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

4,618 篇 会议
499 册 图书
66 篇 期刊文献

馆藏范围

5,182 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

3,388 篇 工学
- 2,748 篇 计算机科学与技术...
- 1,819 篇 软件工程
- 728 篇 信息与通信工程
- 723 篇 光学工程
- 668 篇 电气工程
- 415 篇 生物工程
- 363 篇 控制科学与工程
- 348 篇 生物医学工程（可授...
- 239 篇 机械工程
- 228 篇 电子科学与技术（可...
- 125 篇 仪器科学与技术
- 122 篇 化学工程与技术
- 117 篇 安全科学与工程
- 96 篇 交通运输工程
- 91 篇 材料科学与工程（可...
- 67 篇 建筑学
- 57 篇 土木工程
1,684 篇 理学
- 928 篇 物理学
- 725 篇 数学
- 452 篇 生物学
- 204 篇 统计学（可授理学、...
- 119 篇 化学
- 57 篇 系统科学
490 篇 管理学
- 270 篇 图书情报与档案管...
- 242 篇 管理科学与工程(可...
- 79 篇 工商管理
438 篇 医学
- 417 篇 临床医学
- 127 篇 基础医学(可授医学...
- 89 篇 药学(可授医学、理...
60 篇 法学
- 59 篇 社会学
54 篇 农学
35 篇 教育学
31 篇 艺术学
29 篇 经济学
11 篇 文学
10 篇 军事学

主题

820 篇 computer vision
625 篇 pattern recognit...
538 篇 image processing
355 篇 image processing...
348 篇 artificial intel...
336 篇 image segmentati...
276 篇 feature extracti...
203 篇 image recognitio...
176 篇 deep learning
155 篇 computer graphic...
150 篇 computer imaging...
139 篇 face recognition
128 篇 machine learning
121 篇 object recogniti...
120 篇 convolutional ne...
115 篇 object detection
115 篇 image analysis
108 篇 information syst...
105 篇 cameras
105 篇 shape

机构

25 篇 istituto italian...
24 篇 google deepmind ...
24 篇 meta ai barcelon...
23 篇 politecnico di t...
14 篇 national center ...
14 篇 institute of ima...
11 篇 shanghai jiao to...
10 篇 tsinghua univers...
10 篇 university of ch...
10 篇 institute of aut...
9 篇 institute of ima...
9 篇 computer vision ...
8 篇 indian statistic...
8 篇 inria nancy gran...
8 篇 dalian universit...
8 篇 icube université...
8 篇 tongji universit...
8 篇 erasmus mc - uni...
8 篇 beijing institut...
8 篇 tencent jarvis l...

作者

24 篇 cristian canton
24 篇 alessio del bue
24 篇 tatiana tommasi
24 篇 jordi pont-tuset
17 篇 de-shuang huang
14 篇 stefanie speidel
12 篇 wilfried philips
9 篇 paul scheunders
9 篇 h. bischof
9 篇 jie yang
9 篇 stéphane cotin
9 篇 dan popescu
9 篇 mohamed kamel
8 篇 umapada pal
8 篇 aurélio campilho
8 篇 yefeng zheng
8 篇 kok wai wong
8 篇 christian barill...
8 篇 ilias maglogiann...
8 篇 tieniu tan

语言

4,760 篇 英文
402 篇 其他
70 篇 中文

检索条件"任意字段=4th International Conference on Computer Vision, Pattern Recognition and Image Processing"

共 5183 条记录，以下是551-560 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：

Multi-stage Progressive Reasoning for Dunhuang Murals Inpainting 4

Multi-stage Progressive Reasoning for Dunhuang Murals Inpain...

引用

4th IEEE international conference on pattern recognition and Machine Learning, PRML 2023

作者： Liu, Wenjie Shi, Yuqing Li, Jiacheng Wang, Jianhua Du, Shiqiang Northwest Minzu University Chinese National Information Technology Research Institute Lanzhou China Northwest Minzu University College of Electronic Engineering Lanzhou China Northwest Minzu University College of Mathematics and Computer Science Lanzhou China

ISBN: (纸本)9798350324303

Dunhuang murals suffer from fading, breakage, surface brittleness, and extensive peeling affected by prolonged environmental erosion. the recurrent networks achieved promising performance when repairing severe damages to the mural. However, the recurrent reasoning occurs in the single receptive field network, which lacks awareness of different fields of murals. In this paper, we innovatively designed the multi-stage progressive reasoning (MPR) network containing global and local receptive fields. this network can recursively infer the structural and textural features from the hole boundaries and progressively tighten the constraints on the hole center. Moreover, To adaptively fuse feature information at various scales of murals, a multi-scale feature aggregation module (MFA) is designed to empower the capability to select the significant features of murals. the execution of the model is similar to the process of the mural restorer (i.e., inpainting the structure of a damaged mural globally first and then progressively adding the local texture details based on this). Qualitative and quantitative experiments show that our method has excellent and comprehensive performance that exceeds existing image inpainting methods. © 2023 IEEE.

