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

4,580 篇 会议
572 篇 期刊文献
10 篇 学位论文
5 册 图书
1 篇 科技报告

馆藏范围

5,168 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,665 篇 工学
- 2,216 篇 计算机科学与技术...
- 1,445 篇 软件工程
- 576 篇 电气工程
- 365 篇 控制科学与工程
- 332 篇 信息与通信工程
- 258 篇 机械工程
- 248 篇 石油与天然气工程
- 215 篇 化学工程与技术
- 204 篇 生物医学工程（可授...
- 195 篇 生物工程
- 188 篇 仪器科学与技术
- 175 篇 土木工程
- 163 篇 光学工程
- 157 篇 建筑学
- 151 篇 动力工程及工程热...
- 132 篇 材料科学与工程（可...
- 124 篇 电子科学与技术（可...
- 122 篇 航空宇航科学与技...
1,589 篇 理学
- 601 篇 物理学
- 420 篇 数学
- 313 篇 地球物理学
- 270 篇 地质学
- 221 篇 生物学
- 203 篇 统计学（可授理学、...
- 191 篇 化学
- 120 篇 系统科学
659 篇 管理学
- 420 篇 管理科学与工程(可...
- 267 篇 图书情报与档案管...
- 173 篇 工商管理
400 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
30 篇 文学
12 篇 艺术学
4 篇 军事学
1 篇 历史学

主题

664 篇 visualization
382 篇 data visualizati...
242 篇 visual analytics
170 篇 data mining
149 篇 data analysis
135 篇 feature extracti...
101 篇 data models
93 篇 deep learning
92 篇 image color anal...
90 篇 task analysis
88 篇 training
81 篇 accuracy
79 篇 computational mo...
72 篇 analytical model...
71 篇 big data
66 篇 machine learning
62 篇 cameras
57 篇 predictive model...
57 篇 semantics
56 篇 convolutional ne...

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

4,725 篇 英文
234 篇 其他
161 篇 俄文
48 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 5168 条记录，以下是921-930 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：

Design and Development of Artificial Intelligence based Real-Time Traffic Sign Identification Scheme using Novel Learning Strategy 1

Design and Development of Artificial Intelligence based Real...

引用

1st IEEE International conference on Emerging Research in Computational Science, ICERCS 2023

作者： Tamilselvi, M. Iyswariya, A. Thapa, K. Naresh Kumar Princy, B. Anni vinithra Banu, T. Pandi, v. Samuthira Saveetha Institute of Medical and Technical Sciences School of Engineering Department of Ece Tamil Nadu Chennai India R.M.K. Engineering College Department of Ece Tamil Nadu Chennai India Sathyabama Institute of Science and Technology Department of Ece Tamil Nadu Chennai India Panimalar Engineering College Department of Computer and Communication Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Tamil Nadu Chennai India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350359756

The identification of traffic signs, also known as traffic sign recognition or TSR, is one of the most important aspects of research that has to be done before fully autonomous driving systems can be developed. When it comes to the data that are taken in, autonomous driving systems have very specific criteria. The data must be trustworthy and the system must be able to do situational analysis in real time;there is no room for complicated transformations or complex image processing techniques. This endeavour is made considerably more challenging by the fact that it takes place in an urban environment, which features a greater number of relocating or distracting objects (such as traffic signs, ads, parked cars, people, and so on). In spite of the abundance of approaches that have been published, solutions are often only tested on highways, in rural areas, or at very slow speeds. The development of traffic sign detection scheme, which involves the creation of unmanned vehicles, has moved forward in a consistent manner. Finding a way to eliminate interference from various environmental circumstances is one of the most essential technological difficulties. This is necessary in order to ensure that traffic sign recognition and identification can be carried out in an accurate and time-effective manner. However, because of the limitations of colour and edge detection, conventional visual object recognition is almost entirely dependent on the extraction of visual features. In this paper, a novel traffic sign identification is introduced called Learning Strategy for Traffic Sign Detection (LSTSD), in which it follows the Artificial Intelligence (AI) logic to improve the resulting metric to perform accurate identification of road side traffic signs in an intelligent manner. This learning strategy LSTSD is cross-validated with the conventional learning method called Convolutional Neural Network (CNN) to prove the efficiency of the proposed scheme in clear manner. © 2023 IEEE.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Emotion Recognition from RGB Kinect videos and Physiological Signals Using Pre-Trained CNN Model

Emotion Recognition from RGB Kinect Videos and Physiological...

