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

10,185 篇 会议
404 篇 期刊文献
56 册 图书
14 篇 学位论文
5 件 标准

馆藏范围

10,664 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,454 篇 工学
- 3,495 篇 计算机科学与技术...
- 2,201 篇 信息与通信工程
- 1,750 篇 电气工程
- 1,491 篇 软件工程
- 951 篇 控制科学与工程
- 581 篇 仪器科学与技术
- 538 篇 机械工程
- 391 篇 电子科学与技术（可...
- 367 篇 动力工程及工程热...
- 310 篇 测绘科学与技术
- 205 篇 交通运输工程
- 179 篇 生物工程
- 147 篇 建筑学
- 142 篇 生物医学工程（可授...
- 141 篇 材料科学与工程（可...
- 138 篇 土木工程
- 124 篇 安全科学与工程
- 106 篇 环境科学与工程（可...
- 102 篇 化学工程与技术
1,411 篇 理学
- 496 篇 物理学
- 489 篇 数学
- 245 篇 生物学
- 187 篇 系统科学
- 162 篇 统计学（可授理学、...
- 151 篇 化学
846 篇 管理学
- 639 篇 管理科学与工程(可...
- 259 篇 图书情报与档案管...
- 220 篇 工商管理
271 篇 医学
- 244 篇 临床医学
- 117 篇 基础医学(可授医学...
83 篇 经济学
75 篇 农学
55 篇 法学
44 篇 军事学
37 篇 文学
19 篇 教育学
8 篇 艺术学

主题

3,786 篇 wireless sensor ...
1,743 篇 intelligent sens...
1,053 篇 sensors
932 篇 sensor systems
803 篇 monitoring
756 篇 wireless communi...
646 篇 sensor phenomena...
608 篇 intelligent netw...
457 篇 temperature sens...
432 篇 neural networks
389 篇 energy consumpti...
379 篇 signal processin...
320 篇 routing
313 篇 internet of thin...
296 篇 sensor networks
253 篇 target tracking
253 篇 sensor fusion
246 篇 protocols
226 篇 cameras
222 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 mekruksavanich s...
22 篇 palaniswami mari...
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 vikrant bhateja
12 篇 hanebeck uwe d.
12 篇 uwe d. hanebeck
11 篇 christos g. pana...
10 篇 a. sachenko

语言

10,304 篇 英文
268 篇 其他
90 篇 中文
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 10664 条记录，以下是931-940 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：

AoI-aware DAV Data Collection Based on the IRS's Phase Estimation in Wireless sensor networks

AoI-aware DAV Data Collection Based on the IRS's Phase Estim...

引用

International conference on Wireless Communications and Signal processing (WCSP)

作者： Jiaqi Tang Juan Liu Xiaofan He Lingfu Xie Long Qu School of Electrical Engineering and Computer Science Ningbo University Zhejiang China Electronic Information School Wuhan University Wuhan China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

In Wireless sensor networks (WSNs), ensuring the real-time and reliable collection of state information is crucial for maintaining the efficient operation of the network. To ensure freshness of information in delay-sensitive applications such as autonomous driving, this paper combines Unmanned Aerial Vehicle (UAV) and intelligent Reflecting Surface (IRS) technologies to deal with the IRS-aided UAV online data collection problem. In the formulated problem, the average Age of information (AoI) of sensor nodes (SNs) is minimized by jointly optimizing the IRS's phase shifts, the UAV's trajectory, and SN association. The problem is divided into two coupled subproblems: the IRS's phase control and UAV's data collection. We propose the framework of Proximal Policy Optimization (PPO) to deal with the two subproblems individually, referred to as PPO-Dual. In particular, given the UAV's position and SN association, the optimal phase shifts of the IRS is estimated using PPO based on the partial channel state information (CSI) obtained by sending pilot signals through some active elements mounted on the IRS. Based on the well trained IRS's phase estimation strategy, the UAV's online data collection scheme is also determined using PPO. Simulation results show that the proposed PPO-Dual algorithm can effectively estimate the IRS's phase shifts and achieve the average AoI performance close to that under perfect CSI conditions.