关键词： Fracture mechanics

来源：评论

学校读者我要写书评

暂无评论

Visual Cryptography: A Detailed Analysis 4

Visual Cryptography: A Detailed Analysis

引用

4th international conference on Cognitive Computing and Information processing, CCIP 2022

作者： Mittal, Tanusha Christa, Sharon Graphic Era Deemed to Be University Computer Science and Engineering Dehradun India

ISBN: (纸本)9781665456487

In today's world, securing data is becoming a very important issue for an individual. Some cryptographic techniques are already discovered and some are yet to be revealed. In this paper, we are surveying an advance method of data hiding i.e. Visual Cryptography. Visual cryptography is an encryption technique which hides the information by using images. the encrypted image can be decrypted by the human vision if the correct image key is used. In visual cryptography, we can transform a secret image into various shared images and the combination of these shared images can reveal the secret original image. this paper reviews about visual cryptography, the three techniques of visual cryptography i.e., Binary image, Gray-Scale image and Colored image with its applications. © 2022 IEEE.

关键词： Binary images

来源：评论

学校读者我要写书评

暂无评论

Design of Garbage Intelligent recognition and Automatic Classification Device 4

Design of Garbage Intelligent Recognition and Automatic Clas...

引用

4th international conference on Advances in Electrical Engineering and computer Applications, AEECA 2023

作者： Wu, Jiaqi Zhang, Yuhao Yi, Haibo Deng, Weiping Qu, Tao School of Artificial Intelligence Shenzhen Polytechnic Shenzhen China WeBank Shenzhen China Guangzhou Urban Blockchain Industry Association Guangzhou China

ISBN: (纸本)9798350308082

Artificial Intelligence (AI) has received increasing attention in the field of computer science. and it has been applied in robotics, economic and political decision-making, control systems, and simulation systems. In recent years, there have been efforts to accelerate the classification of household waste, establish a garbage classification and recycling system, and expedite the establishment of a garbage treatment infrastructure for sorting, placement, collection, transportation, and processing. the Raspberry Pi is a credit card-sized microcomputer with a Linux-based operating system. Given the need for a smaller recognition device with higher computational complexity, we choose the Raspberry Pi as our hardware platform for this project. Utilizing the Raspberry Pi's lightweight hardware and AI, intelligent garbage classification can achieve greater accuracy, speed, and efficiency. this article presents an intelligent garbage classification device designed using the Raspberry Pi 4B, which can be used in various scenarios due to its small footprint. the design method proposed in this paper can be widely applied to fields such as smart homes and smart cities. © 2023 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Chaos theory Based Gravitational Search Algorithm For Medical image Segmentation 27th

Chaos Theory Based Gravitational Search Algorithm For Medica...

引用

27th international conference on pattern recognition, ICPR 2024

作者： Rather, Sajad Ahmad Roy, Partha Pratim Das, Sujit Department of Computer Science and Engineering Indian Institute of Technology Roorkee247667 India Department of Computer Science and Engineering National Institute of Technology Telangana506004 India

ISBN: (纸本)9783031781032

Multilevel thresholding plays a crucial role in image processing, with extensive applications in object detection, machine vision, medical imaging, and traffic control systems. It entails the partitioning of an image into distinct regions based on optimal pixel values. However, as the number of threshold levels increases, so does the computational cost for segmentation. To address this challenge, a novel method is proposed namely Chaos theory based Gravitational Search Algorithm (CGSA) for multilevel thresholding. CGSA combines the standard Gravitational Search Algorithm (GSA) for exploration with chaotic maps for exploitation of the complex pixel problem space. In this study, Kapur’s entropy method is utilized to segment sample images into various partitions based on optimal pixel values. the effectiveness of CGSA in real-world scenarios is evaluated using COVID-19 chest CT scan imaging datasets from Kaggle database. the quality, symmetry, and consistency of the segmented output are assessed using metrics like Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Feature Similarity Index Measure (FSIM). Qualitative analysis includes convergence curves, segmented graphs, colormap images, and box plots. Statistical validation is conducted using the signed Wilcoxon rank sum test. Additionally, a comparison is made between CGSA’s performance and that of eight state-of-the-art heuristic algorithms. the findings demonstrate the superior performance of CGSA, evidenced by its reduced computational time and enhanced image quality metrics values. Specifically, CGSA achieved SSIM of 0.81, FSIM of 0.82, and PSNR of 24.27, surpassing the performance of other competitive algorithms. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Harris Hawks Optimization-Based Multilevel thresholding Segmentation of Magnetic Resonance Brain images 4th

Harris Hawks Optimization-Based Multilevel Thresholding Segm...

