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

4,606 篇 会议
577 篇 期刊文献
7 篇 学位论文
5 册 图书

馆藏范围

5,195 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,681 篇 工学
- 2,232 篇 计算机科学与技术...
- 1,450 篇 软件工程
- 584 篇 电气工程
- 374 篇 控制科学与工程
- 345 篇 信息与通信工程
- 259 篇 机械工程
- 250 篇 石油与天然气工程
- 216 篇 化学工程与技术
- 205 篇 生物医学工程（可授...
- 196 篇 生物工程
- 189 篇 仪器科学与技术
- 176 篇 土木工程
- 162 篇 光学工程
- 158 篇 建筑学
- 154 篇 动力工程及工程热...
- 133 篇 材料科学与工程（可...
- 127 篇 电子科学与技术（可...
- 122 篇 航空宇航科学与技...
1,593 篇 理学
- 602 篇 物理学
- 422 篇 数学
- 314 篇 地球物理学
- 270 篇 地质学
- 222 篇 生物学
- 204 篇 统计学（可授理学、...
- 192 篇 化学
- 120 篇 系统科学
666 篇 管理学
- 424 篇 管理科学与工程(可...
- 269 篇 图书情报与档案管...
- 175 篇 工商管理
405 篇 医学
- 307 篇 临床医学
92 篇 法学
86 篇 农学
68 篇 教育学
59 篇 经济学
32 篇 文学
12 篇 艺术学
4 篇 军事学
1 篇 历史学

主题

674 篇 visualization
387 篇 data visualizati...
240 篇 visual analytics
170 篇 data mining
150 篇 data analysis
137 篇 feature extracti...
102 篇 data models
96 篇 deep learning
94 篇 image color anal...
90 篇 task analysis
88 篇 accuracy
87 篇 training
79 篇 computational mo...
73 篇 analytical model...
72 篇 big data
69 篇 machine learning
62 篇 cameras
58 篇 predictive model...
58 篇 semantics
55 篇 information visu...

机构

17 篇 center for space...
17 篇 nagoya universit...
17 篇 department of el...
16 篇 infn sezione di ...
16 篇 department of ph...
16 篇 quantum ict adva...
16 篇 department of ph...
16 篇 department of ph...
15 篇 vrvis res ctr au...
15 篇 institute of spa...
15 篇 faculty of scien...
15 篇 infn sezione di ...
15 篇 institute of par...
15 篇 national institu...
15 篇 via madonna del ...
15 篇 department of as...
15 篇 faculty of engin...
14 篇 univ konstanz co...
14 篇 waseda research ...
14 篇 jem utilization ...

作者

22 篇 asano k.
18 篇 schreck tobias
18 篇 cherry m.l.
18 篇 krizmanic j.f.
17 篇 tamura t.
17 篇 bruno a.
17 篇 kawakubo y.
17 篇 katayose y.
17 篇 binns w.r.
17 篇 castellini g.
17 篇 israel m.h.
17 篇 uchihori y.
17 篇 ebisawa k.
17 篇 yoshida a.
17 篇 bongi m.
17 篇 bigongiari g.
17 篇 shiomi a.
17 篇 collazuol g.
17 篇 nakahira s.
17 篇 ozawa s.

语言

4,452 篇 英文
533 篇 其他
161 篇 俄文
57 篇 中文
3 篇 乌克兰文
2 篇 德文
1 篇 法文
1 篇 葡萄牙文

检索条件"任意字段=Conference on Visual Data Exploration and Analysis V"

共 5195 条记录，以下是1171-1180 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：

varCopy: a visual Exploratory data analysis Platform for Copy Number variation Studies 24

VarCopy: a Visual Exploratory Data Analysis Platform for Cop...

引用

24th International conference Information visualisation (Iv)

作者： Bove, Fabio Mandreoli, Federica Martoglia, Riccardo Pisi, valentino Taccioli, Cristian vischioni, Chiara Univ Modena & Reggio Emilia FIM Modena Italy Univ Padua MAPS Padua Italy

ISBN: (纸本)9781728191348

The study of such a complex phenomenon as cancer, which depends on several but unexplored and unclear factors, needs new ways to visualize, analyze and combine different data both on species characteristics and genes function. To this respect, we propose a novel platform, named varCopy, supporting visual Exploratory data analysis (EDA) in the context of Copy Number variation (CNv) data. The platform will be publicly available as a web application soon, and is, to our best knowledge, the first tool allowing visual, interactive exploration and analysis of the CNv landscape of multiple species, allowing the identification of new target genes that might be useful for biomedical research.

