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

6,793 篇 会议
630 册 图书
130 篇 期刊文献

馆藏范围

7,552 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

3,899 篇 工学
- 3,090 篇 计算机科学与技术...
- 1,403 篇 软件工程
- 794 篇 电气工程
- 679 篇 信息与通信工程
- 503 篇 控制科学与工程
- 299 篇 生物工程
- 281 篇 生物医学工程（可授...
- 265 篇 机械工程
- 191 篇 光学工程
- 163 篇 电子科学与技术（可...
- 145 篇 仪器科学与技术
- 140 篇 化学工程与技术
- 59 篇 安全科学与工程
- 45 篇 材料科学与工程（可...
- 36 篇 交通运输工程
1,222 篇 理学
- 673 篇 数学
- 356 篇 物理学
- 334 篇 生物学
- 198 篇 统计学（可授理学、...
- 147 篇 化学
- 105 篇 系统科学
553 篇 管理学
- 314 篇 管理科学与工程(可...
- 255 篇 图书情报与档案管...
- 59 篇 工商管理
274 篇 医学
- 230 篇 临床医学
- 109 篇 基础医学(可授医学...
- 75 篇 药学(可授医学、理...
66 篇 法学
- 62 篇 社会学
51 篇 艺术学
- 49 篇 设计学（可授艺术学...
42 篇 农学
- 39 篇 作物学
21 篇 教育学
19 篇 文学
18 篇 经济学
5 篇 军事学

主题

3,150 篇 pattern recognit...
535 篇 feature extracti...
429 篇 artificial intel...
385 篇 neural networks
295 篇 data mining
278 篇 machine learning
234 篇 face recognition
224 篇 pattern matching
215 篇 support vector m...
203 篇 image segmentati...
194 篇 pattern classifi...
193 篇 computer imaging...
183 篇 computer science
182 篇 local binary pat...
168 篇 computational mo...
159 篇 computer vision
147 篇 humans
146 篇 testing
142 篇 accuracy
141 篇 training

机构

40 篇 school of comput...
38 篇 national laborat...
25 篇 institute of ima...
24 篇 center for resea...
24 篇 computer vision ...
22 篇 institute of ima...
22 篇 university of ch...
21 篇 department of co...
20 篇 indian statistic...
19 篇 national laborat...
19 篇 institute of com...
16 篇 tongji universit...
16 篇 chinese academy ...
15 篇 institute for pa...
14 篇 national center ...
14 篇 chinese acad sci...
14 篇 częstochowa univ...
13 篇 agh university o...
13 篇 school of electr...
12 篇 indian stat inst...

作者

35 篇 yang jie
31 篇 de-shuang huang
25 篇 tieniu tan
23 篇 umapada pal
19 篇 ryszard tadeusie...
19 篇 liang wang
18 篇 ajith abraham
17 篇 marcin korytkows...
17 篇 lu hanqing
17 篇 jacek m. zurada
17 篇 leszek rutkowski
16 篇 jie yang
16 篇 zhenan sun
16 篇 shamsuddin siti ...
16 篇 pal umapada
15 篇 wang da-han
15 篇 chew lim tan
15 篇 rafał scherer
14 篇 xu changsheng
14 篇 lotfi a. zadeh

语言

7,403 篇 英文
84 篇 其他
77 篇 中文

检索条件"任意字段=International Conference of Soft Computing and Pattern Recognition"

共 7554 条记录，以下是701-710 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：

Innovative Deep Learning Techniques for Solving Complex Computer Vision Challenges and Enhancing pattern recognition Accuracy

Innovative Deep Learning Techniques for Solving Complex Comp...

引用

Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC), international conference on

作者： T. Jayachitra S. Sathya Ramesh P S Jothikumar R Gouri M. S Mohammed Waheeduddin Hussain Department of Electrical Electronics and Communication Engineering Sharda University Greater Noida India Department of Artificial Intelligence and Data Science GRT Institute of Engineering and Technology Tiruttani India Department of Smart Computing Vellore Institute of Technology Vellore India Department of Computer Science and Engineering Shadan College of Engineering and Technology Hyderabad India Department of Computer Science and Engineering Baselios Mathews - II College of Engineering Sasthamcotta Kollam India Department of Information Technology Shadan College of Engineering and Technology Peerancheru Hyderabad India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

The proposed work provides an in-depth analysis of DL techniques to enhance pattern recognition accuracy in difficult computer vision applications. This background explains the present status of the problems in the area and motivates the development of a complex framework that blends innovative neural network topologies, state-of-the-art optimization approaches, and inventive data augmentation strategies. Among the methods are CNNs enhanced with residual blocks and attention mechanisms, which are implemented using the TensorFlow deep learning framework. The results demonstrate significant improvements over baseline models on a number of measures. Using the CIFAR-10 dataset, the proposed system achieves an impressive 92.5% accuracy and 92.1% F1-score for classification tasks. With an IoU of 78.2% and a mAP of 81.4% in object identification tasks, the system shows its robustness in accurately localizing and recognizing things within photos. These findings have practical ramifications for industries needing accurate visual identification, such autonomous driving and medical imaging, in addition to advancing theoretical knowledge. The efficacy of the architecture highlights its potential to serve as a benchmark for next deep learning studies and applications.

