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

2,980 篇 会议
261 册 图书
58 篇 期刊文献
1 篇 学位论文

馆藏范围

3,300 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,988 篇 工学
- 1,553 篇 计算机科学与技术...
- 772 篇 软件工程
- 499 篇 电气工程
- 402 篇 光学工程
- 288 篇 信息与通信工程
- 263 篇 控制科学与工程
- 170 篇 机械工程
- 134 篇 生物工程
- 119 篇 生物医学工程（可授...
- 118 篇 电子科学与技术（可...
- 93 篇 仪器科学与技术
- 65 篇 材料科学与工程（可...
- 52 篇 安全科学与工程
- 45 篇 化学工程与技术
- 45 篇 交通运输工程
- 22 篇 建筑学
- 22 篇 土木工程
1,038 篇 理学
- 828 篇 物理学
- 233 篇 数学
- 146 篇 生物学
- 62 篇 统计学（可授理学、...
- 42 篇 化学
- 22 篇 系统科学
428 篇 医学
- 416 篇 临床医学
- 44 篇 基础医学(可授医学...
- 30 篇 药学(可授医学、理...
232 篇 管理学
- 162 篇 管理科学与工程(可...
- 76 篇 图书情报与档案管...
- 24 篇 工商管理
34 篇 农学
- 31 篇 作物学
21 篇 法学
12 篇 经济学
8 篇 教育学
6 篇 军事学
6 篇 艺术学
5 篇 文学

主题

589 篇 machine vision
558 篇 image processing
532 篇 computer vision
243 篇 machine learning
204 篇 image segmentati...
198 篇 feature extracti...
192 篇 artificial intel...
158 篇 image processing...
150 篇 pattern recognit...
144 篇 deep learning
133 篇 cameras
91 篇 computational mo...
91 篇 training
85 篇 visualization
84 篇 object detection
84 篇 image recognitio...
82 篇 image analysis
82 篇 inspection
79 篇 information syst...
79 篇 image edge detec...

机构

10 篇 center for machi...
9 篇 tongji universit...
7 篇 chongqing univer...
7 篇 hefei university...
7 篇 south china norm...
7 篇 university of ox...
7 篇 harbin institute...
7 篇 univ minnesota c...
6 篇 department of co...
6 篇 moscow state uni...
6 篇 university of no...
6 篇 dipartimento di ...
6 篇 dipartimento di ...
6 篇 graz university ...
6 篇 computational sc...
6 篇 don state tech u...
6 篇 beijing institut...
6 篇 center for machi...
6 篇 dipartimento di ...
6 篇 university of fr...

作者

18 篇 de-shuang huang
13 篇 waltz fm
10 篇 ngoc thanh nguye...
10 篇 abdenour hadid
9 篇 stan sclaroff
9 篇 batchelor bg
9 篇 voronin v.
8 篇 semenishchev e.
7 篇 andrea vedaldi
7 篇 meriaudeau f
7 篇 alberto del bimb...
6 篇 haijun zhang
6 篇 miller jwv
6 篇 ikenaga takeshi
6 篇 tianyong hao
6 篇 jan-michael frah...
6 篇 zelensky a.
6 篇 thomas brox
6 篇 beyerer juergen
6 篇 hugo jair escala...

语言

3,215 篇 英文
49 篇 其他
36 篇 中文
7 篇 土耳其文
1 篇 俄文

检索条件"任意字段=Conference on Image Processing - Machine Vision Applications VI"

共 3300 条记录，以下是181-190 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：

Advancing Multi-Class Arc Welding Defect Classification: DEEPTLWELD Intelligent System Utilizing Computer vision, Deep Learning, and Transfer Learning on Radiographic X-ray images for Bangladesh's Manufacturing Sector

Advancing Multi-Class Arc Welding Defect Classification: DEE...

引用

2024 IEEE International conference on Computing, applications and Systems, COMPAS 2024

作者： Chowdhury, Avijit Chittagong University of Engineering and Technology Department of Mechanical Engineering Chattogram4369 Bangladesh

ISBN: (纸本)9798331529765

Welding defects are a crucial problem in the manufacturing industry. However, the industry faces enormous losses for these defects. Conditional monitoring and quality control can reduce this loss. In Industry 4.0, artificial intelligence revolutionized every field. This research aims to improve industrial automation by creating a multi-class classification system through digital image processing, deep learning, and transfer learning - a real-time application integrated with deep learning, transfer learning, image processing, and MLOPS operations. Accurate prediction occurred by various models, such as custom CNN and pre-trained models (InceptionV3, EfficientNetB7, DenseNet201, and ResNet152). DEEPTLWELD system was developed using a bespoke dataset of 4,000 radiographic X-ray pictures with four frequent categories of defects that are essential for tackling difficulties faced by local industry challenges. This dataset is All radiographic images processed with image processing techniques (distance transform, watershed transform, edge detection). In the transfer learning part, weights were loaded manually as those weights performed better with a particular model. Out of the networks, custom CNN achieved high accuracy with 98% after fine-tuning. The deployment of the produced model in a production environment developed with a Streamlit framework is ensured by its smooth integration into a machine learning pipeline housed on Amazon EC2 servers. This intelligent system has the potential for broader applications in inclusive technology. © 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