引用

4th international conference on Communication, Devices and Computing (ICCDC 2023)

作者： thomas, Elisabeth Kumar, S.N. Lincoln University College Kota Bharu15050 Malaysia Department of EEE Amal Jyothi College of Engineering Kerala Kottayam686518 India

ISBN: (纸本)9789819927098

the segmentation role is inevitable in computer vision and image processing for delineating the specific region of interest. In the healthcare sector, the segmentation role is vital in the diagnosis and prediction of diseases. this research work proposes Harris Hawks optimization-based multilevel thresholding segmentation approach for the MR brain images. Multilevel thresholding is an improved version classical thresholding algorithm, and the optimization algorithm chooses the optimum threshold values for the segmentation. the segmentation model was tested on Alzheimer’s MR brain images and validated in terms of performance computer-aided threshold level of 5 which was found to generate satisfactory results in terms of performance metrics. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Face recognition based on principal component analysis (PCA) 4

Face recognition based on principal component analysis (PCA)

引用

4th international conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2022

作者： Qiu, Caihua Ding, Feng Guangdong University of Science and Technology College of Computer Science Dongguan523000 China Bulacan State University Philippines Guangzhou Xinhua University Dongguan China

ISBN: (纸本)9781665463997

the most important thing in the pattern recognition process is image preprocessing. image preprocessing is an important step in the pattern recognition process. Its purpose is to minimize the influence of external interference on the recognition target, and in accordance with the requirements of the face image recognition method standardize the image. In this paper, for the noise-free source image, based on the principal component analysis (PCA) feature extraction algorithm, the image is preprocessed, and the grayscale, normalization, geometric correction, filter transformation and so on are processed in the preprocessing stage. © 2022 IEEE.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Application of Convolutional Neural Networks and vision Transformer Models for Age and Gender Detection 6th

Application of Convolutional Neural Networks and Vision Tran...

引用

6th international conference on Information Systems and Management Science, ISMS 2023

作者： Adeniyi, Abidemi Emmanuel Brahma, Biswajit Awotunde, Joseph Bamidele Aworinde, Halleluyah Oluwatobi Bhuyan, Hemanta Kumar Department of Computer Science Bowen University Osun State Iwo Nigeria McKesson Corporation USA 32559 Lake Bridgeport St FremontCA94555 United States Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Ilorin240003 Nigeria Andhra Pradesh Guntur India

ISBN: (纸本)9783031707889

this research explore the integration and application of advanced deep learning models, specifically Convolutional Neural Networks (CNNs) and vision Transformer (ViT) models, in the field of age and gender detection. the study begins by outlining the significance and challenges of accurate age and gender detection in various domains such as targeted advertising, security, and humancomputer interaction. It then delves into technical aspects of CNNs and ViTs, elucidating their architecture, working principles, and suitability for image-based task. the proposed techniques used in this study was able to differentiate between the following age groups: 0–15, 15–20, 20–25, 25–30, 30–35, and 40. the purpose is to offer a technique for creating and implementing accurate categorization and age estimation systems capable of operating and achieving high accuracy by integrating and applying a variety of feature extractors and algorithms. Pre-processing is evaluating preliminary data, configuring it, and transforming it to a standard format. the feature extraction component of the age and gender prediction technique is crucial. three different extraction methods (ResNet 50, ViT Small, and ViT Base) are used in this section. Convolutional Neural Network (CNN) and vision Transformer (ViT) classifiers were used. this optional component of pattern recognition system design focuses on system accuracy. To assess pattern recognition system performance, several approaches are employed, including Mean Absolute Error (MAE), Cumulative Score (CS), Leave-One-Out Cross-validation, and Confusion Matrix. In this study, however, gender and age prediction were tested using the Confusion Matrix and Mean Absolute Error (MAE). Python was the programming language utilized in this study. Python is a high-level, general-purpose programming language that is interpreted. Precision, recall, f1score and accuracy were the performance matrices used. A precision of 99% was achieved for male classification whi

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Self-Supervised Learning for Point Clouds through Multi-crop Mutual Prediction 4

Self-Supervised Learning for Point Clouds through Multi-crop...

