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

6,721 篇 会议
330 册 图书
117 篇 期刊文献

馆藏范围

7,167 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
- 806 篇 电气工程
- 771 篇 信息与通信工程
- 592 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
- 212 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
- 127 篇 材料科学与工程（可...
- 120 篇 网络空间安全
- 108 篇 安全科学与工程
- 91 篇 动力工程及工程热...
1,627 篇 理学
- 809 篇 数学
- 493 篇 物理学
- 489 篇 生物学
- 273 篇 统计学（可授理学、...
- 189 篇 化学
- 141 篇 系统科学
843 篇 管理学
- 462 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...
450 篇 machine learning
291 篇 feature extracti...
243 篇 deep learning
203 篇 accuracy
185 篇 support vector m...
134 篇 data mining
128 篇 training
126 篇 neural networks
126 篇 face recognition
104 篇 computer imaging...
103 篇 local binary pat...
102 篇 computer vision
88 篇 image processing...
87 篇 real-time system...
87 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
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

6,318 篇 英文
822 篇 其他
72 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 7168 条记录，以下是481-490 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：

Video extensometry measurement method for materials with large deformations 3

Video extensometry measurement method for materials with lar...

引用

3rd international conference on machine Vision, Automatic Identification, and Detection, MVAID 2024

作者： Shi, Haoran Zhang, Zhijia Yang, Minmin Shenyang University of Technology School of artificial Intelligence China

ISBN: (纸本)9781510681880

This paper addresses the issue of segmentation errors in video extensometer caused by deformation, dispersion, and cracks in markers during the stretching process. A method combining frame-to-frame matching with deep learning is proposed to address the high robustness segmentation problem of black and white markers on materials undergoing large strains. The selection of template position during image matching and the update of the template throughout the stretching process are discussed. Experiments and analysis were conducted on various types of rubber and plastic specimens that exhibit significant strain and irregular deformation. The results demonstrate that this method can be applied to line marker-type video extensometers, enhancing the overall robustness of the measurement algorithm. © 2024 SPIE.

关键词： Image matching

来源：评论

学校读者我要写书评

暂无评论

3rd CAAI international conference on Artificial intelligence, CICAI 2023

3rd CAAI International Conference on Artificial Intelligence...

引用

3rd CAAI international conference on Artificial intelligence, CICAI 2023

ISBN: (纸本)9789819991181

The proceedings contain 100 papers. The special focus in this conference is on Artificial intelligence. The topics include: Equivariant Indoor Illumination Map Estimation from a Single Image;Weakly-Supervised Grounding for VQA with Dual Visual-Linguistic Interaction;STU3: Multi-organ CT Medical Image Segmentation Model Based on Transformer and UNet;integrating Human Parsing and Pose Network for Human Action recognition;lightweight Rolling Shutter Image Restoration Network Based on Undistorted Flow;an Efficient Graph Transformer Network for Video-Based Human Mesh Reconstruction;multi-scale Transformer with Decoder for Image Quality Assessment;low-Light Image Enhancement via Unsupervised Learning;MARS: An Instance-Aware, Modular and Realistic Simulator for Autonomous Driving;GLCANet: Context Attention for Infrared Small Target Detection;fast Point Cloud Registration for Urban Scenes via Pillar-Point Representation;PMPI: Patch-Based Multiplane Images for Real-Time Rendering of Neural Radiance Fields;EFPNet: Effective Fusion Pyramid Network for Tiny Person Detection in UAV Images;end-to-End Object-Level Contrastive Pretraining for Detection via Semantic-Aware Localization;pointerNet with Local and Global Contexts for Natural Language Moment Localization;self-supervised Meta Auxiliary Learning for Actor and Action Video Segmentation from Natural Language;rsMmFormer: Multimodal Transformer Using Multiscale Self-attention for Remote Sensing Image Classification;fashion Label Relation Networks for Attribute recognition;a Modified Fuzzy Markov Random Field Incorporating Multiple Features for Liver Tumor Segmentation;concealed Object Segmentation with Hierarchical Coherence Modeling;weakly Supervised Optical Remote Sensing Salient Object Detection Based on Adaptive Discriminative Region Suppression;SPCTNet: A Series-Parallel CNN and Transformer Network for 3D Medical Image Segmentation;LANet: A Single Stage Lane Detector with Lightweight Attention;Visible and NIR Image Fusion

关键词：

来源：评论

学校读者我要写书评

暂无评论

3rd CAAI international conference on Artificial intelligence, CICAI 2023

3rd CAAI International Conference on Artificial Intelligence...

引用

3rd CAAI international conference on Artificial intelligence, CICAI 2023

ISBN: (纸本)9789819988495

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Development Trend of Artificial intelligence 3

The Development Trend of Artificial Intelligence

引用

3rd international Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2023

作者： Chen, Jiawen Liaoyuan Vocational Technical College Liaoyuan China

This paper aims to discuss the subject concept, progress and future development trend of artificial intelligence(Al), summarize the application prospect of Al technology, and put forward the problems and contradictions existing in the development of Al, It summarizes the ways of man-machine combination to solve this contradictory problem. © The Institution of Engineering & Technology 2023.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Research on Defects in Pipeline Girth Welds of Digital Radiography Test Based on Improved YOLOv8 30th

Research on Defects in Pipeline Girth Welds of Digital Radio...

