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

4,746 篇 会议
55 册 图书
12 篇 期刊文献

馆藏范围

4,813 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,155 篇 工学
- 2,813 篇 计算机科学与技术...
- 2,227 篇 软件工程
- 1,264 篇 信息与通信工程
- 759 篇 控制科学与工程
- 691 篇 生物工程
- 668 篇 光学工程
- 530 篇 电气工程
- 454 篇 生物医学工程（可授...
- 419 篇 电子科学与技术（可...
- 299 篇 网络空间安全
- 182 篇 安全科学与工程
- 163 篇 机械工程
- 160 篇 仪器科学与技术
- 159 篇 交通运输工程
- 152 篇 动力工程及工程热...
- 152 篇 化学工程与技术
- 142 篇 石油与天然气工程
1,643 篇 理学
- 709 篇 生物学
- 637 篇 物理学
- 604 篇 数学
- 242 篇 化学
- 180 篇 统计学（可授理学、...
827 篇 管理学
- 463 篇 图书情报与档案管...
- 443 篇 管理科学与工程(可...
- 119 篇 工商管理
434 篇 医学
- 364 篇 临床医学
- 247 篇 基础医学(可授医学...
- 214 篇 药学(可授医学、理...
- 106 篇 公共卫生与预防医...
125 篇 法学
- 109 篇 社会学
95 篇 农学
45 篇 经济学
44 篇 文学
33 篇 教育学
12 篇 军事学

主题

320 篇 image processing
312 篇 deep learning
231 篇 image segmentati...
191 篇 signal processin...
172 篇 image classifica...
167 篇 image enhancemen...
162 篇 computer vision
140 篇 image recognitio...
138 篇 convolutional ne...
136 篇 feature extracti...
125 篇 training
115 篇 machine learning
96 篇 computer applica...
83 篇 neural networks
83 篇 computational mo...
79 篇 visualization
78 篇 object detection
71 篇 natural language...
69 篇 semantics
68 篇 artificial intel...

机构

24 篇 chitkara univers...
17 篇 maharishi school...
15 篇 lovely professio...
15 篇 tianjin universi...
13 篇 university of ch...
12 篇 the islamic univ...
12 篇 beijing institut...
11 篇 school of comput...
11 篇 centre of interd...
10 篇 peng cheng labor...
10 篇 graphic era hill...
9 篇 national univers...
9 篇 sun yat-sen univ...
9 篇 school of comput...
9 篇 vivekananda glob...
9 篇 college of compu...
8 篇 harbin engineeri...
8 篇 school of comput...
8 篇 maharishi school...
8 篇 gla university d...

作者

13 篇 chauhan rahul
11 篇 yang yang
10 篇 anand vatsala
8 篇 kukreja vinay
8 篇 gupta rupesh
7 篇 luo xiaonan
7 篇 zhao yang
6 篇 bin wang
6 篇 pei jihong
6 篇 kumar ankit
6 篇 choudhury tanupr...
6 篇 zhu ce
6 篇 ce zhu
6 篇 kumar gaurav
6 篇 bing li
6 篇 li wei
5 篇 gill kanwarparta...
5 篇 zhiguo cao
5 篇 nagaraj p.
5 篇 singh kamred udh...

语言

4,761 篇 英文
51 篇 其他
17 篇 中文
1 篇 土耳其文

检索条件"任意字段=2023 IEEE International Conference on Image Processing and Computer Applications, ICIPCA 2023"

共 4813 条记录，以下是4701-4710 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：

Federated Learning based on Feature Transfer: Multi-center Nuclear Segmentation of Histological images

Federated Learning based on Feature Transfer: Multi-center N...

引用

Frontiers Technology of Information and computer (ICFTIC), ieee international conference on

作者： Senliang Lu Bao Feng Yehang Chen Zijun Huang School of Electronic Engineering and Automation Guilin University of Electronic Technology Guilin China Laboratory of Intelligent Detection and Information Processing Guilin University of Aerospace Technology Guilin City Guangxi Province China

