structural Equation Modeling and the Statistical Package for the Social Sciences were used to analyze these aspects addressing research gaps and their implications for AI purveyors, policymakers, and foreign governments. This research is presumed to advance the discourse on the implementation and reception of AI in eGovernment. © 2024 IEEE.

关键词： Artificial intelligence e-Government Korea Technology Acceptance Model United Theory of Acceptance and Use of Technology

来源：评论

学校读者我要写书评

暂无评论

Multi-Target Semantic Parsing with Collaborative Deliberation Network 13

Multi-Target Semantic Parsing with Collaborative Deliberatio...

引用

13th international Joint conference on Natural Language Processing / 3rd conference of the Asia-Pacific-Chapter of the Association-for-Computational-Linguistics (IJCNLP-AACL)

作者： Li, Xiang Lei, Fangyu He, Shizhu Liu, Kang Zhao, Jun Chinese Acad Sci Inst Automat Lab Cognit & Decis Intelligence Complex Syst Beijing Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China

ISBN: (纸本)9798891760189

Semantic parsing aims at mapping natural language utterances into machine-interpretable meaning representations, facilitating user accesses to knowledge bases. However, knowledge in real-world scenarios is often duplicated in multiple storages and different representations. Although researchers have made great success by improving neural semantic parsers, existing works can only handle a specific kind of meaning representation, i.e., the single-target semantic parsing. In this paper, we introduce a multi-target semantic parsing model based on a collaborative deliberation network, which can not only decode multiple meaning representations simultaneously but also allow meaning representations to make use of information from each other while decoding. Experiments show that the proposed model improves the EM accuracy of four MRs averagely by 2.48% to 5.05% on three public datasets.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

2023 3rd international conference on Artificial intelligence and Industrial Technology Applications, AIITA 2023

2023 3rd International Conference on Artificial Intelligence...

引用

2023 3rd international conference on Artificial intelligence and Industrial Technology Applications, AIITA 2023

The proceedings contain 90 papers. The topics discussed include: registration method of single-line point clouds and images based on depth learning;research on landslide detection in SAR images based on multi-channel change detection fusion;support vector regression based on improved Harris Hawk optimization algorithm for power load forecasting;epileptic seizure detection based on semi-supervised generative adversarial network;image recognition of peach pests based on improved convnext;optimization of BP neural network for wind power output prediction based on particle swarm optimization algorithm;application of improved genetic algorithm and ant colony algorithm in multi-objective path planning;automatic bridge detection of SAR images based on interpretable deep learning algorithm;image stitching method based on feature optimization and circular function weighted fusion;natural scene text detection algorithm based on the regional proposal;and research and development of machine vision algorithm performance evaluation system in complex scenes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Physical Abuse Activity recognition using Landmarks of Human Posture and DTW Classifier 3

Physical Abuse Activity Recognition using Landmarks of Human...

引用

3rd IEEE North Karnataka Subsection Flagship international conference, NKCon 2024

作者： Bhavani, Y. V. K. Durga Pagi, V.B. Bagalkote Affiliated to Visvesvaraya Technological University Computer Science and Engineering Karnataka Belagavi590 018 India

ISBN: (纸本)9798350364569

Video Surveillance analysis can help to recognize the different types of crime activities i.e., abuse, fighting, robbery, shooting, etc. The main purpose of this study is to recognize physical abuse activities like kicking, dragging, and beating along with their postures. This study uses the values of landmarks (Left_Wrist, Right_Wrist, Left_Hip, Right_Hip, Left_Ankle, Right_Ankle) of human postures in video frames. Euclidean distance (D1 to D10) between the landmark vectors is used as the input for DTW (Dynamic Time Warping) classifier. DTW measures the similarity between training vectors and test vectors to recognize the type of physically abusive activity and classify the posture. The UCF-101 Crime public dataset is used. The empirical analysis indicates a 96% accuracy. © 2024 IEEE.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

machine Vision-Driven Semantic Segmentation for Autonomous Navigation 3

Machine Vision-Driven Semantic Segmentation for Autonomous N...

引用

3rd international conference on Applied Artificial intelligence and Computing, ICAAIC 2024

作者： Bala Krishna, N. Lokesh, K. Vali, Dudekula Azmeer Mahathi, Kanna Kumar, Koramatla Siva Padmini, Gudisirayula Andhra Pradesh Tirupati India Mother Theresa Institute of Engineering and Technology Department of Artificial Intelligence & Data Science Andhra Pradesh Palamaner India Department of Cse Andhra Pradesh Tirupati India

ISBN: (纸本)9798350375190

One of the main roles played by real time image segmentation is to enhance and catalyse self driving cars that can accurately sense their surroundings due to in terms of proper functioning. The new model was proposed with a completely new image segmentation paradigm for enabling self-driving in real time. The deployment of deep learning techniques, accurate real-time object segmentation through a fusion of fully convolutional network (FCN) with multilevel pyramid analysis. FCN uses the input image for segmentation, and in return creates a map-based on pixel-wise classification from which we can get more detailed information about different objects present in the scene. This approach creates a very large FCN network that is combined with a multiscale pyramid architecture that process an image in multiple stages effectively collecting complex surroundings information to improve performance. The proposed method is then experimented on different data with a particular focus on challenging to adopt such infrastructure in order to achieve modern day results in terms of accuracy and real time performance. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