引用

30th international conference on Computational and Experimental Engineering and Sciences

作者： Niu, Shengyuan Han, Bin Xiao, Wentao Li, Xueda Li, Liying Han, Tao China Univ Petr Sch Mat Sci & Engn West Changjiang Rd Qingdao 266580 Peoples R China

ISBN: (纸本)9783031774911;9783031774898;9783031774881

Defects in girth welds are the main factor causing pipeline failure. Among numerous non-destructive testing technologies, Digital Radiography non-destructive testing technology has become the main non-destructive testing technology due to its high recognition rate and simple equipment. However, the high degree of manual intervention and low recognition rate have become the main factors restricting its development. Therefore, the artificial intelligence recognition of Digital Radiography detection is researched in this article. Firstly, multiple denoising processes are applied to actual Digital Radiography detection images, and the mean filter with a kernel size of 3*3 is obtained to achieve the best denoising effect. Subsequently, various enhancement processes are applied to the denoised image. A linear transformation with a = 0.7 and a Gamma transformation with gamma = 2 has the best Enhancement effect. The Global Attention Mechanism and Bidirectional Feature Pyramid Network are added to the YOLOv8 algorithm to adapt to defect recognition. The improved yolov8 algorithm achieved a recognition rate of 83.1%, which is 10.7% higher than the yolov8 algorithm. Therefore, this method fills the gap in intelligent image recognition of Digital Radiography in pipeline girth welds.

关键词： Girth Weld Defect Digital Radiography Intelligent recognition Global Attention Mechanism YOLOv8

来源：评论

学校读者我要写书评

暂无评论

Classification of Potato Leaf Disease using Deep Learning 3

Classification of Potato Leaf Disease using Deep Learning

引用

3rd international conference for Advancement in Technology, ICONAT 2024

作者： Singh, Neelam Sharma, Deeksha Dev, Saurav Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Department of Computer Application Dehradun India

ISBN: (纸本)9798350354171

Deep learning is one of the subdomains of Artificial intelligence. With the advantages of automatic learning and feature extraction, in recent years, it has become a hot topic in academic and industrial circles. Meanwhile, this has emerged as one of the hotspots within agricultural plant protection research, including plant disease recognition and pest range assessment. Deep learning in plant disease recognition can avoid the shortcomings of artificial selection of features of the disease spot, making the feature extraction of plant diseases more objective, promoting research efficiency, and increasing technological transformation speed. The goal of this work is to analyze potato leaf diseases using CNN in order to determine the model's optimal performance using a large dataset (10,000 photos) of potato leaves in the analysis. The most effective model will support farmers in making decisions that will keep potato production from declining. This investigation revealed that the model worked better when forty epochs were applied to the dataset of 10,000 photos. Additionally, three different epochs were applied and achieved 100% accuracy for 30 and 50 as achieved 99.97% and 99.98% respectively. By offering recommendations for how to categorise Potato Leaf Disease with the best result, the study made a substantial contribution to the agricultural industry and farmers. While working with big volumes of data, researchers should be concerned about the system because running code takes longer time. To focus this, a dataset including 2152 photos was gathered from Kaggle, with an additional 7848 images sourced from various platforms such as Google and raw data from Potato Field. To determine which epochs performed the best, a range of epochs were applied and results shows that 40 epochs led to 100% accuracy. © 2024 IEEE.

关键词： artificial intelligence deep learning potato disease

来源：评论

学校读者我要写书评

暂无评论

Multi-strategy Central pattern Generator and Reinforcement Learning Integration for Quadruped Locomotion 3rd

Multi-strategy Central Pattern Generator and Reinforcement L...

引用

3rd international conference on machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Zuo, Guoyu Wang, Yong Yu, Shuangyue Beijing University of Technology Beijing100124 China

ISBN: (纸本)9789819624676

Legged animals have the flexibility to change their gait locomotion pattern strategies under different environments and walking speeds, which is important for efficient locomotion. However, legged locomotion is currently studied as a fixed set of pre-programmed gait patterns, which limits locomotor flexibility. Moreover, the process of designing multiple coping strategies for multiple tasks is cumbersome. In this study, we introduce a novel framework for quadrupedal locomotion learning, enabling robots to swiftly and adaptably transition between gait patterns tailored to various environments. In addition, we introduce an environmental feedback framework to improve the quadrupedal robot's ability to perceive external environmental features. We obtain a strategy network through a two-stage training and deploy it to real robots. Finally, a multi-strategy controller is obtained, which enables the quadruped robot to realize flexible strategy shifts and, moreover, efficient traversal of various complex terrain environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Depression recognition Based on Deep Learning Using RR Intervals 24

Depression Recognition Based on Deep Learning Using RR Inter...

