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

10,152 篇 会议
404 篇 期刊文献
16 册 图书
14 篇 学位论文
5 件 标准

馆藏范围

10,591 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,442 篇 工学
- 3,488 篇 计算机科学与技术...
- 2,193 篇 信息与通信工程
- 1,747 篇 电气工程
- 1,493 篇 软件工程
- 948 篇 控制科学与工程
- 580 篇 仪器科学与技术
- 537 篇 机械工程
- 390 篇 电子科学与技术（可...
- 366 篇 动力工程及工程热...
- 310 篇 测绘科学与技术
- 202 篇 交通运输工程
- 180 篇 生物工程
- 146 篇 建筑学
- 143 篇 材料科学与工程（可...
- 141 篇 生物医学工程（可授...
- 135 篇 土木工程
- 123 篇 安全科学与工程
- 104 篇 环境科学与工程（可...
- 101 篇 化学工程与技术
1,411 篇 理学
- 496 篇 物理学
- 490 篇 数学
- 246 篇 生物学
- 187 篇 系统科学
- 162 篇 统计学（可授理学、...
- 152 篇 化学
845 篇 管理学
- 641 篇 管理科学与工程(可...
- 256 篇 图书情报与档案管...
- 220 篇 工商管理
269 篇 医学
- 242 篇 临床医学
- 115 篇 基础医学(可授医学...
83 篇 经济学
75 篇 农学
55 篇 法学
43 篇 军事学
37 篇 文学
18 篇 教育学
8 篇 艺术学

主题

3,778 篇 wireless sensor ...
1,729 篇 intelligent sens...
1,052 篇 sensors
925 篇 sensor systems
799 篇 monitoring
752 篇 wireless communi...
645 篇 sensor phenomena...
607 篇 intelligent netw...
456 篇 temperature sens...
432 篇 neural networks
389 篇 energy consumpti...
376 篇 signal processin...
318 篇 routing
310 篇 internet of thin...
293 篇 sensor networks
252 篇 target tracking
252 篇 sensor fusion
248 篇 protocols
226 篇 cameras
223 篇 robot sensing sy...

机构

24 篇 department of co...
17 篇 univ melbourne d...
16 篇 school of electr...
16 篇 king mongkut's u...
15 篇 maharishi school...
15 篇 university of ph...
14 篇 school of inform...
14 篇 school of comput...
13 篇 school of electr...
13 篇 school of inform...
11 篇 institute for in...
11 篇 department of ma...
10 篇 centre of resear...
10 篇 syracuse univ de...
10 篇 national institu...
9 篇 department of co...
9 篇 college of infor...
9 篇 beijing key labo...
9 篇 college of infor...
9 篇 ieee

作者

27 篇 sakorn mekruksav...
27 篇 anuchit jitpatta...
23 篇 palaniswami mari...
23 篇 mekruksavanich s...
21 篇 jitpattanakul an...
15 篇 leckie christoph...
15 篇 huadong ma
14 篇 wang wei
13 篇 varshney pramod ...
13 篇 leonard barolli
13 篇 rajasegarar suth...
13 篇 barolli leonard
12 篇 liang liu
12 篇 elmazi donald
12 篇 yang yang
12 篇 hanebeck uwe d.
12 篇 uwe d. hanebeck
11 篇 christos g. pana...
10 篇 a. sachenko
10 篇 hnoohom narit

语言

10,426 篇 英文
86 篇 中文
74 篇 其他
6 篇 土耳其文
2 篇 西班牙文

检索条件"任意字段=Intelligent Sensors, Sensor Networks and Information Processing Conference"

共 10591 条记录，以下是201-210 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：

Navigating the Future: A Review of Contemporary AI Methodologies in Autonomous Vehicle Development for 6G networks 5

Navigating the Future: A Review of Contemporary AI Methodolo...