引用

Intelligent Computing and Next Generation Networks（ICNGN), International conference on

作者： Shruthi Anand Lenin Mookiah Bakkialakshmi v S S Sembon Surakshitha Department of Computing Technologies SRM Institute of Science and Technology Kattankalathur India Independent Researcher Nevada USA

ISBN: (数字)9798331529222

ISBN: (纸本)9798331529239

This study presents an innovative approach to emotion recognition by integrating RGB Kinect video data with physiological signals, including electroencephalography (EEG), electrocardiography (ECG), and galvanic skin response (GSR). Using the AMIGOS dataset, which includes video recordings and self-assessment emotional ratings, we improve emotion prediction through a comprehensive multimodal analysis. Our method involves feature extraction and averaging from both video and physiological signals, emphasizing the connection between visual cues and emotional responses. A pre-trained ResNet model is used for advanced feature extraction from video data. various machine learning algorithms are applied to evaluate predictive models against self-assessment labels. Results indicate that the combination of ResNet-based visual features and physiological signals enhances emotion prediction accuracy, underscoring the value of a multimodal approach in capturing complex emotional dynamics.

关键词： visualization Emotion recognition Machine learning algorithms Predictive models Electrocardiography Brain modeling Feature extraction Physiology data models Skin

来源：评论

学校读者我要写书评

暂无评论

SHAPELET BASED visual ASSESSMENT OF CLUSTER TENDENCY IN ANALYZING COMPLEX UPPER LIMBMOTION

SHAPELET BASED VISUAL ASSESSMENT OF CLUSTER TENDENCY IN ANAL...

引用

IEEE International conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Datta, Shreyasi Karmakar, Chandan Rathore, Punit Palaniswami, Marimuthu Univ Melbourne Dept Elect & Elect Engn Melbourne Vic Australia Deakin Univ Sch Informat Technol Melbourne Vic Australia MIT Senseable City Lab Cambridge MA 02139 USA

ISBN: (纸本)9781728176055

The evolution of ubiquitous sensors has led to the generation of copious amounts of waveform data. Human motion waveform analysis has found significance in clinical and home-based activity monitoring. exploration of cluster structure in such waveform data prior to developing learning models is an important pattern recognition problem. A prominent category of algorithms in this direction, known as visual Assessment of (cluster) Tendency (vAT), employs visual approaches to study cluster evolution through heat maps. This paper proposes shape-ivAT, a new relative of an improved vAT model, that captures local time-series characteristics through representative subsequences, known as shapelets, to identify interesting patterns in motion data. We propose an unsupervised method for shapelet extraction using maximin shape sampling and shape-based distance computation for selecting key shapelets representing characteristic motion patterns. These shapelets are used to transform waveform data into a dissimilarity matrix forvAT evaluation. We demonstrate that the proposed method outperforms standard vAT with global distance measures for identifying complex upper limb motion captured using a camera-based motion sensing device. We also show that our method has significance in efficient and interpretable cluster tendency assessment for anomaly detection and continuous motion monitoring.

关键词： Cluster tendency distance measures shapelet time-series upper limb motion

来源：评论

学校读者我要写书评

暂无评论

Predictive analysis of Kidney Diseases with Artificial Intelligence and data Science

Predictive Analysis of Kidney Diseases with Artificial Intel...

引用

visual Analytics and data visualization (ICvADv), International conference on

作者： G Eswar C Hariharan S Lavein v Akilandeswari Department of Computer Science and Engineering Velammal College of Engineering and Technology

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

In the Field of Medical diagnosis, nowadays there are many new methods are getting introduced each day and also gets advanced by many people around the world. The Kidney is one of the most vital organ of a Human body that helps a lot by filtering blood and throws the waste toxic contents through excretory organs. But the food habits and other bad habits can affect the process of Kidney and further even affects kidney. As a result our kidney can also suffer from various disease. Most vital Kidney diseases can include Chronic Kidney Disease(CKD), Diabetic Nephropathy at the 2nd stage of Diabetes, and still many more. In the process of predicting of these diseases, we can use machine learning algorithms like Random Forest with Decision Tree and Supervised Learning algorithms we can train a model that can use the previous datasets to clarify if the new person is diagnosed with the particular Kidney disease. The Random Forest algorithm provides around 90% accuracy that is better in prediction of results for the collected information. Using these techniques we can detect the problem at early stage which can give a greater chance to prevent it from getting worse.

关键词： Analytical models Machine learning algorithms Accuracy Predictive models Prediction algorithms data models Diabetes Kidney Random forests Diseases

来源：评论

学校读者我要写书评

暂无评论

data-driven visual analytics of Human Mobility data and green cover using Image Processing for Smart Cities

Data-driven visual analytics of Human Mobility data and gree...