引用

3rd Asia conference on Algorithms, Computing and machine Learning, CACML 2024

作者： Zhang, Wenshuo Liu, Wenlong Lin, Yongzhong Teng, Fei Wang, Hongyu Dalian University of Technology DUT Artificial Intelligence Institute Dalian China Dalian Key Laboratory of Artificial Intelligence DUT Artificial Intelligence Institute Dalian China The Second Affiliated Hospital of Dalian Medical University China Central Hospital of Dalian University of Technology China

ISBN: (纸本)9798400716416

The diagnosis of depression relies on the subjective judgment and experience of doctors, which lacks sufficient objectivity and efficiency. To address the above problems, we propose temporal convolutional network (TCN) based on the Inception architecture. This network takes RR interval sequences as input and classifies these sequences in depression patients (DP) and healthy controls (HC). The TCN modules employ different dilation rates to extract features at various scales from RR interval sequences. And the Inception model architecture effectively facilitates multi-scale feature fusion. The experimental results indicate that the Inception-TCN model demonstrates strong classification performance with an Area Under Curve (AUC) of 0.9527, accuracy of 89.95%, recall of 90.49%, precision of 91.68%, and an F1-score of 0.9108. Compared to the other four deep learning models, the performance of proposed model is significantly superior. © 2024 ACM.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Stability Analysis of 3C Electronic Industry Robot Grasping Based on Visual-Tactile Sensing 3

Stability Analysis of 3C Electronic Industry Robot Grasping ...

引用

3rd international conference on Robotics, Automation and Artificial intelligence (RAAI)

作者： Yan, Teng Sun, Yuxiang Zhang, Yang Yu, Zhenxi Li, Wenxian Zhang, Kailiang Shenzhen Univ Shenzhen Peoples R China Shenzhen Technol Univ Shenzhen Peoples R China

ISBN: (纸本)9798350307573;9798350307566

This study addresses the stability of robotic grasping and assembly in the 3C electronics industry, an area often plagued by issues such as slippage and twisting of target objects during grasping, which negatively impacts production efficiency and product quality. Previously, solutions primarily relied on conventional visual detection techniques, which suffered from low recognition rates in complex environments, strong dependence on light and background, and suboptimal performance with transparent or reflective objects. Although advances in sensor technology allowed traditional tactile detection methods to effectively gauge grasp strength and prevent objects from being damaged, these approaches were constrained by the objects' material, shape, and friction, affecting accuracy. Unfortunately, both of these require considerable datasets to train. We propose a new grasping solution with small datasets. It integrates Visual-Tactile sensing to counter these limitations via a Dual-Stream neural network-based model to synthesize data. The merged data are then fed into a Vision Transformer (ViT) network to determine the grasping stability, with an achieved accuracy of 98.86%. This approach enhances grasping stability and exhibits superior adaptability in complex environments.

关键词： robotic grasping stability visual-tactile sensing small datasets multi-source data fusion vision transformer

来源：评论

学校读者我要写书评

暂无评论

Predicting House Price Model : A Comprehensive Analysis with Random Forest and Decision Tree Method 3

Predicting House Price Model : A Comprehensive Analysis with...

引用

3rd international conference for Innovation in Technology, INOCON 2024

作者： Sharma, Mansi Sharma, Deepak Burle, Rushikesh Patil, Pawan Joge, Isha Puri, Chetan Datta Meghe Institute of Higher Education and Research Department of Computer Science and Design Wardha India Department of Commerce & Management Sciences Maharashtra Wardha India Datta Meghe Institute of Higher Education and Research Department of Artificial Intelligence and Machine Learning Wardha India Datta Meghe Institute of Higher Education and Research Department of Artificial Intelligence and Data Science Wardha India

ISBN: (纸本)9798350381931

This paper explores the field of predicting property prices through a thorough comparison of several regression techniques. Linear regression, decision tree regression, random forest regression, K-neighbors regression, gradient boosting regression, and XGBoost regression are the regression models that are being examined. Finding the best model to reliably estimate house prices based on a set of features is the *** dataset used in this study includes location, bedroom count, square footage, and other relevant parameters that are known to affect property values. Each regression model is trained and tested on this dataset using a methodical evaluation procedure, and its performance is evaluated using important metrics including R-squared, Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and overall correctness. predicting house prices mainly use harlfoxem (Owner) repository of housing dataset will contain the homes sold between May 2014 and May 2015 with 21613 entries and 21 attribute were used to evaluate the performance of machine learning prediction model. For practitioners and scholars working in real estate, housing market analysis, and related sectors, this study offers insightful information. It emphasizes how crucial it is to properly choose regression techniques depending on the particulars of the prediction task and the distinct qualities of the dataset. © 2024 IEEE.

关键词： Decision trees

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 << < 45 46 47 48 49 50 51 52 53 54 > >>

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：