引用

5th IEEE International conference on Emerging Trends in Electrical, Electronic and Communications Engineering, ELECOM 2024

作者： Lama, Sirine Akinsolu, Mobayode O. Wrexham University Faculty of Arts Computing and Engineering Wrexham United Kingdom School of Electrical and Mechanical Engineering ECAM LaSalle Lyon France

ISBN: (纸本)9798331532475

The development of autonomous vehicles (AVs) has advanced dramatically due to the rapid evolution of artificial intelligence (AI) technologies, which hold the potential to revolutionize the transportation industry. This paper investigates the integration of sensor fusion, deep learning (DL), and machine learning (ML) techniques with 6G network infrastructure to enhance A V capabilities. 6G networks' improved connectivity and reduced latency enable real-Time vehicle-To-everything (V2X) communication and data processing, which are essential for the effective and safe operation of A Vs. Through a comprehensive review of recent literature and case studies, this paper assesses the effectiveness of AI technologies in real-world scenarios, highlighting their impact on the automotive industry. It covers ethical and technological issues, including data privacy, decision-making, cybersecurity risks, data processing, and sensor reliability. The paper also examines the regulatory environment, underscoring the necessity of well-coordinated international frameworks. The findings emphasize a multidisciplinary approach to developing A V technology and creating laws that promote public safety and confidence. Significant research gaps are identified, and future research directions are suggested, including developing reliable sensors, maintaining cybersecurity, and creating efficient algorithms and regulatory frameworks. These initiatives will help AVs operate seamlessly in an intelligent transportation ecosystem supported by 6G networks. © 2024 IEEE.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

ARSteth: Enabling Home Self-Screening with AR-Assisted intelligent Stethoscopes 22

ARSteth: Enabling Home Self-Screening with AR-Assisted Intel...

引用

22nd ACM/IEEE International conference on information processing in sensor networks (IPSN)

作者： Hou, Kaiyuan Xia, Stephen Bejerano, Emily Wu, Junyi Jiang, Xiaofan Columbia Univ New York NY 10027 USA

ISBN: (纸本)9798400701184

The stethoscope is one of the most important diagnostic tools used by healthcare professionals, through a process called auscultation, to screen patients for abnormalities of the heart and lungs. While there are digital stethoscopes on the market which ease this process, it still takes years of training to properly use these devices to listen for abnormal sounds within the body. We present ARSteth, an intelligent stethoscope platform that improves the accessibility of stethoscopes for the general population, allowing anyone to perform auscultation in the comfort of their own homes. Our platform utilizes a combination of augmented reality (AR), acoustic intelligence, and human-machine interaction to dynamically guide users on where to place the stethoscope on different parts of the body (auscultation points), through visual and audio cues. Through user studies, we show that ARSteth, on average, can guide users within 13.2 mm from optimal auscultation points marked by licensed physicians in 13.09 seconds for each auscultation point. By guiding users towards more effective auscultation points, make preventative health screening more accessible and effective for everyone we are able to achieve higher confidence on classifying heart murmurs.

关键词： digital stethoscope human computer interaction smart home

来源：评论

学校读者我要写书评

暂无评论

A novel attention-based long short-term memory network for human activity recognition based on wearable sensor data

A novel attention-based long short-term memory network for h...

引用

2024 International conference on Automation Control, Algorithm, and intelligent Bionics, ACAIB 2024

作者： Yuan, Huihui School of Information Engineering Shanghai Maritime University Shanghai201306 China