引用

Intelligent Technologies (CONIT), International conference on

作者： Sivasubramanian Ramanathan Kulsoom Syed Tejaswini Chavan SVKMs NMIMS Navi Mumbai B. Tech Computer Science & Business Systems Mumbai India SVKMs NMIMS Navi Mumbai School of Technology Management & Engineering Mumbai India

This research paper presents an approach to data-driven visual analytics of human mobility data using Kernel Density Estimation visualized through heatmaps, highlighting the need for exploration of forecasting methods and intuitive visualizations using the ARIMA model. A specific geographic area is chosen for the demonstration of the scope of the proposed system. The system is a web application developed using Streamlit, an open-source python framework. To effectively implement the smart city concept, it is crucial to integrate diverse IoT systems, data sources, data streams, and analytical tools into a unified and seamless platform that facilitates the collection, analysis and presentation of information related to urban systems and subsystems. We propose taking into consideration several attributes when analyzing human mobility patterns, such as vehicle/traffic density, modes of transport, transport data, demographics, latitude, and longitude. Additionally, the system utilizes image processing as an efficient method for calculating urban green cover using morphological operations that are computationally cheaper and easy to use as compared to traditional surveys that are time and resource intensive. This information is used to develop smart plans to sustain or increase green cover in select areas, leading to the creation of sustainable and green smart cities.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Stock Market Prediction Based on Time Series data and Multimodal Sentiments

Stock Market Prediction Based on Time Series Data and Multim...

引用

IEEE International conference on Big data Computing Service and Applications (BigdataService)

作者： Jikang Zhao Yancong Deng School of Computing University of Leeds Leeds United Kingdom Jacob School of Engineering University of California San Diego La Jolla United States

ISBN: (数字)9798350366389

ISBN: (纸本)9798350366396

Investor sentiment significantly influences stock market dynamics, often displaying pronounced volatility. Con-currently, objective financial news remains a crucial determinant of market shifts. This study sourced an extensive collection of textual comments from the StockTwits trading platform. We then implemented a semi-supervised GAN-Bert methodology to perform sentiment analysis on these unlabeled remarks. Following this, the Inception v3 model facilitated sentiment evaluation of financial visuals from The Wall Street Journal (WSJ). Upon validation and integration of sentiment scores from these visuals, we amalgamated sentiments derived from both textual and visual data into a Bi-LSTM framework. This integrated model underwent training for predictive analytics, underpinning trading simulations based on anticipated returns. The experimental results demonstrated a notable return of 30.41% during our evaluation period, showcasing an improvement over single sentiment feature analysis.

关键词： Training visualization Analytical models Sentiment analysis Time series analysis Machine learning Predictive models data models Stock markets Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Dynamic Fusion of Text, video and Audio models for Sentiment analysis 4th

Dynamic Fusion of Text, Video and Audio models for Sentiment...

引用

4th International conference on Innovative data Communication Technologies and Application, ICIDCA 2022

作者： vasanth, K. Srideviponmalar, P. Shete, vikram Ravi, C.N. venkata Sai Krithik, P. Vidya Jyothi Institute of Technology Hyderbad500075 India School of Computing SRM Institute of Science and Technology Chennai603203 India NinsarAgritech Pune411038 India

The paper aims to propose a technique for sentiment analysis that combines audio, textual, and visual data collected from customer input on social media sites such as Instagram, Facebook, and Twitter, as well as feedback forms and product evaluations. The feelings of individuals are represented in these online social media reviews. As a result, sentiment research will be essential for helping the growth of enterprises and individuals. The work assigns variable weights using recording technique for different modules and subsequently fusing it. This enables us to determine which model is optimal for sentiment analysis and how each model affects the final results. A system that can extract information about people's feelings regarding a certain product from text, audio, and video. We may utilize model predictions to determine the amount of consumer happiness with the product, enabling the company to take the required steps to enhance the product. © 2023 The Authors. Published by Elsevier B.v.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Local Field Potential Microstate analysis 18

Local Field Potential Microstate Analysis

引用

IEEE 18th International conference on Intelligent Computer Communication and Processing (ICCP)

作者： Salagean, Andreea Pasc, Andreea-Madalina Ardelean, Eugen Richard Muresan, Raul C. Moca, vasile v. Dinsoreanu, Mihaela Potolea, Rodica Lemnaru, Camelia Tech Univ Cluj Napoca Cluj Napoca Romania Transylvanian Inst Neurosci Cluj Napoca Romania

