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

15,847 篇 会议
204 篇 期刊文献
147 册 图书
1 篇 专利

馆藏范围

16,199 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

9,992 篇 工学
- 8,671 篇 计算机科学与技术...
- 6,594 篇 软件工程
- 3,105 篇 信息与通信工程
- 2,988 篇 光学工程
- 2,499 篇 生物工程
- 1,545 篇 控制科学与工程
- 1,484 篇 生物医学工程（可授...
- 1,163 篇 电气工程
- 851 篇 电子科学与技术（可...
- 618 篇 化学工程与技术
- 561 篇 安全科学与工程
- 538 篇 机械工程
- 469 篇 网络空间安全
- 398 篇 交通运输工程
- 342 篇 仪器科学与技术
- 278 篇 材料科学与工程（可...
5,905 篇 理学
- 2,951 篇 物理学
- 2,562 篇 生物学
- 1,892 篇 数学
- 675 篇 化学
- 663 篇 统计学（可授理学、...
2,179 篇 管理学
- 1,288 篇 图书情报与档案管...
- 1,022 篇 管理科学与工程(可...
- 408 篇 工商管理
1,626 篇 医学
- 1,457 篇 临床医学
- 891 篇 基础医学(可授医学...
- 759 篇 药学(可授医学、理...
- 260 篇 公共卫生与预防医...
344 篇 农学
- 337 篇 作物学
302 篇 法学
- 280 篇 社会学
165 篇 经济学
135 篇 教育学
65 篇 文学
38 篇 军事学
2 篇 哲学
2 篇 历史学
2 篇 艺术学

主题

1,288 篇 computer vision
781 篇 deep learning
486 篇 image segmentati...
413 篇 image processing
386 篇 object detection
360 篇 image enhancemen...
338 篇 feature extracti...
303 篇 convolutional ne...
299 篇 image classifica...
275 篇 machine learning
203 篇 training
200 篇 computational mo...
198 篇 signal processin...
196 篇 image recognitio...
168 篇 visualization
163 篇 neural networks
158 篇 artificial intel...
153 篇 convolution
150 篇 face recognition
132 篇 generative adver...

机构

54 篇 chitkara univers...
41 篇 peng cheng labor...
39 篇 university of ch...
38 篇 school of comput...
31 篇 university of sc...
31 篇 tsinghua univers...
30 篇 the islamic univ...
26 篇 college of compu...
26 篇 college of compu...
25 篇 school of comput...
24 篇 shanghai jiao to...
23 篇 school of electr...
21 篇 college of compu...
21 篇 shenzhen interna...
21 篇 school of comput...
20 篇 school of comput...
19 篇 centre of interd...
19 篇 department of co...
19 篇 national univers...
19 篇 shanghai ai labo...

作者

18 篇 li li
18 篇 chen chen
18 篇 yang yang
16 篇 lee sung-hak
16 篇 liu yang
14 篇 jia zhenhong
14 篇 li yang
14 篇 kim young-choon
13 篇 hao zhang
13 篇 luc van gool
12 篇 luo xiaonan
12 篇 zhou gang
12 篇 zhang bo
11 篇 yulun zhang
11 篇 wang wei
10 篇 li xin
10 篇 zhang lei
10 篇 wang jing
10 篇 chen dong
10 篇 liu lei

语言

15,959 篇 英文
224 篇 其他
99 篇 中文
3 篇 土耳其文
2 篇 西班牙文

检索条件"任意字段=2023 International Conference on Image Processing and Computer Vision, IPCV 2023"

共 16199 条记录，以下是4881-4890 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：

EmNeF: Neural Fields for Embedded Variational Problems in Imaging 9th

EmNeF: Neural Fields for Embedded Variational Problems in ...