ISBN: (纸本)9781510682597

Wearable sensor-based activity recognition refers to the utilization of sensors worn on the body to collect human motion data. Through deep learning methods, different activities can be classified and recognized. This technology has wide applications in areas like health monitoring, smartwatches, and sports tracking. While deep learning-based Human Activity Recognition (HAR) has made great progress, challenges such as insufficient feature representation and underutilization of spatial and channel information still exist, leading to potential misclassifications. To address these issues, we propose an Attention-based Long Short-Term Memory Convolutional Neural Network framework (ACL-CNN). In this framework, the Convolutional Block Attention Module (CBAM) applies adaptive spatial and channel attention to the extracted features, highlighting important spatial positions and channel correlations to better capture behavioral characteristics. Additionally, the Long Short-Term Memory (LSTM) module processes the time-series data after feature extraction, effectively capturing long-term dependencies in the temporal sequence and enhancing the model's capability to model time-series data. The experiments are carried out on two publicly accessible datasets, namely WISDM and OPPORTUNITY. The results show that our method achieves the best performance on all four evaluation metrics. This validates the effectiveness and superiority of our method in wearable sensor-based activity recognition. © 2024 SPIE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

MULTI-sensor information FUSION TECHNOLOGY: PRINCIPLE, APPLICATIONS AND KEY TECHNOLOGIES EXPLORATIONS 2

MULTI-SENSOR INFORMATION FUSION TECHNOLOGY: PRINCIPLE, APPLI...

引用

2nd International conference on Mechatronic Automation and Electrical Engineering, ICMAEE 2024

作者： Wu, Wenchen Xu, Ruizhe Guangdong Country Garden School Foshan528312 China The Affiliated Middle School of Fujian Normal University Fuzhou350007 China

ISBN: (纸本)9781837242672

Multi-sensor information fusion (MSIF) has emerged as a critical technology in various fields due to the growing complexity of systems and the demand for precise information. This paper explores the fundamental principles, key technologies, and potential applications of MSIF. The paper delves into the design and implementation of MSIF systems, discussing various system architectures such as centralized, distributed, and hybrid models. Key technologies crucial to MSIF, including sensor calibration, data association, filtering methods, and fusion algorithms like Bayesian Criterion, Dempster-Shafer Evidence Theory, Fuzzy Theory, and Neural networks, are thoroughly examined. The study highlights the importance of data preprocessing and feature extraction techniques in achieving efficient data fusion. Furthermore, the potential of MSIF in diagnosing complex systems is demonstrated through applications in industrial automation, environmental monitoring, and healthcare. MSIF also faces challenges related to data synchronization, algorithm complexity, and the integration of diverse data sources. With ongoing advancements in sensor technology and data processing, MSIF is poised to play an increasingly significant role in intelligent systems, including autonomous vehicles and smart cities. © The Institution of Engineering & Technology 2024.

关键词： information fusion

来源：评论

学校读者我要写书评

暂无评论

Enhancing the capability of registration networks in multimodal remote sensing image registration using synthetic data 4

Enhancing the capability of registration networks in multimo...

引用

4th International conference on Image processing and intelligent Control, IPIC 2024

作者： Tian, Liyu Luo, Jin Yu, Meng China University of Geosciences Wuhan430074 China Duhai Technology and Humanistic Intelligence Laboratory Guangzhou510289 China School of Mathematics Sun Yat-sen University Guangzhou510000 China

ISBN: (纸本)9781510682313

The accurate alignment of multimodal remote sensing images is of paramount importance for a wide range of applications, including environmental monitoring, change detection, and resource management. These tasks require robust registration techniques capable of handling the inherent variations in image appearance due to different sensor modalities. In this study, we introduce a novel approach that leverages synthetic data to improve the performance of image registration networks for multimodal remote sensing imagery. Our method involves the generation of synthetic image pairs through color-space transformations applied to synthetic data, which are then utilized to fine-tune a neural network specifically designed for image registration tasks. By training on these synthetic pairs, the network learns to cope with the complex variations between different sensor modalities. The fine-tuned network demonstrates state-of-the-art (SOTA) performance when applied to real-world remote sensing images, showcasing the effectiveness of synthetic data in enhancing the network’s ability to generalize across diverse imaging conditions. This advancement represents a significant step forward in the field of remote sensing image analysis, offering a robust solution for the precise registration of multimodal datasets. © 2024 SPIE.