Federated learning has enabled multiple medical data centers to collaboratively train segmentation models without sharing data. However, the existence of Non-IID data across different data centers leads to poor model generalization. To address this issue, we propose a personalized federated learning approach based on feature transfer, suitable for multi-center medical image segmentation tasks. Firstly, to construct personalized local segmentation models and reduce the influence of heterogeneous feature information in the global segmentation model, we employ a meta-network to automatically identify and select transferable features from the encoding layers of U-Net. It generates feature transfer weights and constructs a feature transfer loss to enhance the local models’ attention to informative features. Secondly, to filter out heterogeneous feature information from each local model and enable the global model to identify and transfer robust features from local models, the meta-network computes feature transfer weights based on the representations of each local model and construct an aggregation loss. This loss is then used to update the feature transfer weights based on the variation of soft dice loss of the global segmentation model. Experimental evaluations are conducted on six central datasets for cell nuclei segmentation tasks, and comparisons are made with three existing federated learning algorithms. The experimental results demonstrate that the proposed method achieves the highest dice coefficient in centers A, B, C, E, and F, with a nearly 10% improvement in the dice coefficient for center F.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Car Defect Detection Using image processing

Car Defect Detection Using Image Processing

引用

Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF), international conference on

作者： S. Durai T. Sujithra Athmakuri Sai Charan Sai Kiran Pulyala Battula Vishnuwardhan Satyam Dept. of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Computer Science and Engineering Manipal Institute of Technology Manipal

Defect Detection became one of the hardest problems in this world nowadays. As of now humans detected the defects with the help of their naked eye. This process is time consuming and this can be done by only experts and these decisions may be differ from expert to expert. To avoid this problem we are training the collected data set. This will consume very less time and provides the best solution. The detection of defects is essential in quality control in manufacturing to get high quality products in less time. Humans can identify large defects but in case of micro defects humans can't found those so, this implementation will helpful in finding large as well as micro and milli defects as well. In this project we are trying to detect the defects such as dents and ripples present on the surface of the car which are macro in size at the time of manufacturing the cars and in the case of accidents happened. We'll use a high-quality camera to simultaneously capture photographs of the vehicle's five sides. We will use Convolution Neural Network [CNN] for training (which highlights the location of the defects). Once trained, that model we can use it for different end user applications.

关键词： Training Deep learning Convolution Neural networks User interfaces Prediction algorithms Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Implementation of Braun and Baugh-Wooley Multipliers Using QCA

Implementation of Braun and Baugh-Wooley Multipliers Using Q...

引用

Innovation in Technology (INOCON), ieee international conference for

作者： P. Kishore Rohan Sirimalla K. Sai Sushma R. Saikiran Reddy Dept. of ECE VNRVJIET Hyderabad India ECE VNRVJIET Hyderabad India

Matrix multiplication is a key element in digital signal processing systems, as well as a repetitive procedure in several signal processing and computing tasks. The circuit complexity is mostly determined by the number of multiplications necessary to create the system. A parallel array multiplier is a method for meeting high execution speed requirements. In the last step of a standard Braun multiplier, there is an assembly containing 16 AND gates, 9 Full Adders, as well as a ripple carry adder (RCA). Researchers studied other 4nano devices as an alternative to CMOS since circuits are constrained by technological scalability. Quantum-dot Cellular Automata (QCA) system is really a viable alternative to CMOS technology in a variety of nano devices. It is appealing because of its quick speed, small size, with low power consumption. The creation of a small and high-speed Baugh Wooley multiplier utilizing Quantum Dot Cellular Automata is presented in this study. In DSP processors, multipliers are the fundamental building elements of many calculations. Various adder as well as multiplier models on QCA have already been presented, however there has been little effort done on signed multiplication. This paper utilizes the unique QCA characteristics to design a Baugh-Wooley Multiplier that is fast and efficient to implement both signed and unsigned multiplication and comparison will be done with present implemented multipliers. Multiplication is the basic building block for several DSP processors, image processing and many other. QCA Designer is used to display simulation results. The computational complexity of algorithms employed inside Digital Signal Processors (DSPs) has significantly grown over time. Braun design is a simulation model of a similar array multiplier. A parallel array multiplier is a form of Braun multiplier. Braun multiplier architecture comprises mainly multiple Carry Save Adders, an array of AND gates, and a Ripple Carry Adder.

关键词： Program processors Power demand Array signal processing Quantum dots Digital signal processors computer architecture Logic gates

来源：评论

学校读者我要写书评

暂无评论

Morlet wavelet-based feature extraction algorithm with Fuzzy logic for an Iris Recognition System for Non-ideal images

Morlet wavelet-based feature extraction algorithm with Fuzzy...