关键词： Copy Number variations interactive visualization Exploratory data analysis scalable data science data analysis models

来源：评论

学校读者我要写书评

暂无评论

What Happened While I Was Away? Leveraging visual Transition Techniques to Convey Robot States in Multi-robot Teleoperation 13th

What Happened While I Was Away? Leveraging Visual Transition...

引用

13th International conference on Social Robotics (ICSR) - Robotics in Our Everyday Lives

作者： Seo, Stela H. Young, James E. Kyoto Univ Grad Sch Informat Kyoto Japan Univ Manitoba Comp Sci Winnipeg MB Canada

ISBN: (纸本)9783030905255;9783030905248

In real-time multi-robot teleoperation, the operator faces a challenge of maintaining sufficient awareness of all robots in a team. We propose a novel approach to supporting operators, in instances where operators switch between controlling or observing multiple robots in a team. Just as how cinema or video games use visual and narrative techniques to support viewers when transitioning between scenes, we argue that multi-robot teleoperation interfaces should likewise leverage this transition time to provide pertinent information. That is, when switching to a new robot, the interface should take the opportunity to bring the operator up to speed, highlighting what happened while they were away, what current robot states are, and what specifics of the new robot being controlled are;thus, supporting situational awareness. In this paper, we outline this agenda and present our initial exploration and analysis of this informative visual transition.

关键词： Teleoperation Multi-robot teleoperation Control transition Interface design

来源：评论

学校读者我要写书评

暂无评论

Advanced Underwater Imagery Enhancement using CycleGAN for Marine Research and Photography

Advanced Underwater Imagery Enhancement using CycleGAN for M...

引用

Pervasive Computing and Social Networking (ICPCSN), International conference on

作者： Abhishek Sarsiha Stewart Kirubakaran S Anitha J Santhiya P Ebenezer v Shobana M Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Division of Data Sciences and Cyber Security Karunya Institute of Technology and Sciences Coimbatore India Department of Computer Science and Engineering SNS College of Technology Coimbatore India

ISBN: (数字)9798331535193

ISBN: (纸本)9798331535209

This paper proposes the Underwater Image Enhancement using CycleGAN generative adversarial network (GAN). It can be seen that underwater images encounter kinds of color distortion, low contrast, and haziness due to the interaction of light with water. CycleGAN helps our system to overcome the challenge of fine tuning raw underwater images to better quality images in terms of color and contrast. The goal of this method is to serve those in marine biology, underwater photography, and research by delivering superior visual data for enhanced identification and representation purposes. We mention below that we have compared the outcome with existing approaches, judged by standard image quality measures. Consequently, the results show the possible application of CycleGAN for achieving better image quality with minimized preprocessing time.

关键词： Photography Image quality Pervasive computing visualization Image color analysis Social networking (online) Generative adversarial networks Image enhancement Tuning Standards

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Photorealistic Immersive System using Augmented Situated visualization within virtual Reality

An Enhanced Photorealistic Immersive System using Augmented ...

引用

28th IEEE conference on virtual Reality and 3D User Interfaces (IEEE vR)

作者： Iglesias, Maria Insa Jenkins, Mark Morison, Gordon Glasgow Caledonian Univ Sch Engn & Built Environm Glasgow Lanark Scotland

ISBN: (纸本)9781665440578

This work presents a system which allows image data and extracted features from a real-world location to be captured and modelled in a virtual Reality (vR) environment combined with Augmented Situated visualizations (ASv) overlaid and registered in a virtual environment. Combining these technologies with techniques from data Science and Artificial Intelligence (AI)(such as image analysis and 3D reconstruction) allows the creation of a setting where remote locations can be modelled and interacted with from any-where in the world. This Enhanced Photorealistic Immersive (EPI) system is highly adaptable to a wide range of use cases and users as it can be utilized to model and interact with any environment which can be captured as image data (such as training for operation in hazardous environments, accessibility solutions for exploration of historical/tourism locations and collaborative learning environments). A use case example focused on a structural examination of railway tunnels along with a pilot study is presented, which can demonstrate the usefulness of the EPI system.

