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

6,718 篇 会议
329 册 图书
119 篇 期刊文献

馆藏范围

7,165 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

4,792 篇 工学
- 3,971 篇 计算机科学与技术...
- 2,033 篇 软件工程
- 809 篇 电气工程
- 773 篇 信息与通信工程
- 593 篇 控制科学与工程
- 395 篇 生物工程
- 381 篇 生物医学工程（可授...
- 297 篇 光学工程
- 296 篇 机械工程
- 214 篇 仪器科学与技术
- 182 篇 电子科学与技术（可...
- 138 篇 化学工程与技术
- 128 篇 材料科学与工程（可...
- 121 篇 网络空间安全
- 109 篇 安全科学与工程
- 91 篇 动力工程及工程热...
1,630 篇 理学
- 810 篇 数学
- 493 篇 物理学
- 490 篇 生物学
- 273 篇 统计学（可授理学、...
- 191 篇 化学
- 141 篇 系统科学
845 篇 管理学
- 464 篇 管理科学与工程(可...
- 425 篇 图书情报与档案管...
- 181 篇 工商管理
679 篇 医学
- 604 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...
122 篇 法学
- 115 篇 社会学
92 篇 教育学
58 篇 农学
52 篇 经济学
43 篇 艺术学
12 篇 文学
4 篇 军事学
1 篇 哲学

主题

927 篇 pattern recognit...
801 篇 artificial intel...
447 篇 machine learning
291 篇 feature extracti...
243 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...
88 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 school of comput...
18 篇 univ waterloo de...
17 篇 vishwakarma inst...
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
11 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

6,735 篇 英文
403 篇 其他
65 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 7166 条记录，以下是591-600 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：

Enhanced Multiclassification of Avocado Leaf Diseases: CNN and Random Forest Integration 3

Enhanced Multiclassification of Avocado Leaf Diseases: CNN a...

引用

3rd international conference for Innovation in Technology, INOCON 2024

作者： Mir, Taifa Ayoub Gupta, Sheifali Chauhan, Rahul Singh, Mukesh Banerjee, Deepak Kumar, Bura Vijay Chitkara University Chitkara University Institute of Engineering and Technology Punjab India Graphic Era Hill University Uttarakhand Dehradun India Graphic Era Deemed to Be University Uttarakhand Dehradun India Sr University School of Computer Science and Artificial Intelligence Warangal India

ISBN: (纸本)9798350381931

Through the use of advanced machine learning techniques, the primary objective of this research is to develop and evaluate a classification model to identify a variety of illnesses that may affect avocado leaves. Despite exhibiting remarkable accuracy, recall, and F1-score metrics, the model displays good performance across a wide range of illness categories. The accuracy levels of the model, which range from 92.61% to 95.32%, are indicative of the effectiveness of the model in reliably detecting different kinds of diseases. Furthermore, recall rates, ranging between 91.53% and 94.44%, demonstrate the model's efficacy in collecting important cases within each illness categorization. The model demonstrates resilience in the classification of avocado leaf diseases, as it maintains an overall accuracy of roughly 93.66% during its operation. These results suggest that the model has the potential to facilitate early disease diagnosis and accurate identification, which would give major contributions to the enhancement of disease control systems in avocado farming. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Stock Price Prediction using Transformer and Bidirectional Long Short-term Memory 3

Stock Price Prediction using Transformer and Bidirectional L...

引用

3rd international conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Murugan, Vigneshwaran Moorthy, Rajalakshmi Shenbaga Sri Ramachandra Institute of Higher Education and Research Sri Ramachandra Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (纸本)9798350369083

Predicting stock prices has always been a challenging problem since it would be tough for algorithms to find complex patterns in stock datasets. This article proposes a new method TRAN-BiLSTM. This method consists of a hybrid architecture of transformers and BiLSTM together. Since the stock dataset is huge and time series, the prices must be noted from the start, so it requires long-term and short-term dependencies. The encoder of the transformer contains multi-head-self-attention-mechanism to get a long and short-term dependency. Transformer's ability to capture the sequence data is weak. Bidirectional Long Short-term Memory (BiLSTM) is utilized to get sequential information as it can able to handle the data in and from directions. Stock datasets taken from Yahoo Finance API have been used in this research. Three different algorithms TRAN-BiLSTM, LSTM, and BiLSTM have been used and compared to propose which algorithm is best suited for the stock price prediction. Experimentations revealed that the TRAN-BiLSTM method outperforms the other two algorithms. © 2024 IEEE.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

The Fast K Algorithm Based on a Fixed Grid Method 3

The Fast K Algorithm Based on a Fixed Grid Method

引用

3rd international conference on Artificial intelligence, Robotics and Control, AIRC 2022

作者： Jan, Gene Eu Su, Kuan-Lin Hsieh, Hui-Ching Luo, Chaomin Tainan National University of the Arts Tainan City Taiwan National Taipei University Department of Electrical Engineering New Taipei City Taiwan Mississippi State University Department of Electrical and Computer Engineering Mississippi State United States