引用

international conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Georgie Ann Regencia Christian Benedict Gaba Noel Linsangan School of Electrical Mapua University Electronics and Computer Engineering Manila Philippines

ISBN: (数字)9798350381177

ISBN: (纸本)9798350381184

This study investigates the integration of Fuzzy Logic into an Iris Recognition System, with a specific focus on its impact on system performance and its enhancement of the Morlet Wavelet Transform-based feature extraction process. This study explores the integration of Fuzzy Logic into an Iris Recognition System, focusing on enhancing the Morlet Wavelet Transform-based feature extraction process. By addressing non-ideal iris images, including different-sized irises, specular reflections, occlusions, blurred images, and off-angle shots, Fuzzy Logic significantly improves system performance. Despite achieving an overall accuracy of 85.43%, this study acknowledges the potential for further enhancement by optimizing image capture conditions. In comparison to previous research by Panganiban, Linsangan, and Caluyo, which achieved impressive percentages of up to 93% and 94.5% in iris recognition accuracy, albeit in ideal image conditions, there is room for improvement. This study underscores the importance of maintaining consistent lighting and proper iris positioning to minimize errors. With future advancements in algorithms and image capture techniques, even greater accuracy can be achieved. Recommendations include upholding consistent image capture conditions and further exploring the potential of Fuzzy Logic for broader iris recognition applications. The normalization step standardizes the extracted iris region, opening doors for advanced and dependable iris recognition systems in the future.

关键词： Fuzzy logic Wavelet transforms Accuracy System performance Lighting image capture Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Metal-Ceramic and Epoxy Composite Materials Nanostructure Coatings

Metal-Ceramic and Epoxy Composite Materials Nanostructure Co...

引用

international conference on Nanomaterials: Application & Properties (NAP)

作者： Volodymyr Korzhyk Petpo Stukhliak Olena Berdnikova Junjun ZHao Kseniia Lepilina Ihor Skachkov Dept. of Electrothermal Processes of Material Processing E. O. Paton Electric Welding Institute of the NAS of Ukraine Kyiv Ukraine Computer-Integrated Technologies Department Ternopil National Technical University named after Ivan Pulyu Ternopil Ukraine Dept. of Physical and Chemical Research of Materials E. O. Paton Electric Welding Institute of the NAS of Ukraine Kyiv Ukraine Scientific Research Institute of Welding Technologies named after E. O. Paton in Zhejiang Province Hangzhou People's Republic of China National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kyiv Ukraine

One of the ways to increase the reliability of various products is the use of protective coatings. As for now scientific and technical developments offer various methods and ways of applying and forming multipurpose functional coatings. They include various composition materials gas flame spraying. Nowadays the method of cumulative-detonation multi-chamber high-speed spraying of metal powders, their oxides, nitrides, carbides, etc., has been actively developed and implemented. The advantages of this method include the high strength of adhesive joints to the base, the nanostructures formation, and the possibility of the formation of phases with different types in coating material. Metal details protective properties are improved. The combination of metal-ceramic and polymer coatings will expand a functional range of their potential use. Gradient multilayer coatings based on aluminum oxide and epoxy composite are proposed. The first adhesive layer is sprayed with a thickness of 100–150 microns from aluminum oxide (Al 2 O 3 ) with a dispersion of 5–15 microns. Aluminum oxide is more preferable when applied to an aluminum base. Such a layer has high electrical breakdown strength, thermal conductivity and adhesive strength due to the crystalline compatibility between the aluminum base and the material of the sprayed layer. In addition, nanostructured formations appear in the coating material during spraying. It gives a wide range of required coatings operational characteristics. This will provide the coating with a set of operational characteristics.

关键词：

来源：评论

学校读者我要写书评

暂无评论

2nd international conference on Computing, Communication, and Learning, CoCoLe 2023

2nd International Conference on Computing, Communication, an...

引用

2nd international conference on Computing, Communication, and Learning, CoCoLe 2023