关键词： virtual reality Situated visualization Immersive analytics visual structural inspection

来源：评论

学校读者我要写书评

暂无评论

Interpretation of Brain Tumour Using Deep Learning Model 4th

Interpretation of Brain Tumour Using Deep Learning Model

引用

4th International conference on Computer and Communication Technologies, IC3T 2022

作者： Avanija, J. Ramji, Banothu Prabhu, A. Maheswari, K. vittal, R. Hitesh Sai Jagannadham, D.B.v. Kumar, voruganti Naresh Department of CSE Sree Vidyanikethan Engineering College Andhra Pradesh Tirupati India CMR Technical Campus Telangana Hyderabad India Department of CSE CMR Technical Campus Telangana Hyderabad India Hyundai Mobis Telangana Hyderabad India Department of ECE Gayatri Vidya Parishad College of Engineering Madhurawada Visakhapatnam India

ISBN: (纸本)9789811985621

Brain tumour analysis without human involvement is a crucial field of study. Convolutional neural networks, on the other hand, excelled at solving computer vision and other challenges such as visual object recognition, detection, and segmentation. It aids in the diagnosis of brain tumours by improving brain pictures utilising segmentation algorithms that are extremely resistant to noise and cluster size sensitivity issues, as well as automated area of interest (ROI) detection. One of the key arguments for using CNNs is that they have a high level of accuracy and do not require human feature extraction. Detecting a brain tumour and correctly identifying its kind is a difficult undertaking. Because of its widespread use in image recognition, CCN performs better than others. Providing assistance to diagnose brain tumours becomes difficult if performed manually. Furthermore, it becomes difficult process when there is a huge amount of data to assist. Extracting tumour from the images becomes difficult. To overcome this drawback, the proposed method uses convolutional neural network-based model using MobileNet for detection of brain tumours given MRI images. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Deep Learning: Exploring the Depths of Artificial Neural Networks for Advanced data analysis and Pattern Recognition

Deep Learning: Exploring the Depths of Artificial Neural Net...

引用

Global conference for Advancement in Technology (GCAT)

作者： Rajesh Jagadeesan Ravikumar A. Ammupriya Devi.P.P v.Samuthira Pandi Akhila Akula K. Sankar Software Engineering Senior Advisor Evernorth Health Services Chattanooga TN Department of MBA St Joseph's College of Engineering Chennai Department of Artificial Intelligence and Machine Learning Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Avadi Chennai Centre for Advanced Wireless Integrated Technology Chennai Institute of Technology Chennai Tamil Nadu India Department of ECE MLR Institute of Technology Hyderabad Department of Biomedical Engineering Rajalakshmi Engineering College Chennai

ISBN: (数字)9798350376685

ISBN: (纸本)9798350376692

This research provides a comprehensive exploration of LSTMs, CNNs, and RNNs, with a focus on their application in advanced data analysis and pattern recognition. We begin by examining the theoretical underpinnings of each architecture, highlighting their unique features and the mechanisms by which they process and learn from data. In the process of collecting long-term relationships in sequential data, LSTMs have been demonstrated to perform exceptionally well, making them an excellent choice for applications such as language modeling and time series prediction. CNNs are discussed in the context of their ability to extract hierarchical features from spatial data, rendering them particularly effective for image and video analysis. RNNs, with their inherent ability to process sequences of varying lengths, are analyzed for their applications in speech recognition and machine translation. Following this, the research begins to conduct a comparative examination of different architectures, examining how well they perform on benchmark datasets as well as challenges that are encountered in the real world. We assess their strengths and limitations, considering factors such as accuracy, computational efficiency, and scalability. Additionally, we explore the challenges associated with training deep neural networks, including the need for extensive data preprocessing, the risk of overfitting, and the importance of hyperparameter tuning. Finally, we discuss the implications of these findings for future research and practical applications in data analysis and pattern recognition. The study concludes that while each architecture has its niche, the combination of LSTMs, CNNs, and RNNs offers a powerful toolkit for tackling complex problems across diverse domains. The research underscores the potential of deep learning to unlock insights from data at unprecedented scales and complexities, paving the way for innovative solutions in fields ranging from healthcare to finance.