关键词： Image registration

来源：评论

学校读者我要写书评

暂无评论

HBOD: A Novel Dataset with Synchronized Hand, Body, and Object Manipulation Data for Human-Robot Interaction 19

HBOD: A Novel Dataset with Synchronized Hand, Body, and Obje...

引用

IEEE 19th International conference on Body sensor networks (IEEE BSN)

作者： Kang, Peiqi Zhu, Kezhe Jiang, Shuo He, Bin Shull, Peter Shanghai Jiao Tong Univ Sch Mech Engn State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China Frontiers Sci Ctr Intelligent Autonomous Syst Shanghai 200120 Peoples R China

ISBN: (纸本)9798350338416

Estimating hand and body posture is crucial for enabling human-robot collaboration, preventing occupational diseases, and training humanoid robots. Although advances in wearable motion sensors, such as Inertial Measurement Units (IMUs), have resulted in public datasets in industrial and occupational settings, these datasets rarely include movements with subjects holding and manipulating objects. However, it is crucial to have data on how humans move and interact with different objects so that we can better understand human motion intention and movement strategies in specific scenarios. We thus propose the HBOD dataset (hand-body-object dataset), which encompasses synchronized human pose data from an IMU sensor network, hand posture data from a smart data glove, and object position and attitude information obtained from a motion capture system, while subjects move and interact with a screwdriver, hammer, spanner, electric drill, and a rectangular workpiece. This paper provides an overview of the hardware setup, experimental protocol, data format, and data visualization results. This dataset provides crucial object information absent from existing datasets, thus offering highly valuable manipulation data for occupational diseases research, human-robot interaction, and robot skill acquisition.

关键词： Human posture Hand gesture In-hand object estimation

来源：评论

学校读者我要写书评

暂无评论

Harnessing Deep Learning for Activity Recognition in Seniors' Daily Routines with Wearable sensors 47

Harnessing Deep Learning for Activity Recognition in Seniors...

引用

47th International conference on Telecommunications and Signal processing, TSP 2024

作者： Mekruksavanich, Sakorn Phaphan, Wikanda Jitpattanakul, Anuchit School of Information and Communication Technology University of Phayao Department of Computer Engineering Phayao Thailand Research Group in Statistical Learning and Inference King Mongkut's University of Technology North Bangkok Department of Applied Statistics Faculty of Applied Science Bangkok Thailand Intelligent and Nonlinear Dynamic Innovations Research Center King Mongkut's University of Technology North Bangkok Department of Mathematics Faculty of Applied Science Bangkok Thailand

ISBN: (纸本)9798350365597

Wearable sensors are increasingly popular for monitoring the daily activities of older individuals, sparking significant interest in human activity recognition (HAR). Accurate and timely identification of these activities is crucial for providing personalized care and timely interventions to maintain the well-being of elderly individuals. However, existing HAR methods often need support with complex activity patterns, limited labeled data, and the need for real-time performance. To address these challenges, this study proposes a novel deep-learning approach called ResBiGRU for precisely identifying daily activities in older adults using wearable sensors. The ResBiGRU architecture combines residual connections with BiGRU networks to capture short-term and long-term dependencies in sensor data effectively. We also propose a data augmentation strategy to improve generalization performance. Evaluation of the HAR70+ dataset, consisting of activities performed by 18 elderly individuals, demonstrates superior performance of our ResBiGRU model with an accuracy of 97.39% and an F1-score of 97.74%. Furthermore, our model supports real-time inference, making it suitable for practical applications. Implementing the ResBiGRU approach could significantly enhance monitoring and care for older adults by accurately identifying their daily activities. This research advances HAR methods tailored for elderly individuals, opening new avenues for personalized healthcare and assisted living technologies. © 2024 IEEE.

关键词： Wearable sensors

来源：评论

学校读者我要写书评

暂无评论

intelligent Building System based on Multi-Modal Optimization of Energy Data Center 3

Intelligent Building System based on Multi-Modal Optimizatio...