引用

9th international conference on Scale Space and Variational Methods in computer vision, SSVM 2023

作者： Bednarski, Danielle Lellmann, Jan Institute of Mathematics and Image Computing University of Lübeck Lübeck Germany

ISBN: (纸本)9783031319747

We propose a model-driven neural fields approach for solving variational problems. The approach can be applied to a variety of problems with convex, 1-homogeneous regularizer and arbitrary, possibly non-convex, data term. Our strategy is to embed the non-convex energy into a higher-dimensional space, reaching a convex primal-dual formulation. Instead of using classical gradient-descent based optimization algorithms, we propose training multiple fields representing the primal and dual variables in order to solve the problem. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Gradient methods

来源：评论

学校读者我要写书评

暂无评论

Research on the lane line detection method based on YOLOv5 5

Research on the lane line detection method based on YOLOv5

引用

5th international conference on Artificial Intelligence and computer Science, AICS 2023

作者： Gu, Xiang Shu, Wenjie School of Computer and Information Engineering Nantong Institute of Technology Jiangsu Nantong China School of Information Science and Technology Nantong University Jiangsu Nantong226001 China

ISBN: (纸本)9781510668621

Lane-line detection is one of the key technologies in the field of intelligent driving. This paper changes the anchor box regression loss function of the YOLOv5s to the EIoU function to construct a kind of lane-line detection model. The experimental results show that the improved detection model is more accurate in lane-line detection. The improved model improved mAP by about 11.1% compared to the conventional YOLOv5 model. At the same time, it can solve the problems of traditional models such as low real-time performance and underfitting to curved lane lines. © 2023 SPIE. All rights reserved.

关键词： Education and training Object detection Data modeling Detection and tracking algorithms image processing Deep learning Performance modeling Roads Video Video acceleration

来源：评论

学校读者我要写书评

暂无评论

Improving Diabetic Retinopathy Detection Using Patchwise CNN with biGRU Model 8

Improving Diabetic Retinopathy Detection Using Patchwise CNN...

引用

8th international conference on computer Science and Engineering, UBMK 2023

作者： Darici, Muazzez Buket Yigit, Gulsum Kadir Has University Department of Electrical-Electronics Engineering Istanbul Turkey Kadir Has University Department of Computer Engineering Istanbul Turkey

ISBN: (纸本)9798350340815

This study addresses Diabetic Retinopathy (DR), a diabetes complication that can lead to vision loss if not promptly diagnosed and treated. Recent advances in deep learning have shown promising results in detecting DR from retinal images. The study introduces a novel patch-based CNN-biGRU model for DR detection. The proposed model extracts patches from retinal images employing a sliding window strategy and then uses a Convolutional Neural Network (CNN) architecture to extract features from each patch. The features extracted from each patch are then concatenated, and a 4-layer bidirectional Gated Recurrent Unit (biGRU) is applied to predict the whole image. We assessed the proposed model on a publicly available dataset named APTOS 2019 Blindness Detection and achieved an accuracy of 73.5%, outperforming existing state-of-the-art approaches. The given patch-based CNN model can improve the accuracy of DR detection and aims to assist ophthalmologists in making more accurate diagnoses. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

SIGVIC: Spatial Importance Guided Variable-Rate image Compression 48

SIGVIC: Spatial Importance Guided Variable-Rate Image Compre...

引用

48th IEEE international conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Liang, Jiaming Liu, Meiqin Yao, Chao Lin, Chunyu Zhao, Yao Beijing Jiaotong University Institute of Information Science Beijing100044 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China

ISBN: (纸本)9781728163277

Variable-rate mechanism has improved the flexibility and efficiency of learning-based image compression that trains multiple models for different rate-distortion tradeoffs. One of the most common approaches for variable-rate is to channel- wisely or spatial-uniformly scale the internal features. However, the diversity of spatial importance is instructive for bit allocation of image compression. In this paper, we introduce a Spatial Importance Guided Variable-rate image Compression (SigVIC), in which a spatial gating unit (SGU) is designed for adaptively learning a spatial importance mask. Then, a spatial scaling network (SSN) takes the spatial importance mask to guide the feature scaling and bit allocation for variablerate. Moreover, to improve the quality of decoded image, Top-K shallow features are selected to refine the decoded features through a shallow feature fusion module (SFFM). Experiments show that our method outperforms other learning- based methods (whether variable-rate or not) and traditional codecs, with storage saving and high flexibility. © 2023 IEEE.

关键词： image compression scale factor shallow feature spatial importance variable-rate

来源：评论

学校读者我要写书评

暂无评论

Accuracy of image Registration During Similarity Transformation 3rd

Accuracy of Image Registration During Similarity Transformat...