ISBN: (纸本)9781665459471

k-Nearest Neighbor (k-NN) is a well-known instance-based learning algorithm;widely used in pattern recognition. A classifier can generate highly accurate predictions if provided with sufficient training instances. Thus, it plays a pivotal role in many fields. However, though its accuracy can improve with more data, the need for computational resources increases as well. In this paper, we propose a novel approach which pre-partitions instance space into smaller cells in order to reduce computational cost and greatly reduce the time complexity. Assume every instance is mapped to a point in the d-{dimensional} Euclidean space and a training set D contains n training instances. Given a query instance, the brute force k-{NN} algorithm has the O(nd) time complexity for predicting the class of a query instance. This algorithm can improve the time complexity. © 2022 IEEE.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Third international conference on Communications, Information System, and Data Science, CISDS 2024

Third International Conference on Communications, Informatio...

引用

3rd international conference on Communications, Information System, and Data Science, CISDS 2024

ISBN: (纸本)9781510688315

The proceedings contain 18 papers. The topics discussed include: client dependability evaluation in federated learning framework;FPGA-based hardware optimization and implementation of YOLOv4-tiny;MTOClus: multi-type objects clustering in heterogeneous information networks;FPFS: federated privacy-preserving feature selection with privacy techniques for vertical federated learning;renal tumor classification and detection based on artificial intelligence;stat-net: spatio-temporal aggregation transformer network for skeleton-based few-shot action recognition;dynamic feedback-based vulnerability mining method for highly closed terminal protocols;a RevVIT-based discrimination model for concrete crack images;and acquisition of adaptive knowledge in case-based reasoning for the online set-point control of industrial process.

关键词：

来源：评论

学校读者我要写书评

暂无评论

PhishGuard: A Convolutional Neural Network-Based Model for Detecting Phishing URLs with Explainability Analysis 3

PhishGuard: A Convolutional Neural Network-Based Model for D...

引用

3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Islam, Md Robiul Islam, Md Mahamodul Afrin, Mst. Suraiya Antara, Anika Tabassum, Nujhat Amin, Al Uttara University Dept. of Computer Science and Engineering Dhaka Bangladesh University of Oslo Dept. of Informatics Oslo Norway Dept. of Building Engineering and Construction Management Khulna Bangladesh BRAC University Dept. of Electrical and Electronics Engineering Dhaka Bangladesh North South University Dept. of Electrical and Computer Engineering Dhaka Bangladesh Dept. of Computer Science American International Dhaka Bangladesh

ISBN: (纸本)9798350372120

Cybersecurity is one of the global issues because of the extensive dependence on cyber systems of individuals, industries, and organizations. Among the cyber attacks, phishing is increasing tremendously and affecting the global economy. Therefore, this phenomenon highlights the vital need for enhancing user awareness and robust support at both individual and organizational levels. Phishing URL identification is the best way to address the problem. Various machine learning and deep learning methods have been proposed to automate the detection of phishing URLs. However, these approaches often need more convincing accuracy and rely on datasets consisting of limited samples. Furthermore, these black-box intelligent models' decision to detect Suspicious URLs needs proper explanation to understand the features affecting the output. To address the issues, we propose a 1 D Convolutional Neural Network (CNN) and trained the model with extensive features and a substantial amount of data. The proposed model outperforms existing works by attaining an accuracy of 99.85 %. Additionally, our explainability analysis highlights certain features that significantly contribute to identifying the phishing URL. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

A Design pattern-Based Approach for Analyzing MapReduce Applications 3rd

A Design Pattern-Based Approach for Analyzing MapReduce Appl...

引用

3rd international conference on Language Processing and Knowledge Management-LPKM

作者： Bessifi, Mayssa Ben Younes, Ahlem Ben Ayed, Leila Univ Sfax FSEGS Sfax Tunisia Univ Tunis ENSIT Tunis Tunisia Univ Manouba ENSI Manouba Tunisia

ISBN: (纸本)9783031850660;9783031850677

MapReduce is a widespread programming paradigm used to develop scalable parallel applications in various fields. Despite the simplicity of the MapReduce model, using it to effectively solve real-life problems can be challenging for developers and designers. Furthermore, ensuring the reliability and correct requirements of any system is fundamental at the early stage of development, as late corrections are estimated to be more than 200 times greater than corrections during requirement engineering. Therefore, a systematic approach is required to assist designers in developing reliable MapReduce applications. In this paper, we present a design pattern-based approach to the specification and formal verification of MapReduce applications using the BPMN notation and the Event B method.

关键词： MapReduce Design pattern Fromal verification BPMN Event B

来源：评论

学校读者我要写书评

暂无评论

An Efficient Scheme for Facial Expression recognition using Random Forest and CNN 3

An Efficient Scheme for Facial Expression Recognition using ...