关键词： Deep learning Training Technological innovation Time series analysis Computer architecture Speech recognition Feature extraction Computational efficiency Tuning Overfitting

来源：评论

学校读者我要写书评

暂无评论

Sentiment analysis and Machine Learning Algorithm Implementation on Flipkart Product Customer Reviews

Sentiment Analysis and Machine Learning Algorithm Implementa...

引用

Advanced Computing Technologies and Applications (ICACTA), International conference on

作者： R Nancy Deborah S Alwyn Rajiv A vinora A Gobinath S vigneswaran K v Shiivadhanush Department of Information Technology Velammal College of Engineering and Technology Madurai Tamilnadu Department of Electronics and Communication Engineering Kamaraj College of Engineering and Technology Viruthunagar Tamilnadu

Sentiment analysis is a vital aspect of data mining that aims to prize private information from textual data. With the adding fashionability of online shopping platforms like Flipkart, assaying client feedback through product reviews have become a pivotal task for businesses to ameliorate their products and services. In recent times, researchers have explored the operation of machine knowledge algorithms for sentiment analysis of Flipkart product reviews. The results of this approach have demonstrated great promisein directly classifying the opposition of reviews as positive, negative, or neutral. colorful ways similar as Naive Bayes, SvM, Random Forest, Decision Trees, deep literacy, and rule-grounded approaches have been used for sentiment analysis on Flipkart reviews. also, preprocessing ways like Bag of Words, TF-IDF, Word Embeddings, and N-grams have been employed for point birth. This literature check highlights ten exploration papers published from 2017 to 2022, which bandy the perpetration of sentiment analysis and machine literacy algorithms on Flipkart product reviews. The findings of these studies give perceptivity into the effectiveness of different approaches and ways for sentiment analysis on Flipkart product reviews, and can guide unborn exploration in this field. We proposed a model called “GRUUSE” (Gated Recurrent Unit - Universal Sentence Encoder), which can directly classify the product reviews into any one of the three orders positive, negative or neutral. It is a neural network model that converts variable-length words into numerical representations of a fixed length using GRU cells. Tasks like phrase similarity or grouping are made possible by these representations, which capture semantic meaning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Real-Time Cyberbullying Detection Across Multimodal Platforms Using XLNET and Deep CNN 3

Real-Time Cyberbullying Detection Across Multimodal Platform...

引用

Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), International conference on

作者： Suresh Kumar K Abi C Asmitha v Dharshine S Department of Information Technology Sri Krishna College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

Cyberbullying has emerged as a primary societal concern with the widespread use of social media and online communication systems. The developing complexity of virtual interactions, together with text messages, social media comments, and images with embedded textual content, makes computerized detection way more challenging and complex. Conventional methods frequently fail to adequately convey the complex and dynamic character of cyberbullying practices. Here, we recommend a robust solution which makes use of Deep Convolutional Neural Networks (Deep CNNs) for potent classification of messages and XLNet for feature extraction. This can process a variety of input types, including textual and visual information, to enhance the identification of bullying patterns more efficient by integrating these contemporary system learning techniques. This framework's ability to detect various forms of online movement makes it more effective across multiple modalities thus contributing to the development of a safer and more inclusive online environment through corrective action for all users.

关键词： Training Sentiment analysis Adaptation models visualization Text analysis Cyberbullying Feature extraction Real-time systems data models Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Quantum of Corneal Scarring Calculation by Image analysis of Anterior Segment OCT Images 4

Quantum of Corneal Scarring Calculation by Image Analysis of...