Electoral Symbols and Vote detection in Paper Ballots - A Case from Nepal's Election 17

Electoral Symbols and Vote detection in Paper Ballots - A Ca...

引用

17th International conference on machine vision, ICMV 2024

作者： Shrestha, Raju Acharya, Suraj Department of Computer Science Oslo Metropolitan University Oslo Norway

ISBN: (纸本)9781510688278

This paper investigates the potential of advanced object detection technologies to automate and enhance the accuracy and efficiency of the vote counting process in democratic elections that utilize paper-based ballots with electoral symbols. The study focuses on detecting electoral symbols and votes on paper ballots by utilizing two state-of-the-art object detection models: Faster R-CNN, and YOLO. These models were fine-tuned by training them with the ballot papers created using the dataset prepared from the electoral symbols used in Nepal's general election to ensure high accuracy and reliability in recognizing and validating votes. The system's effectiveness was demonstrated through a comparison of the models, highlighting the superior performance of Faster R-CNN in terms of precision, despite its slower processing speed compared to YOLO. The results indicate that incorporating object detection technologies into electoral systems can significantly improve efficiency of vote counting process. The study underscores the potential for broader applications of these technologies in promoting transparent and fair elections, especially in countries like Nepal, where traditional paper ballots are still prevalent. This innovative approach ensures a more reliable and efficient electoral process, reducing human error and increasing trust in election outcomes. © 2025 SPIE.

关键词： Object detection Systems modeling image processing Performance modeling Transparency Data modeling Artificial intelligence Deep learning

来源：评论

学校读者我要写书评

暂无评论

Computer vision Based Hybrid Classroom Attention Monitoring

Computer Vision Based Hybrid Classroom Attention Monitoring

引用

2024 IEEE International conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Rawat, Saniya Rodrigues, Malivia Sheregar, Prateeksha Wagaskar, Kalpita Ajinkya Tripathy, Amiya Kumar Mumbai India

ISBN: (纸本)9798350382693

This research presents a novel computer vision-based attention monitoring system designed for both online and offline contexts. Leveraging advanced image processing and machine learning algorithms, the system analyzes human gaze patterns, eye movements, and facial expressions to accurately gauge attention levels. In online scenarios, the system employs real-time webcam-based gaze tracking and facial recognition to provide immediate insights into user engagement during activities like video conferencing and virtual meetings. For offline analysis, recorded video footage is retrospectively examined, facilitating applications in education, workplace productivity, and user experience assessments. Privacy considerations are addressed through the implementation of privacy-preserving techniques. Experimental results demonstrate the system's efficacy in monitoring attention dynamics across diverse settings, contributing to a deeper understanding of human attention in various domains. © 2024 IEEE.

关键词： video conferencing

来源：评论

学校读者我要写书评

暂无评论

Embedded Intelligence for Safety and Security machine vision applications 21st

Embedded Intelligence for Safety and Security Machine Vision...

引用

21st International conference on image Analysis and processing (ICIAP)

作者： Lioupis, Panagiotis Dadoukis, Aris Maltezos, Evangelos Karagiannidis, Lazaros Amditis, Angelos Gonzalez, Maite Martin, Jon Cantero, David Larranaga, Mikel Inst Commun & Comp Syst ICCS Zografos 15773 Greece Fdn Tekniker Inaki Goenaga 5 Eibar 20600 Spain

ISBN: (纸本)9783031133244;9783031133237

Artificial intelligence (AI) has experienced a recent increase in use across a wide variety of domains, such as image processing for security applications. Deep learning, a subset of AI, is particularly useful for those image processing applications. Deep learning methods can achieve state-of-the-art results on computer vision for image classification, object detection, and face recognition applications. This allows to automate video surveillance reducing human intervention. At the same time, although deep learning is a very intensive task in terms of computing resources, hardware and software improvements have emerged, allowing embedded systems to implement sophisticated machine learning algorithms at the edge. Hardware manufacturers have developed powerful co-processors specifically designed to execute deep learning algorithms. But also, new lightweight open-source middleware for constrained resources devices such as EdgeX foundry have emerged to facilitate the collection and processing of data at sensor level, with communication capabilities to cloud enterprise applications. The aim of this work is to show and describe the development of Smart Camera Systems within S4AllCities H2020 project, following the edge approach.