引用

3rd international conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Susan Jacob, Sharon Mahatma Gandhi University Faculty School of Artificial Intelligence and Robotics Kerala Kottayam India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

As humans, we use our facial expressions to communicate our thoughts and feelings without saying a word. The recognition of these facial expressions can provide a better idea of people's thoughts or opinions. At present, the high performance of deep learning procedures has influenced the high efficiency of image recognition systems. This paper proposes a Facial Expression recognition System (FER) using Convolutional Neural Network (CNN). We have made use of features such as Gabor wave coefficients, Histogram of Oriented Gradient (HOG), Speed-Up Robust Features (SURF), and Local Binary patterns (LBP). We have used the Random Forest algorithm for the selection of the best features from the extracted feature set, accordingly, the learning procedure can be faster. The widely used CK+ database can be used for the appraisal of our proposed system. We have also compared our proposed method against similar FER systems and the consequences are satisfactory. © 2022 IEEE.

关键词： Local binary pattern

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence based Self-Driving Car using Robotic Model 3

Artificial Intelligence based Self-Driving Car using Robotic...

引用

3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Sujitha, S. Pyari, Surat Jhansipriya, W.Y. Roopeswar Reddy, Yannam Vinod Kumar, R. Ravi Nandan, P. New Horizon College of Engineering Department of Electrical and Electronics Engineering Bangalore India

ISBN: (纸本)9781665462167

The future cars are more dependent on the internet. It is all-electric and independent, where both the knowledge is equally required. The expanded requirement for safe electronic frameworks in vehicles, that drivers and travelers can depend on, are the underpinning of trust and shape the future towards more elevated levels of robotized driving. The effective and business utilization of self-driving/driverless/automated/computerized vehicle will make human existence more straightforward. This article discusses about this challenge. This paper surveys the vital innovation of a self-driving vehicle. In this paper, the four vital advances in self-driving vehicle, in particular, red and green light detection, object detection, lane end detection and stop sign detection, are tended to and overviewed. The principal research establishments and bunches in various nations are summed up. At last, the discussions of self-driving vehicle are talked about and the improvement pattern of self-driving vehicle is anticipated. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Utilizing the Random Forest Algorithm to Enhance Alzheimer's disease Diagnosis 3

Utilizing the Random Forest Algorithm to Enhance Alzheimer's...

引用

3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Kaur, Chamandeep Panda, Tuhina Panda, Subhasis Rahman Mohammed Al Ansari, Abdul Nivetha, M. Kiran Bala, B. Jazan University Dept of It Saudi Arabia Gandhi Institute for Education and Technology Computer Science Engineering India Gandhi Institute for Education and Technology Electrical and Computer Science Engineering India Salmanyia Hospital Department of Surgery Bahrain K.Ramakrishnan College of Engineering Department of Artificial Intelligence and Data Science Tamil Nadu Trichy India

ISBN: (纸本)9781665462167

machine learning is widely used in many aspects of healthcare. The development of medical technology has made it possible to gather better data for early disease symptom diagnosis. This study makes an effort to categorize Alzheimer's disorder. Alzheimer's disease is a fatal disorder that may result in memory loss and mental impairment. To prepare for medical attention, this needs early disease diagnosis. Magnetic resonance imaging (MRI) can be used to accurately and non-invasively diagnose Alzheimer's disease. Effective feature extraction and segmentation techniques are necessary for the accurate diagnosis of MRI images. Utilizing MRI data of the brain's white matter, grey matter, and cerebrospinal fluid, feature selection is carried out. Random forest trees are used in standard machine learning methods like regression and classification. The results of the utilized method were next contrasted with those of other machine learning techniques. As a result, RF model-based interpolation analysis surpasses the RF non-imputation method with greater accuracy, specificity, sensitivity, f-measure, and ROC. © 2023 IEEE.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Facial Expression Classification using Fusion of Deep Neural Network in Video

Facial Expression Classification using Fusion of Deep Neural...

引用

IEEE/CVF conference on Computer Vision and pattern recognition (CVPR)

作者： Kim Ngan Phan Hong-Hai Nguyen Van-Thong Huynh Kim, Soo-Hyung Chonnam Natl Univ Dept Artificial Intelligence Convergence Gwangju South Korea

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

For computers to recognize human emotions, expression classification is an equally important problem in the human-computer interaction area. In the 3rd Affective Behavior Analysis In-The-Wild competition, the task of expression classification includes eight classes with six basic expressions of human faces from videos. In this paper, we employ a transformer mechanism to encode the robust representation from the backbone. Fusion of the robust representations plays an important role in the expression classification task. Our approach achieves 30.35% and 28.60% for the F-1 score on the validation set and the test set, respectively. This result shows the effectiveness of the proposed architecture based on the Aff-Wild2 dataset and our team archives 5th for the expression classification task in the 3rd Affective Behavior Analysis In-The-Wild competition.

关键词： Human computer interaction Emotion recognition Computational modeling Neural networks Transformers Behavioral sciences pattern recognition

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 << < 56 57 58 59 60 61 62 63 64 65 > >>

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：