ISBN: (纸本)9783031569975

The proceedings contain 25 papers. The special focus in this conference is on Computing, Communication, and Learning. The topics include: Yolo and RetinaNet Ensemble Transfer Learning Detector: Application in Pavement Distress;stock Market Prediction Performance Analysis by Using Machine Learning Regressor Techniques;nearest Neighbor and Decision Tree Based Cloud Service QoS Classification;object Recognition Through Content Based Feature Extraction and Classification of Sounds in IoT Environment;detection of Malicious Activity on Credit Cards Using Machine Learning;agent-Based Modeling for Optimum Location Selection: Enhancing Day-Ahead Market Analysis for Microgrid Integration;a Comparative Approach for Skin Cancer Detection Using Artificial Bee Colony;a Hybrid Approach to Enhance Software Quality by Sentiment Analysis of Developer;unsupervised Sentiment Analysis of Amazon Fine Food Reviews Using Fuzzy Logic;sentiment Analysis of Crypto Currency Trading applications in India Using Machine Learning;Graph Similarity Join (GSJ) Approach to Detect Near Duplicate Text Documents;three Factor Authentication Scheme for Telecare Medical Information System;an Effective Threshold Based Technique for Retinal image Blood Vessel Segmentation on Fundus image Using Average and Gaussian Filters;substantiation System Using Facial Recognition and Principal Component Analysis;impact of Stress on Faculties’ Attitudes: A Study of Higher Education Institutes;dynamic Cross-Layer Communication Design for Multi-objective Optimization in Wireless Sensor Networks;Implementation of Weighted Parallel Interference Cancellation Technique for Multi User Detection in UWA Communication;analysis and Comparison of Firefly Algorithm for Measuring Convergence Rate in Distributed Environment;A Comparative Study on Social Behavior of Tribes and Non Tribes in ITDA Paderu by Using Network Science;raster Big Data processing Using Spark with GeoTrellis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Layout Analysis of Malayalam Palm Leaf images with Fully Convolutional Networks

Layout Analysis of Malayalam Palm Leaf Images with Fully Con...

引用

international conference on Advances in Electronics, computers and Communications (ICAECC)

作者： Kamal Boyina Dutta Swetchana Gujja Manaswi Reddy Karru Sushrutha Peeta Basa Pati Jyotsna C Remya Sivan Department of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798350305449

ISBN: (纸本)9798350305456

Palm leaf manuscripts have been used for centuries as a medium for preserving ancient knowledge and cultural heritage. To prevent their loss, digitization of these manuscripts has become crucial. Layout analysis specifically involves the localization and classification of various objects found in the document, such as text, tables, images, graphics, document boundaries, and background elements. However, layout analysis of palm leaf images presents significant challenges due to their irregular shapes and sizes, complex layouts, and varying degrees of deterioration. This research paper proposes the utilization of Fully Convolutional Networks (FCN) for the layout analysis of Malayalam palm leaf images. Multiple variations of FCN, including FCN-8, FCN-16, FCN-16, and FCN-8 with skipped connections, are explored to accurately extract and classify layout components such as background, text, and punch holes. The research uses a manually crafted masked dataset and combines manual research, deep learning, and image processing techniques. The results demonstrate the potential of FCN-based models for analyzing palm leaf manuscript layouts and contribute to their preservation and understanding. Significantly, FCN-8 yielded the best score, achieving a Mean Average Precision (MAP) of 0.79 at Intersection over Union (IOU). The paper provides an in-depth analysis of the methodology, dataset, and results, offering new avenues for research and preservation in this domain.

关键词： Location awareness Deep learning computers Analytical models Shape image processing Layout

来源：评论

学校读者我要写书评

暂无评论

Security & Privacy Issues in IoT Using Blockchain and ML

Security & Privacy Issues in IoT Using Blockchain and ML

引用

international conference on image Information processing

作者： Muna Muhammad Ahthasham Sajid Gunjan Chhabra Hamed Taherdoost Inam Ullah Khan Keshav Kaushik Engineering and Management Sciences Balochistan University of Information Technology Balochistan Pakistan Faculty of Computing Capital University of Science and Technology Islamabad Pakistan Department of CSE Graphic Era Hill University Dehradun Uttarakhand India Q Minded | Quark Minded Tehnology Inc. University Canada West Vancouver Canada Department of Electronic Engineering School of Engineering and Applied Sciences (SEAS) Isra University Islamabad Campus Pakistan School of Computer Science University of Petroleum and Energy Studies Dehradun India

ISBN: (数字)9798350371406

ISBN: (纸本)9798350371413

As Internet of Things (IoT) devices are being involved in abundant applications, security, and privacy of the IoT users have been of more concern. The security threats are rapidly growing making the solutions of security and privacy not inadequate. Thereby, each thing on the internet can be a point of target for hackers. Accordingly, ML algorithms are utilized for producing accurate outputs by using large and complex databases in which the produced outputs could be used in the prediction and detection of weaknesses in IoT systems. Additionally, BC methods are also being used for providing security and privacy solutions in IoT networks. Many existing studies have been carried out on BC techniques or ML algorithms or both. Though, these existing studies focus on either providing privacy or security issues by using BC techniques or ML algorithms, therefore, give rise to need for aa combined survey on solutions made recently which address both privacy and security issues by using BC techniques and ML algorithms. In this paper, we give a summarized survey of research works that happened in the last four years by addressing privacy and security issues by using BC techniques and ML algorithms in IoT networks. Different literatures have been categorized on privacy and security of BC techniques and ML algorithms in IoT. Then at last, some research challenges and future works are highlighted by using BC techniques and ML algorithms for addressing security and privacy issues in IoT networks.