引用

3rd International conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Du, Danyou School of Architecture Science and Civil Engineering Xiamen Institute of Technology Fujian361000 China

ISBN: (数字)9798350396157

ISBN: (纸本)9798350396157

This study introduces an intelligent building system designed for comprehensive data management, which integrates various subsystems to regulate devices and technologies in buildings. As a fundamental pillar of smart buildings, building mechanization mechanisms improve efficiency, reduce energy consumption, and prioritize human interests. This study specifically focuses on multimodal optimization within energy data centers, employing innovative strategies to improve system efficiency, with special emphasis on energy resource management in data centers. The proposed system integrates ZigBee-based sensor networks, tilt sensors, and temperature sensors for comprehensive architectural security monitoring. A semantic data model based on metadata is applied for improved analysis and representation of multimodal data, contributing to improved clarity and efficiency in data management. The proposed research study also addresses issues related to uninterruptible power supply (UPS) and automatic repair of primary physical connection relationships in building electromechanical systems. The final intelligent building system design includes a hierarchy of integrated platforms with communication interface layers, core control layers, and user interface layers. The effectiveness of the system is demonstrated through a systematic simulation using the METASYS building control system. The experiment shows the successful implementation of Modbus communication for power conversion and distribution systems, highlighting the practical application of the proposed intelligent building system. © 2024 IEEE.

关键词： information management

来源：评论

学校读者我要写书评

暂无评论

Adaptive FCM Clustering Routing Algorithm Based on PSO Optimization 2

Adaptive FCM Clustering Routing Algorithm Based on PSO Optim...

引用

2nd International conference on Signal processing and intelligent Computing, SPIC 2024

作者： Liu, Yue Liang, Ying Shenyang Ligong University School of Information Science and Engineering Shenyang China

ISBN: (纸本)9798350368888

To solve the problems of large node energy consumption and missing data transmission path in Marine sensor networks, a clustering routing algorithm utilizing particle swarm optimization (PSO-DAFCA) was introduced. The algorithm uses fuzzy C-means method of particle swarm optimization to optimize cluster head selection and cluster member configuration, and selects the best cluster head by dynamically updating cluster center. During the data transmission phase, combined with the global search ability of cat swarm optimization algorithm, the path evaluation function based on energy and distance parameters is introduced to determine the optimal transmission route. Simulation results indicate that the PSO-DAFCA algorithm can enhance network energy efficiency, prolong network lifespan, and improve the real-time accuracy of marine environmental monitoring. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Additive manufacture of polymeric organometallic ferroelectric diodes (POMFeDs) for structural neuromorphic hardware 23

Additive manufacture of polymeric organometallic ferroelectr...

引用

Annual Neuro-Inspired Computational Elements conference (NICE)

作者： Browner, Davin Anderson, Paul Sareh, Sina Royal Coll Art Robot Lab London England

ISBN: (纸本)9781450399470

Hardware design and implementation for online machine learning applications is complicated by a number of facets of conventional artificial neural networks (ANN), e.g. deep neural networks (DNNs), such as reliance on atemporal locality, offline learning using large datasets, potential difficulties in transfer from model to substrates, and issues with processing of noisy sensory data using energy-efficient and asynchronous information processing modalities. Analog or mixed-signal spiking neural networks (SNNs) have promise for lower power, temporally localised, and stimuli selective sensing and inference but are difficult fabricate at low cost. Investigation of beyond-CMOS alternative organic substrates may be worthwhile for development of unconventional neuromorphic hardware with pseudo-spiking dynamics for structural electronics integration in bio-signal processing and robotics. Here, polymeric organometallic ferroelectric diodes (POMFeDs) are introduced for development of printable ferroelectric in-sensor SNNs.

关键词： Event based spiking auditory sensors spiking neural networks ferroelectrics additive manufacture

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 << < 17 18 19 20 21 22 23 24 25 26 > >>

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：