引用

3rd international conference on Machine vision and Augmented Intelligence, MAI 2023

作者： Babayan, Pavel Kozhina, Ekaterina Gagarin Str. Ryazan State Radio Engineering University Named After V.F. Utkin 59/1 Ryazan390005 Russia

ISBN: (纸本)9789819743582

This paper considers the problem of assessing the accuracy of image registration using a multi-reference algorithm. This algorithm is based on a random selection of reference areas in the image, with the help of which geometric transformations are estimated. The similarity image transformation model is used in the work. The novelty of this article lies in the fact that, unlike other articles, methods for assessing the accuracy of image registration are proposed to improve the quality of image analysis. The correlation matrix of errors in the estimation of the parameters of geometric transformations and the correlation matrix of registration errors for the entire image have been determined. The nature of the dependence of the registration error variance on the zone of choice of reference areas is shown. Experimental studies were carried out on images obtained by semi-natural modeling based on video captured by a vehicle traffic control system. The research results can be applied when developing image processing algorithms, for example, image stabilization, registration, and moving object detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image correlation

来源：评论

学校读者我要写书评

暂无评论

international conference on Artificial Intelligence and Communication Technology, ICAICT 2023

International Conference on Artificial Intelligence and Comm...

引用

international conference on Artificial Intelligence and Communication Technology, ICAICT 2023

ISBN: (纸本)9789819966400

The proceedings contain 33 papers. The special focus in this conference is on Artificial Intelligence and Communication Technology. The topics include: Optimal Design of Hydrodynamic Journal Bearing Based on BP Neural Network Optimized by Improved Particle Swarm Algorithm;the Intelligent Human–computer Interaction Method for Application Software of Electrical Energy Metering Based on Deep Learning Algorithm;Short Text Classification of Invoices Based on BERT-TextCNN;design of Fully Automatic Calibration Scheme for Load Box Based on Visual Recognition;deepScan: Revolutionizing Garbage Detection and Classification with Deep Learning;Chapter 16 Research on Portable Methane Telemetry System Based on TDLAS;Recommendation Algorithm Based on Wide&Deep and FM;simulation of E-Commerce Big Data Classification Model Based on Artificial Intelligence Algorithm;research and Implementation of Data Feature Extraction Technology for Multisource Heterogeneous Data in Electric Distribution Network;extraction and Fusion of Geographic Information from Multi-source Remote Sensing images Based on Artificial Intelligence;chapter 20 Design and Optimization of Business Decision Support System Based on Deep Learning;performance Evaluation of Container Identification Detection Algorithm;application and Prospect of Deep Learning and Machine Learning Technology;chapter 23 Simulation of Intelligent image processing Model Based on Machine Learning Algorithm;Chapter 24 Design and Implementation of a Health Monitoring Management Platform Based on IoT and DL;chapter 25 Design of Hospital Equipment Information Management System Based on computer vision Technology;chapter 26 Design and Implementation of an Internet of Things-Based Real-Time Five-Layer Security Surveillance System;chapter 27 Logistics Security Integrated Communication System Under the Background of 5G Artificial Intelligence.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deception Detection in the Digital Age: Pioneering Linguistics and vision 2

Deception Detection in the Digital Age: Pioneering Linguisti...

引用

2nd international conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Thampi, Abhijith A. Megha, R. Varma, Vanapala Bharath Chandra Abhishek, S. Anjali, T. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798350340235

The cutting-edge methodology for deception detection presented in this research study employs Deep Learning (DL) and Natural Language processing (NLP) methodologies. Long a challenging and significant area of study, deception detection has applications in security, law enforcement, and interpersonal communication. In this study, a unique method for using neural networks in conjunction with Natural Language processing (NLP) and speech processing is discussed to distinguish between dishonest and truthful statements. Our approach explores the distinguishing elements in text data and the acoustic properties ingrained in spoken language. This has the intention to provide a deception detection technique with significant potential in real-world circumstances by combining these two modalities. This research opens up new possibilities for things like fraud detection, security screening, and perhaps even bettering human- AI interactions. Our novel technique represents a substantial advancement in the field of deception detection and providesuseful insights into the possibilities of AI-driven solutions in dealing with complicated human behaviors. © 2023 IEEE.