关键词： Surveys Threat modeling Privacy Databases computer hacking Information processing Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

A Key-Points Based Anchor-Free Cervical Cell Detector

A Key-Points Based Anchor-Free Cervical Cell Detector

引用

Annual international conference of the ieee Engineering in Medicine and Biology Society (EMBC)

作者： Tong Shu Jun Shi Yushan Zheng Zhiguo Jiang Lanlan Yu School of Computer Science and Information Engineering Hefei University of Technology Hefei China School of Software Hefei University of Technology Hefei China School of Engineering Medicine Beihang University Beijing China Beijing Advanced Innovation Center for Biomedical Engineering Beihang University Beijing China Image Processing Center School of Astronautics Beihang University Beijing China Motic (Xiamen) Medical Diagnostic Systems Co. Ltd. Xiamen China

Cervical cell detection is crucial to cervical cytology screening at early stage. Currently most cervical cell detection methods use anchor-based pipeline to achieve the localization and classification of cells, e.g. faster R-CNN and YOLOv3. However, the anchors generally need to be pre-defined before training and the detection performance is inevitably sensitive to these pre-defined hyperparameters (e.g. number of anchors, anchor size and aspect ratios). More importantly, these preset anchors fail to conform to the cells with different morphology at inference phase. In this paper, we present a key-points based anchor-free cervical cell detector based on YOLOv3. Compared with the conventional YOLOv3, the proposed method applies a key-points based anchor-free strategy to represent the cells in the initial prediction phase instead of the preset anchors. Therefore, it can generate more desirable cell localization effect through refinement. Furthermore, PAFPN is applied to enhance the feature hierarchy. GIoU loss is also introduced to optimize the small cell localization in addition to focal loss and smooth L1 loss. Experimental results on cervical cytology ROI datasets demonstrate the effectiveness of our method for cervical cell detection and the robustness to different liquid-based preparation styles (i.e. drop-slide, membrane-based and sedimentation).

关键词：

来源：评论

学校读者我要写书评

暂无评论

UAV-based Digital Field Phenotyping for Crop Nitrogen Estimation using RGB imagery

UAV-based Digital Field Phenotyping for Crop Nitrogen Estima...

引用

Emerging Technologies (GlobConET), ieee IAS Global conference on

作者： Suchitra M Patil Sunita Choudhary Jana Kholová Krithika Anbazhagan Yogesh Parnandi Priyanka Gattu Srikanth Mallayee Prasad KSVV V Padma Kumar P Rajalakshmi Magesh Chandramouli J Adinarayana Centre of Studies in Resources Engineering Indian Institute of Technology Bombay Powai Mumbai Maharashtra India Crop Physiology and Modeling International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) Patancheru Telangana India Department of Information Technologies Czech University of Life Sciences Prague Prague Czech Republic Indian Institute of Technology Hyderabad Kandi Telangana India International Livestock Research Institute Patancheru Telangana India Computer Graphics Technology Purdue University NW Hammond IN USA

Nitrogen (N) is one of the essential nutrients required for healthy crop growth. Field phenotyping for nitrogen stress symptoms is laborious and time-consuming, that way, it is a major bottleneck in nutrition-inclusive agricultural research. Recent advancements in sensors and image processing facilitate color-based quantification of crop greenness from high-resolution RGB images. In this paper, we present unmanned aerial vehicle (UAV)-based digital field phenotyping for the estimation of crop nitrogen content. For this, we conducted a field experiment during the post-rainy season of 2021 at international Crops Research Institute for Semi-Arid Tropics (ICRISAT), Hyderabad, India with long-stature cereal model crop, sorghum (Sorghum bicolor L.) cultivated under three different regimes varying in moisture and soil nitrogen content. A high-resolution RGB sensor (XenmuseX5S) mounted on DJI Matric 210 quadcopter was used for capturing the spatiotemporal imagery. Five different RGB spectrum vegetation indices indicating crop greenness were correlated with ground truth values of crop N content using simple linear regression and stepwise backward regression. With a prediction potential of R 2 =0.65 and MAE=0.27 for an independent dataset, we present a stepwise backward linear regression model as a promising approach for real-time estimation of the N status of sorghum crop.

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482页 << < 467 468 469 470 471 472 473 474 475 476 > >>

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：