关键词： Horizon2020 Edge EdgeX foundry machine vision Artificial intelligence Deep learning

来源：评论

学校读者我要写书评

暂无评论

GRADIENT PATTERN ANALYSIS APPLIED FOR COMPUTER vision IN MEDICAL ULTRASOUND DIAGNOSIS 17

GRADIENT PATTERN ANALYSIS APPLIED FOR COMPUTER VISION IN MED...

引用

17th International conference on Interfaces and Human Computer Interaction 2023, IHCI 2023, the 17th International conference on Computer Graphics, visualization, Computer vision and image processing 2023, CGVCviP 2023 and 16th International conference on Game and Entertainment Technologies 2023, GET 2023

作者： Sautter, Rubens Andreas Rosa, Reinaldo Roberto Alavarce, Debora Cristina Silva, Daniel Guimarães Av. Dos Astronautas 1.758 CEP 12245-027 São José dos Campos SP Brazil Hipocampus EdTech - Digital Learning R. do Serimbura 320 CEP 12243-360 São José dos Campos SP Brazil

ISBN: (纸本)9789898704498

This paper describes a new application of the technique known as Gradient Pattern Analysis (GPA), focused here on computer vision. In the GPA domain, the image is translated into a tessellation triangulation field based on the vectors positions that make up the gradient lattice of the matrix image. The GPA version considered here generates three attributes (G1, G2 and G3) that can be used as labels for a supervised machine-learning model. The case study presented here shows that GPA is a useful tool for real-time fetal biometry from 2D ultrasound images. The application in obstetrics indicates that the technique can also be useful for learning diagnostic imaging in gynecology, hepatology and oncology. The generalization of the technique to other applications in practical learning in health is discussed. © 2023 Proceedings of the International conferences on Interfaces and Human Computer Interaction 2023, IHCI 2023;Computer Graphics, visualization, Computer vision and image processing 2023, CGVCviP 2023;and Game and Entertainment Technologies 2023, GET 2023. All rights reserved.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

Identification Method of Dress Pattern Drawing based on machine vision Algorithm 3

Identification Method of Dress Pattern Drawing based on Mach...

引用

3rd International conference on Computer vision, image and Deep Learning and International conference on Computer Engineering and applications, CviDL and ICCEA 2022

作者： Lyu, Ke Yan, Haizhang Zhejiang Sci-Tech University School of International Education Zhejiang310000 China Xidian University School of Computer Science and Technology Xi'an71000 China

ISBN: (纸本)9781665459112

This paper uses the machine vision method to identify the skirt module. We have constructed three kinds of machine recognition models of skirt profile processing, structure analysis of style drawing, and size estimation. The author constructs a relatively complete image recognition system for dress pattern drawing. In addition, we conducted an effect evaluation with a certain number of samples at the later stage of the experiment. This study has A good effect in distinguishing an A-type skirt from an H-type skirt, identifying the reasonable degree and length of the skirt, and determining the quantity statistics of each component element in the skirt pattern diagram. © 2022 IEEE.

关键词： image recognition

来源：评论

学校读者我要写书评

暂无评论

MFA-DAF: Unsupervised Multimodal Medical image Fusion via Multiscale Fourier Attention and Detail-Aware Fusion Strategy 2

MFA-DAF: Unsupervised Multimodal Medical Image Fusion via Mu...

引用

2nd International conference on image processing, Computer vision and machine Learning, ICICML 2023

作者： Xie, Xinyu Zhang, Xiaozhi Xiong, Dongping Ouyang, Lijun University of South China School of Electrical Engineering Hengyang China University of South China School of Computing/Software Hengyang China

ISBN: (纸本)9798350331417

Multimodal medical image fusion is vital for extracting complementary information and generating comprehensive images in clinical applications. However, existing deep learning-based fusion approaches face challenges in effectively utilizing frequency-domain information, designing appropriate integration strategies and modelling long-range context correlation. To address these issues, we propose a novel unsupervised multimodal medical image fusion method called Multiscale Fourier Attention and Detail-Aware Fusion (MFA-DAF). Our approach employs a multiscale Fourier attention encoder to extract rich features, followed by a detail-aware fusion strategy for comprehensive integration. The fusion image is obtained using a nested connected Fourier attention decoder. We adopt a two-stage training strategy and design new loss functions for each stage. Experiment results demonstrate that our model outperforms other state of the art methods, producing fused images with enhanced texture information and superior visual quality. © 2023 IEEE.