A Novel Multi-view Fuzzy Clustering Algorithm Based on Fuzzy C-Means 1

引用

3rd international conference on Artificial intelligence Logic and Applications, AILA 2023

作者： Lin, Ze Chen, Yixiang National Engineering Research Center of Trustworthy Embedded Software East China Normal University Shanghai200062 China

ISBN: (数字)9789819978694

ISBN: (纸本)9789819978687

Fuzzy c-means (i.e., FCM) is a representative clustering method that is widely used in machine learning and pattern recognition. It can describe the degree of fuzziness of objects to clusters using memberships, but it cannot assess the degree of fuzziness of the clustering results. Motivated by such issues, in this paper, we propose a multi-view fuzzy clustering method based on FCM and a fuzzy assessment is introduced to assess the fuzziness of clustering results. Specifically, we constructed a multi-view FCM to obtain a reasonable membership matrix by fully integrating multi-view information. Based on this, we propose a fuzzy assessment method to evaluate the fuzziness of the clustering results and mark the objects between the different clusters (i.e., the object has the feature of multiple clusters). The experimental result shows that the proposed multi-view fuzzy clustering method achieves better performance than several related clustering methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

NABP: Social Network Alignment Algorithm based on Pre-trained Language Models 3

NABP: Social Network Alignment Algorithm based on Pre-traine...

引用

3rd international conference on Artificial intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Ding, Linjun Chen, Jing School of Artificial Intelligence and Computer Science Jiangnan University Jiangsu Wuxi214122 China Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computing Intelligence Jiangnan University Jiangsu Wuxi214122 China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

The existing social network matching algorithms have problems in processing text attribute information, as they cannot handle polysemy issues of word meanings well and cannot effectively extract deep semantic information from the text. To address the aforementioned issues, this paper introduces pretrained models to extract information from attribute text and proposes a social network alignment algorithm called NABP (Network Alignment based on Pre-trained Language Models). NABP first preprocesses the attribute text data to extract the text feature vectors;then, it uses the DeepWalk algorithm to perform graph representation learning on the two networks to extract their structural features. Next, the attribute feature vectors and structural feature vectors are concatenated to form the final feature vector. Then, a projection function is learned using supervised information to further improve the algorithm's performance. To verify the effectiveness of NABP algorithm, this study conducted experiments on two real social network datasets. The results show that the NABP algorithm performs better than existing algorithms in both the Accuracy and Precision@k metrics, demonstrating the effectiveness of the algorithm and pre-trained language models. © 2023 SPIE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

An Effective Stock Market Prediction using an Advanced machine Learning Algorithm and Emotional Analysis 3

An Effective Stock Market Prediction using an Advanced Machi...

引用

3rd international conference on Applied Artificial intelligence and Computing, ICAAIC 2024

作者： Kishore, Thejaswini Praveenchandar, J. Karunya Institute of Technology and Sciences Division of Computer Science and Technology Karunya Nagar Coimbatore641114 India Karunya Institute of Technology and Sciences Division of Artificial Intelligence and Machine Learning Karunya Nagar Coimbatore641114 India

ISBN: (纸本)9798350375190

The structure of the stock exchange is complex, dynamic, and difficult to predict. Emotional analysis and machine learning have increased forecast accuracy. The implementation of sentiment detection and machine learning to stock exchange forecasts will be examined in this study. We'll also talk about creating a web application which utilizes the most of these technologies to give users access to real-time stock exchange estimates. Sentiment analysis is a technique for analyzing the emotional undertones of texts. Sentiment analysis is a stock exchange prediction tool that uses an examination of social media writes, reports, and other sources of information to ascertain the general sentiment of investors. With the use of emotional analysis algorithms, future stock prices for the following seven days can be predicted, and recommendations for price increases or decreases can be made. Utilizing the anticipated value from the three algorithms - ARIMA, LSTM, and Linear Regression - this forecast is made. The AutoRegressive Integrated Moving Average, or AriMA-like, technique is employed in time series prediction and defines the next step as a linear function of the difference between observations and errors. A particular type of recurrent neural network architecture called Long Short-Term Memory, or LSTM, is perfect for categorizing, assessing, and forecasting time series with irregular gaps between important occurrences. One of the best ways for rdNs to learn is through experience. On the contrary, linear regression fits a linear equation to observed data in order to illustrate the relationship amongst one or more independent factors and a dependent variable. It evaluates several variables, including volume, adj close, high, low, date, open, and close © 2024 IEEE.

关键词： Sentiment analysis

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 << < 31 32 33 34 35 36 37 38 39 40 > >>

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：