关键词： Deep learning Computer vision Visualization Accuracy Network topology Neural networks Data augmentation Topology pattern recognition Object recognition

来源：评论

学校读者我要写书评

暂无评论

Combining Attention Mechanism and Local-Global Features Association Network for Vehicle Re-identification 11

Combining Attention Mechanism and Local-Global Features Asso...

引用

11th international conference on computing and pattern recognition, ICCPR 2022

作者： Li, Cai-Xia Du, Xia Wu, Yun Wang, Da-Han Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen University of Technology Xiamen361024 China

ISBN: (纸本)9781450397056

Vehicle re-identification (Re-ID) aims to retrieve the target vehicle from a large dataset composed of vehicle images captured by multiple cameras. Most vehicles are difficult to recognize in the environment of low resolution, occlusion, and viewpoint change, which brings challenges to vehicle Re-ID. Existing work usually uses additional attribute information to distinguish different vehicles, such as color, viewpoint, and model. However, this requires expensive manual annotation. Therefore, we propose a three-branch network based on attention mechanism and local-global feature association (AM-LGFA) to improve the accuracy of vehicle Re-ID. In the global branch, the global features of the vehicle are extracted. A multi-scale channel attention module is introduced into the attention branch to suppress irrelevant information and extract important channel features. The features extracted from the backbone are divided into different stripe features in the horizontal direction in the local branch. Then connect each stripe feature with the global information to enhance the context between features. Finally, the features extracted from the three branches are concatenated as the feature representation of the test phase. The experimental results show that the features extracted by the AM-LGFA network are complementary. The effectiveness of this method is verified on two challenging public datasets, VehicleID and VeRi-776. © 2022 ACM.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Cluster-aware Pseudo-Labeling for Supervised Open Relation Extraction 29

Cluster-aware Pseudo-Labeling for Supervised Open Relation E...

引用

29th international conference on Computational Linguistics, COLING 2022

作者： Duan, Bin Wang, Shusen Liu, Xingxian Xu, Yajing Pattern Recognition & Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China

Supervised open relation extraction aims to discover novel relations by leveraging supervised data of pre-defined relations. However, most existing methods do not achieve effective knowledge transfer from pre-defined relations to novel relations, they have difficulties generating high-quality pseudo-labels for unsupervised data of novel relations and usually suffer from the error propagation issue. In this paper, we propose a Cluster-aware Pseudo-Labeling (CaPL) method to improve the pseudo-labels quality and transfer more knowledge for discovering novel relations. Specifically, the model is first pre-trained with the pre-defined relations to learn the relation representations. To improve the pseudo-labels quality, the distances between each instance and all cluster centers are used to generate cluster-aware soft pseudo-labels for novel relations. To mitigate the catastrophic forgetting issue, we design the consistency regularization loss to make better use of the pseudo-labels and jointly train the model with both unsupervised and supervised data. Experimental results on two public datasets demonstrate that our proposed method achieves new state-of-the-arts performance © 2022 Proceedings - international conference on Computational Linguistics, COLING. All rights reserved.

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

AffectPro: Towards Constructing Affective Profile Combining Smartphone Typing Interaction and Emotion Self-reporting pattern 22

AffectPro: Towards Constructing Affective Profile Combining ...

引用

24th ACM international conference on Multimodal Interaction, ICMI 2022

作者： Hari, Satchit Ajay, N. Sarcar, Sayan Sen, Sougata Ghosh, Surjya Bits Pilani Goa India Birmingham City University United Kingdom