ISBN: (纸本)9781665464376

Correct depth of anesthesia (DOA) assessment is a serious and widespread medical problem and an active scientific research topic. Anesthesia is known to alter the dynamics of neural networks within the brain that ultimately results in the impairment of pain perception. Nevertheless, linking the composition and dosage of various anesthetics, to a target level of anesthesia is not trivial. In this paper we explore the use of microstates as a viable tool to discriminate between anesthesia levels in intracranial recordings from mouse visual cortex. We show such symbolic analysis is able to capture DOA specific information in local field potentials (LFP). Microstates are characterized by the appearance of set of prototypical maps of activations over recording sites (electrodes) that define stereotypical patterns of activation in the recorded neural networks. Although microstates have been defined and characterized in electroencephalogram (EEG) data, our study shows for the first time that microstates can be effective when considering LFPs as well. We performed statistical analysis of average duration, time coverage, and occurrence of the microstates in order to differentiate between different DOA levels. By increasing the number of microstates, the analysis is more insightful and it is easier to discriminate between DOA levels.

关键词： LFP microstates anesthesia mice

来源：评论

学校读者我要写书评

暂无评论

visualization system for a radio images 10

Visualization system for a radio images

引用

10th International Scientific and Practical conference Information and Measuring Equipment and Technologies, IMET 2020

作者： Khmelev, v.L. Gromov, M.L. Department of Radiophysics National Research Tomsk State University Tomsk Russia

Radio wave tomography (radiotommography) allows restoring the shape of objects hidden behind radio-transparent barriers. Radiotommography detectors use this technology for location and visualization for metal, metalized, and dielectric communications in walls and floors. An interpretation of tomography images obtained during radio wave measuring is a difficult task for non-specialists. Moreover, they have no visual reference to the objects of the scene under exploration. To simplify a perception and analysis of the obtained data of radio wave measurements, we propose to combine digital radio and optical images of the scene. This article describes the solution to the problem of combining optical and radio wave images. It allows to estimate visually the size and position of the hidden objects. © Published under licence by IOP Publishing Ltd.

关键词： Radio waves

来源：评论

学校读者我要写书评

暂无评论

Tackling Well Productivity and Sustainability in a Jurassic Horizontal HPHT Well with the First Multistage Unconventional Hydraulic Fracturing in MFS Formation: A Case Study of an exploration Well

Tackling Well Productivity and Sustainability in a Jurassic ...

引用

2024 SPE International conference and Exhibition on Formation Damage Control, FD 2024

作者： Bosalhah, A. Al-Mulla, S. Duggirala, v. Ayyavoo, M. Al-Saqabi, M.B. Mubarak, A. Salem, A. Enkababian, P. Peiwu, L. Fituri, M. Pochetnyy, v. Kuwait Oil Company Kuwait SLB Middle East Saudi Arabia SLB Saudi Arabia

ISBN: (纸本)9781959025139

The unconventional Lower Najmah Limestone MFS fractured reservoir is a nanodarcy rock located below the Najmah Kerogen source rock. The first horizontal well drilled across the MFS is in North Kuwait and was drilled to explore the hydrocarbon potential. The 3D seismic interpretation and several seismic attributes indicate that the well location is likely to encounter a high fracture corridor area to support production after multistage hydraulic fracturing. The lateral length is approximately 1,900 ft placed in the MFS after reaching the planned total depth (TD), 18,900 ft. The well was completed using a 15,000-psi-rated openhole multistage completion (MSC) system to place six hydraulic proppant fractures and access most of the nearby natural fractures in the reservoir. Over 20 well interventions were conducted by coiled tubing (CT) to shift the MSC frac ports, log the well by caliper and spinners, perforate stages, attempt milling out the inner completion seats, and, finally, perform nitrogen lifting of the hydraulic fracturing treatment fluids to the surface. Due to the high-pressure nature of the reservoir and multiple additional completion challenges, it was difficult to initiate hydraulic fractures into the formation below the maximum allowable working pressure of completion. Therefore, 20 ft of 12 shots per foot (SPF) perforations were added per stage for four stages, which significantly lowered the fracture initiation pressures. Complete data fracturing analysis was conducted in each stage to redesign stimulation treatments. Four unconventional hydraulic proppant fracturing stages were successfully completed, sequencing high-viscosity slickwater and a crosslinked fluid system placing 110,000 lbm of proppant per stage into the formation. Multiple milling attempts were conducted with CT to reach TD but were unsuccessful due to uncertain obstructions. However, an unconventional method was applied and finally succeeded in accessing the full lateral and flowing bac

关键词： Horizontal wells

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 << < 89 90 91 92 93 94 95 96 97 98 > >>

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：