关键词： Detail-aware Fine-grained information Fourier Transform Multimodal medical image fusion

来源：评论

学校读者我要写书评

暂无评论

Development Of An image Restoration Algorithm Utilizing Generative Adversarial Networks (GAN’s) For Enhanced Performance In Engineering applications: A Comprehensive Approach To Improving image Quality And Clarity Through Advanced machine Learning Techniques

Development Of An Image Restoration Algorithm Utilizing Gene...

引用

2024 IEEE International conference on Innovation and Novelty in Engineering and Technology, INNOVA 2024

作者： Manjunath, T.C. Pavithra, G. Samyama Gunjal, G.H. Ninawe, Swapnil S. Dept. of Electronics & Communication Engineering Rajrajeswari College of Engineering Bangalore India Department of Electronics & Communication Engineering Dayananda Sagar College of Engineering Karnataka Bangalore India Department of Computer Science & Engineering University Visvesvaraya College of Engineering Karnataka Bangalore India

ISBN: (纸本)9798331505134

image restoration, a critical task in computer vision and image processing, focuses on recovering degraded or damaged images to their original, high-quality state. This paper introduces an innovative approach to image restoration using Generative Adversarial Networks (GANs). GANs, a prominent deep learning framework, consist of two neural networks—a generator and a discriminator—that compete to produce and evaluate realistic images. The generator creates images, while the discriminator distinguishes between real and generated ones, refining the generator's capability through adversarial training. Leveraging GANs' ability to learn complex image features, the proposed algorithm restores degraded images affected by noise, blur, and low resolution, producing high-quality, realistic results. Simulation outcomes demonstrate significant advancements in image restoration, showcasing GANs as a powerful tool for addressing challenges in this domain. The study underscores the potential of GANs in generating visually appealing restorations and advancing the state-of-the-art in image processing and restoration tasks. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Planning the trajectory of an object in a confined space using stationary machine vision systems 10

Planning the trajectory of an object in a confined space usi...

引用

conference on Optical Metrology and Inspection for Industrial applications X

作者： Urunov, Salavat Voronin, viacheslav Semenishchev, Evgenii Moscow State Tech Univ STANKIN 1a Vadkovsky Moscow 127055 Russia

ISBN: (纸本)9781510667877;9781510667884

The article proposes an approach to the formation of the trajectory of the spatial movement of a controlled object in a confined space using stationary vision systems. For its implementation, the following main steps are used in the work: 1. Preprocessing of data generated by the machine vision system. The task includes multicriteria image processing in order to minimize the noise component and determine the boundaries of objects. 2. An automated method for adaptive non-local separation of objects on borders, background and objects. 3. Execution of the task of adaptive nonlocal binarization. 4. Building a mask of stationary and current moving objects. 5. Formation of an equidistant displacement trajectory. 6. Checking the trajectory by moving in adjacent frames. 7. Prediction and remeasurement of the position of objects in the frame based on displacement vectors and correction of the object's movement trajectory. 7. Formation of a control team to move an object in a confined space using stationary vision systems. To test the effectiveness, studies were conducted on a set of test sequences. The studies were carried out on a group of cameras in the visible spectrum (1920x1080, RGB, 8 bits) covering the entire field of view. The adaptability of the application of the proposed approach in solving complex problems is showed.

关键词： machine vision edge detection preprocessing multicriteria method planning trajectory

来源：评论

学校读者我要写书评

暂无评论

Research on visual Target Detection and Recognition of Shopping Robots Based on Improved YOLO Algorithm 7th

Research on Visual Target Detection and Recognition of Shopp...

引用

7th International conference on Wireless Communications, Networking and applications, WCNA 2023

作者： Lu, Yufan Zhejiang Gongshang University Hangzhou China

ISBN: (纸本)9789819624089

This research aims to improve the visual target detection and recognition capabilities of shopping robots in various sales environments by optimizing and improving the YOLO algorithm, in order to improve accuracy and real-time performance. The research method involves embedded spatial hierarchical sampling technology and it adapts to image processing of different sizes, uses a separate convolutional neural network structure to reduce computational complexity, and cultivates a more concise network model by refining the effective data of complex models. Experimental results show that the improved YOLO algorithm performs well in weak Its average accuracy has been significantly improved under light, medium light and strong light environments, especially in the detection of small items. A study shows that improved programming significantly improved the vision of shopping assistance robots. Recognition capabilities enable robots to provide more accurate and faster services in real shopping environments. © The Author(s) 2025.

关键词： machine vision

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330页 << < 15 16 17 18 19 20 21 22 23 24 > >>

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：