ISBN: (纸本)9781450393904

The ubiquity of smartphones and the widespread usage of text entry by soft keyboard in different instant messaging applications (e.g., WhatsApp, FB messenger) have opened the possibilities of inferring emotions from longitudinal typing data. To build this emotion inference engine, we apply machine learning models on features extracted from user's typing patterns (not content). However, one major challenge encountered while developing the emotion inference model is the requirement of individual training data as typing patterns are often person-specific. In this paper, we investigate the possibility of combining typing pattern with emotion self-reporting to identify a group of similar users so that the training data among these users can be shared to fulfill the requirement of personalized dataset. We develop a framework AffectPro, which quantifies the typing interaction behavior (e.g., typing speed, error rate) and self-reporting pattern (e.g., emotion state transition probability) to construct the affective profiles of users. We evaluated AffectPro in a 6-week in-the-wild study involving 28 users, who used an Android application encompassing a custom keyboard to perform all their typing activities, and to report their instantaneous emotions. We extracted different typing signatures and self-report behavior details from the collected dataset (≈ 5000 typing sessions, ≈ 108 hours of typing data) to construct the affective profile of users. Our results demonstrate similarity across users in terms of typing signature, emotion self-reporting pattern, and a combination of both;which can be leveraged to share training data among similar users to overcome the challenges of personalized data collection. © 2022 ACM.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

Application of pattern recognition in Computer Image Processing

Application of Pattern Recognition in Computer Image Process...

引用

international conference on Multi-modal Information Analytics, MMIA 2021

作者： Yang, Pei Xi’an Fanyi University Xi’an Shaanxi China

ISBN: (纸本)9783030748135

The application of computer image processing technology is more and more extensive, which is involved in many fields, and improves the image quality. pattern recognition technology is a new recognition technology extended from artificial intelligence technology, which plays a very important role in computer image processing. It can not only improve the efficiency of image processing, but also ensure the accuracy of the image. This paper first introduces the pattern recognition technology, especially its advantages, then analyzes its application principle, and finally launches the practical application and development of pattern recognition technology. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Facial emotion recognition based on Textural pattern and Convolutional Neural Network 4

Facial emotion recognition based on Textural pattern and Con...

引用

4th IEEE international conference on computing, Power and Communication Technologies, GUCON 2021

作者： Mukhopadhyay, Moutan Dey, Aniruddha Shaw, Rabindra Nath Ghosh, Ankush Bengal Institute of Technology Department of Computer Science Engineering Kolkata India MAKAUT Department of Information Technology Kolkata India Galgotias University Department of EC and Communication Engineering India School of Engineering and Applied Science Neotia University Kolkata India

ISBN: (纸本)9781728199511

Human emotional states can be detected by various ways such as analysingthe brain signals (EEG), speech, skin responses, facial expressions, body gestures etc. But facial expressions recognition is one of the popular techniquesand easy to detect with computers using various computer visions techniques. In this work, we have proposed a new approach to detect basic facial expressions from textural images using deep learning model Convolution neural network (CNN). In the proposed approach textural images of human faces are generated using Local binary pattern(LBP) method and trained the CNN model with the LBPimages. In the proposed approach all the images of extended Cohn-Kanade(CK+)dataset are converted into LBP images that are used to train the CNN model. The performance of proposed facial expression recognition system has been validated on modifiedCK+dataset. Facial emotionrecognition Accuracy of conventional CNN model with CK+ dataset and proposed method on modified CK+ dataset is also compared. © 2021 IEEE.

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Anomolous Behavioral pattern Analysis for IoT Application Using Firewall

Anomolous Behavioral Pattern Analysis for IoT Application Us...

引用

Electrical Electronics and computing Technologies (ICEECT), international conference on

作者： Mayank Agrawal Preeti Badhani Neha Tripathi Neeraj Kumar Pandey Amit Kumar Mishra Ankur Dumka Department of Computer Engineering & Applications GLA University Mathura India Department of CSE Graphic Era Hill University Dehradun Uttarakhand India Department of CSE Graphic Era (Deemed to be University) Dehradun India Department of CSE Women Institute of Technology Dehradun Uttarakhand India

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

As Internet of Things (IoT) devices grow in many areas, such as smart homes, healthcare, business automation, and transportation, providing a security mechanism also becomes important. This brief presents a security solution that uses electronic technology to enhance IoT applications against various cyber threats. The solution begins by identifying the unique security challenges posed by the IoT ecosystem, including device diversity, access restrictions, and communication gaps. Recognizing the important role of firewalls in network security, our approach includes firewall resources designed for IoT environments. This article includes a behavioral analysis to identify negative behavioral patterns that indicate potential security hazards resulting in threat and response. It proposes a new concept that integrates machine learning algorithms with an electronic engine to crack code. Extensive experiments have been conducted to evaluate the effectiveness of the Framework. Using IoT traffic data from various applications. The results show that it is possible to identify bad patterns, including interference of illegal equipment, unreliable information, and poor communication.