引用

4th IEEE Eurasia conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2022

作者： Solomons, Cassandra D. Mathew, Ammu Anna Karthikeyan, v. Shanmugasundaram, vivekanandan Thomas, Hannah Mary Sathya, A. Rose, Jeyanth School of Electrical Engineering Vellore Institute of Technology Vellore India Christian Medical College Dept. of Radiation Oncology Vellore India

ISBN: (数字)9781728195797

ISBN: (纸本)9781728195797

Anterior Segment OCT is a valuable tool in providing B scan images of the cornea and anterior segment of the eye. Corneal scarring is a residue of various ocular diseases which include corneal ulcers, trauma and dystrophies. Corneal scarring results in corneal blindness and severe visual disability for the affected patient. Current grades of assessing corneal scarring are purely qualitative in nature. Though these clinical grades (nebula, macula, leucoma) are useful in guiding clinicians in making clinical decisions regarding treatment, they lack precision because of the absence of numeric data. Experimental research involving corneal scarring would greatly benefit from quantitative methods which are amenable to statistical analysis. Purpose: To determine the quantum of corneal scarring by image analysis of Anterior Segment Optical Coherence Tomographic (AS-OCT) vertical and horizontal scans of both the scarred and normal corneas of 32 subjects. Methods: Image processing and pixel analysis of the vertical and horizontal AS-OCT scans were done in the normal and scarred eyes to determine the mean pixel intensity, corneal thickness and quantum of corneal scarring. Results: The mean pixel intensity for scarred corneas was determined to be 126.2 for horizontal and 136.17 for vertical and 100.09 for horizontal, 96.75 for vertical on the normal corneas. The mean corneal thickness on scarred eyes was 204.46 and 217.38 for horizontal and vertical. Whereas on the normal corneas was 202.78 and 201.09 for horizontal and vertical. Quantum of variability for the scarred eyes was 26.11 and 39.42 for horizontal and vertical, respectively. The differences in medians of quantums of three scarred groups were statistically significant. © 2022 IEEE.

关键词： Image analysis

来源：评论

学校读者我要写书评

暂无评论

Development of an Augmented Reality Interface to Aid Astronauts in Extravehicular Activities

Development of an Augmented Reality Interface to Aid Astrona...

引用

IEEE Aerospace conference (AeroConf)

作者： Miller, Lea S. Fornito, Michael J. Flanagan, Riley Kobrick, Ryan L. Embry Riddle Aeronaut Univ 1 Aerosp Blvd Daytona Beach FL 32114 USA Paragon Space Dev Corp 445 Union BlvdSuite 125 Lakewood CO 80228 USA

ISBN: (纸本)9781728174365

NASA's projected return to the lunar surface with the Artemis program opens the possibility for technological developments that maximize human exploration in ways that were unimaginable during the Apollo program. Specifically, the implementation of heads-up displays (HUD) has the potential to greatly increase astronaut performance during extravehicular activities (EvA) by increasing their situational awareness, providing relevant scientific resources, and presenting live personal biometric data that can safeguard mission success and astronaut health. Though they are an excellent mechanism for conveying information without incurring unnecessary physical strain, the implementation of heads-up displays in the vacuum of space presents challenges including: illumination variance;brightness;contrast;interface control mechanisms;and the general volume of data that can be conveyed without inducing cognitive burnout through clutter. To satisfy the desire to improve astronaut performance with HUDs while also accounting for the above design challenges, ALEXEI, short for Augmented Lunar exploration and Extravehicular Interface, was developed in the Embry-Riddle Aeronautical University (ERAU) Spacesuit Utilization of Innovative Technology Laboratory (S.U.I.T. Lab) to be an augmented reality interface that can enhance an astronauts ability to conduct successful, scientifically relevant EvAs on the lunar surface. The resulting deliverable was created for the 2020 NASA SUITS (Spacesuit User Interface Technologies for Students) Challenge and balances features that past and current astronauts have expressed a functional desire for while also being cautious of human limitations in terms of visualizing and synthesizing information. Those features include a simplistic visual appearance, which displays a breadth of information that monitors mission progress, provides detailed instructions of mission tasks, and displays biometric vital signs, while only requiring a minimalistic level of i

关键词： visualization Biometrics (access control) Moon NASA User interfaces Task analysis Usability

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 << < 114 115 116 117 118 119 120 121 122 123 > >>

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：