引用

4th IEEE international conference on pattern recognition and Machine Learning, PRML 2023

作者： Zeng, Changyu Wang, Wei Xiao, Jimin Nguyen, Anh Yue, Yutao Institute of Deep Perception Technology JITRI Wuxi China Xi'An Jiaotong-Liverpool University School of Advanced Technology Suzhou China University of Liverpool Department of Computer Science Liverpool United Kingdom

ISBN: (纸本)9798350324303

As the demand for high-level autonomous driving continues to grow, efficient processing of large amount of point cloud data from LiDAR sensors has become a severe issue. Despite its great success, it is extremely difficult, if not impossible, to apply supervised learning in many real-world applications with natural scenes lacking annotations. In addition, removing label dependency and improving algorithm generalization ability are the current key research challenges in 3D deep learning. We propose a crop-based self-supervised learning framework for point clouds called Multi-Crop Mutual Prediction (MCMP). By cropping the original point clouds into different number of multiscale patches and making patches from the same object as close as possible through dynamic updates of online prototypes, the encoder is well able to maintain consistency between both local and global features. MCMP framework is model-agnostic so it is convenient to integrate it into encoders of any architectures. We pre-train three commonly used point cloud feature extraction networks on a single object-level dataset MondelNet40 and evaluate MCMP on three downstream tasks, namely, object classification, partial segmentation and semantic segmentation. Experimental results show that MCMP outperforms the previous crop-based self-supervised approaches in the object classification and semantic segmentation tasks and produces comparable results with the supervised benchmark methods. © 2023 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Research on image Restoration Algorithms Based on Transformer Prediction Networks

Research on Image Restoration Algorithms Based on Transforme...

引用

pattern recognition and Machine Learning (PRML), IEEE international conference on

作者： Qingjuan Wang Shan Xiao Yan Zhou Lin Wang School of Computing Beijing Institute of Technology Zhuhai Zhuhai China School of Innovative Engineering Macau University of Science and Technology Macau China

In recent years, with the rapid development of computer vision, there have been significant advancements in image restoration techniques. However, many current algorithms still struggle with accurately restoring degraded images with lost information. In this paper, we present a new image restoration algorithm called CodeFormerGAN, which is based on the Transformer model. this algorithm consists of three main components: Codebook, CLT network, and CFT. the Codebook module is responsible for learning self-reconstruction and storing high-quality face image parts. the Transformer in the CLT network models the overall composition of the face using low-quality input. the CFT module transforms image features to achieve a flexible balance between restoration quality and fidelity. Additionally, we introduce a GAN-based image super-resolution enhancement algorithm to enhance the sharpness of the restored image. the results of our experiments demonstrate that our proposed method produces higher-quality restoration results and exhibits better robustness when processing images in complex scenes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

4th international conference on Smart Systems: Innovations in Computing, SSIC 2023

4th International Conference on Smart Systems: Innovations i...

引用

4th international conference on Smart Systems: Innovations in Computing, SSIC 2023

ISBN: (纸本)9789819736898

the proceedings contain 60 papers. the special focus in this conference is on Smart Systems: Innovations in Computing. the topics include: An Algorithmic Framework for Clustering Cab Pickup Geo-points for Cab Recommender System (CRS);simulation and Analysis of Routing Protocols Using Real-Time Data in Vehicular Ad Hoc Networks;research Trends and Key themes in the Intersection of Renewable Energy and Smart Homes;smart Attendance System Using Face recognition;Data Augmentation to Improve Fake Account Detection Using ANN;end-to-End Portfolio Optimization Using Transformer Encoder Model for Long Positions Strategy;phonetic Redundancy Avoidance Technique;towards Sustainable Power: A Quantitative Analysis of Environmental Factors and Energy Demand in Different Indian States;customer Segmentation Using K-means Clustering;web Miner: Automated Web Crawling and Database System with Puppeteer and ***;machine Learning-Based Cardiovascular Disease Prediction;Efficient Identification of Waste in Water Bodies with YOLO V7-Object Detection;bumbleBee: the Multi-purpose Voice Assistant;efficientNet Deep Learning Model for computer-Aided Polyps Classification from Colonoscopy images;improved Gastric Cancer Diagnosis with Machine Learning Technique: Addressing Imbalanced Data Distribution;an Effective and Secure Privacy Diagnosis Made Online System for the E-Healthcare Ecosystem Based on Federated Learning;efficientViT: An Efficient vision Transformer for Fire and Smoke image Classification;Tomato Disease Classification Using CNN;artificial Intelligence Application for Electronic Governance to Achieve Sustainability: A Case of Selected Segments of Indian Economy;analyzing Sentiments of Global Workforce Towards Hybrid Work Culture in the New Normal;deep Learning Techniques for Real-Time Object Detection and Classification;Task Scheduling Cost Evaluation over Cloud with Using GA, ACO, PSO.

关键词：

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 << < 52 53 54 55 56 57 58 59 60 61 > >>

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：