关键词： Firewalls (computing) Transportation Telecommunication traffic Smart homes Real-time systems Internet of Things Security Object recognition pattern analysis Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

(Street) Lights Will Guide You: Georeferencing Nighttime Astronaut Photography of Earth

(Street) Lights Will Guide You: Georeferencing Nighttime Ast...

引用

IEEE Computer Society conference on Computer Vision and pattern recognition Workshops (CVPRW)

作者： Alex Stoken Peter Ilhardt Mark Lambert Kenton Fisher Jacobs Technology NASA Johnson Space Center NASA Johnson Space Center

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Astronaut photography from the international Space Station provides the highest spatial resolution nighttime Earth observations imagery publicly available, offering up to a 150x increase in resolution over other freely accessible satellite data sources. Yet, this imagery is underutilized in science applications because it lacks the geolocation meta-data required for downstream analysis. We present Night-Match, a fast and accurate method for localizing and geo-rectifying nighttime astronaut photography. By combining street network data with daytime satellite imagery, we produce a reliable reference target for similarity detection via pairwise image matching. We curate and release the Astronaut Imagery Matching Subset - Night (AIMS-Night), a collection of 363 images and ground truth localizations, and benchmark our method against this set to establish a robust localization pipeline. Our method correctly localizes 81.8% of AIMS-Night, and can be quickly deployed on the over 2 million nighttime astronaut photographs to produce a high quality analysis-ready data product.

关键词： Photography Location awareness Earth Roads Geology soft sensors Urban areas

来源：评论

学校读者我要写书评

暂无评论

Enhancing Graph Database Interaction through Generative AI-Driven Natural Language Interface for Financial Fraud Detection

Enhancing Graph Database Interaction through Generative AI-D...

引用

international conference on computing and Networking Technology (ICCNT)

作者： T Simran J Geetha Department of Computer Science and Engineering Ramaiah Institute of Technology Bangalore India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The rapid evolution of financial services has led to an increase in fraudulent activities, necessitating advanced detection methods. Traditional techniques often struggle with the volume and complexity of financial transactions, leading to inaccuracies and delays. This research addresses the enhancement of graph database interaction through a generative AI-driven natural language interface for more accurate fraud detection. We employ the T5 and LLaMA-2 models, trained on a balanced dataset of financial transactions, to recognize fraud patterns. The $\mathbf{T 5}$ model handles natural language queries, extracting key details such as transaction amounts and account numbers. The LLaMA-2 model generates predictions on the likelihood of transactions being fraudulent. The system then converts these processed queries into Cypher queries for the Neo4j graph database to retrieve relevant transaction data. This approach enables efficient pattern analysis and interactive data exploration. Experimental results demonstrate that our system accurately identifies fraudulent transactions, significantly reducing the time and expertise needed for detection. This approach makes use of Neo4j’s powerful features to increase the efficacy and precision of financial detection systems for fraud.

关键词： Databases Computational modeling Natural languages Finance Predictive models Feature extraction Fraud pattern recognition pattern analysis Financial services

来源：评论

学校读者我要写书评

暂无评论

Knock Detecting Door Unlock System using IOT

Knock Detecting Door Unlock System using IOT

引用

Intelligent and Innovative Technologies in computing, Electrical and Electronics (IITCEE), international conference

作者： Divyam Arora Anika Kirana Venkat Sudarshan Manjunath G Asuti Dept. of ECE B N M Institute of Technology Bengaluru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

This paper presents the design and implementation of a Knock Detecting Door Lock System, aimed at enhancing security by eliminating traditional lock and key mechanisms. The proposed system utilizes an ESP32-based setup to detect specific knocking patterns, ensuring that only authorized individuals can unlock the door. The system addresses common security issues associated with key duplication and passcode vulnerabilities by relying on a personalized knocking sequence. Key features include the ability to set, and update knocking patterns, detect discrepancies, and maintain a balance between security and convenience. The hardware components include an ESP32, piezo sensors, and a servo motor, while the software is developed using the Arduino IDE. It can also incorporate two-factor authentication by generating a One-Time Password (OTP) when a valid knocking pattern is recognized. The OTP is sent to the user’s mobile device as an additional verification step before access is granted. By integrating the knock-based mechanism with the OTP feature, this system offers a robust, user-friendly solution that addresses both analog and digital security needs. The system’s innovative approach offers a cost-effective, efficient, and secure solution for modern door locking needs, with potential applications in various settings, including residential and commercial properties.

关键词： Vibrations Accuracy Authentication Sensor systems software pattern recognition Security Intelligent sensors Smart phones Testing

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 << < 67 68 69 70 71 72 73 74 75 76 > >>

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：