关键词： Acoustic Characteristics Artificial Intelligence Deception detection Natural Language processing Neural Networks S peech processing Text Analysis

来源：评论

学校读者我要写书评

暂无评论

Deep learning based on coconut tree leaf disease detection and classification for precision farming 9

Deep learning based on coconut tree leaf disease detection a...

引用

9th IEEE international conference on Smart Structures and Systems, ICSSS 2023

作者： Yogabalajee, V. Kaliappan, Vishnu Kumar Kpr Institute of Engineering and Technology Department of Computer Science Engineering Tamilnadu Coimbatore641407 India

ISBN: (纸本)9798350384208

The agricultural sector faces serious obstacles from plant diseases, which lower crop production and cause financial losses. Numerous leaf diseases can affect coconut, a beverage that is enjoyed widely worldwide. Traditionally, diagnosing this disease has required labor- and time-intensive manual visual interpretation. To identify the disease one of the popular know deep learning method based image classification methods are Resnet50, vision Transformers, Convnext and Convnextv2 Method. In this work we proposed MConvnextV2 performed well among the above algorithms compared by the Performance matrixes. In Proposed MConvnextV2 w use an Swin optimizer to perform to obtain the 99% of the accuracy according to the results. The overarching objective of this study is to encourage sustainable agriculture practices by leveraging advanced technology for the accurate classification of plant disease. © 2023 IEEE.

关键词： image classification

来源：评论

学校读者我要写书评

暂无评论

Research on intelligent aided design of architectural space based on deep learning 3

Research on intelligent aided design of architectural space ...

引用

3rd international conference on Advanced Algorithms and Signal image processing, AASIP 2023

作者： Chen, Xi Jiangxi Science and Technology Normal University Nanchang330013 China

ISBN: (纸本)9781510668522

Information technology has been developing rapidly in recent years, the application of computer aided design (CAD) in architectural design is more and more. Based on the computer-Aided design method, designers can parameterize the design scheme in the software, and use a series of variables to control and transform the design scheme, which brings great convenience for the architect to optimize the process of architectural scheme. But the building performance optimization method based on intelligent algorithm is mainly used in scientific research and is difficult to put into practical engineering. Therefore, for the purpose of solving the above problems, this paper carries on the mathematical modeling to the building performance prediction problem which takes the building spatial parameters as the optimization variables. Based on BP neural network, this paper builds an accurate and efficient building performance prediction platform to assist designers to make decisions. The simulation results show that the prediction and optimization proposed here can give accurate and reliable optimal solutions, and the optimal construction scheme has strong rationality and high engineering application value. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： computer aided design

来源：评论

学校读者我要写书评

暂无评论

MULTI-DOMAIN image GENERATION AND TRANSLATION WITH IDENTIFIABILITY GUARANTEES 11

MULTI-DOMAIN IMAGE GENERATION AND TRANSLATION WITH IDENTIFIA...

引用

11th international conference on Learning Representations, ICLR 2023

作者： Xie, Shaoan Kong, Lingjing Gong, Mingming Zhang, Kun Carnegie Mellon University United States Mohamed bin Zayed University of Artificial Intelligence United Arab Emirates The University of Melbourne Australia

Multi-domain image generation and unpaired image-to-to-image translation are two important and related computer vision problems. The common technique for the two tasks is the learning of a joint distribution from multiple marginal distributions. However, it is well known that there can be infinitely many joint distributions that can derive the same marginals. Hence, it is necessary to formulate suitable constraints to address this highly ill-posed problem. Inspired by the recent advances in nonlinear Independent Component Analysis (ICA) theory, we propose a new method to learn the joint distribution from the marginals by enforcing a specific type of minimal change across domains. We report one of the first results connecting multi-domain generative models to identifiability and shows why identifiability is essential and how to achieve it theoretically and practically. We apply our method to five multi-domain image generation and six image-to-image translation tasks. The superior performance of our model supports our theory and demonstrates the effectiveness of our method. The training code are available at https://***/Mid-Push/i-stylegan. © 2023 11th international conference on Learning Representations, ICLR 2023. All rights reserved.

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 << < 485 486 487 488 489 490 491 492 493 494 > >>

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：