关键词： Wireless communication Wireless sensor networks Simulation Phase estimation Signal processing algorithms Data collection Autonomous aerial vehicles Trajectory Optimization Surface treatment

来源：评论

学校读者我要写书评

暂无评论

Development of Dynamic Traffic Control Based on Congestion Level Using IoT

Development of Dynamic Traffic Control Based on Congestion L...

引用

International conference on Computer and Communications Technologies (ICCCT)

作者： T. Manju S. Sundar P. Edwin Richard R. Vishnu Vardhan M. Pavithran Dept of Information Technology Sri Sairam Engineering College Chennai India

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

Urban traffic congestion is a growing trend that leads to problems like pollution, prolonged delays, and vital risks, particularly for ambulances and fire engines. Primarily, traditional traffic management systems with fixed time-based traffic signals do not accommodate the dynamic nature of traffic, exacerbating these issues. Our project introduces an intelligent traffic light system powered by IoT sensors and Artificial intelligence algorithms to counter these situations as and when they arise. The system comprises two principal components namely: 1) infrared and radar sensors which keep watch over traffic intensity on various lanes, dynamically altered signal timings for alleviating the jam and 2) paving the way for ambulances by making automatic adjustments of the stream of road traffic to let them travel rapidly and securely. In as far as sensor processing data is involved, microcontrollers like STM32 are employed whilst Python and AI-driven algorithms take the role of decision-making. This is not only a way of alleviating urban transport congestion but also enhances road safety on the network leading towards smart sustainable cities.

关键词： Heuristic algorithms Urban areas Transportation Traffic control Market research sensor systems Road safety Delays Vehicle dynamics intelligent sensors

来源：评论

学校读者我要写书评

暂无评论

Stacking U-Nets in U-shape: Redesigning the information Flow in Model-based networks for MRI Reconstruction

Stacking U-Nets in U-shape: Redesigning the Information Flow...

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Xiaoyu Qiao Weisheng Li Bin Xiao Yuping Huang Lijian Yang Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Cyberspace Big Data Intelligent Security Chongqing University of Posts and Telecommunications Ministry of Education Chongqing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Model-based networks have shown convincing performance in MRI reconstruction. However, the unrolled cascades within the networks are constrained to solely obtain information from the preceding counterpart, resulting in potential error accumulation. Moreover, the linear structure fails to address the challenge of recovering fine-grained details. To tackle these problems, we propose to redesign the information flow in model-based networks. Our method features a large U-shaped network, where the nodes are built with unrolled cascades and U-Net-based regularizers. We design an input-level integration module to help the cascades acquire information from adjacent and skip-connected counterparts, building robust mappings to the target. We further design a coarse-to-fine feature-level integration module, aiming at guiding the network to progressively recover fine details. Intermediate reconstructions produced by subnetworks of different scales are integrated, enabling the extraction of complementary information to enhance the final performance. Compared with cutting-edge methods on different datasets, our method exhibits superior performances.

关键词： Magnetic resonance imaging Stacking Buildings Signal processing Feature extraction Acoustics sensors Data mining Speech processing

来源：评论

学校读者我要写书评

暂无评论

AI Driven Rat Detection for Warehouse

AI Driven Rat Detection for Warehouse

引用

Emerging Smart Computing and Informatics (ESCI), conference on

作者： Ann Vincent Bhavesh Patil Aditya Murbade Hemalata Mote Shruti Mehata Dept. Elec and Telecomm. Engg. Don Bosco Institute of Technology Mumbai Mumbai India BharatGodam Solutions LLP Ahmedabad India

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

The project’s goal is to create a system for controlling insect activity and monitoring of warehouses in sizable grain storage facilities. The idea behind the system uses neural networks, deep learning algorithms, and imagery processing methods to identify, monitor, track, and notify users of the activity of pests, notably rats, in real-time. By using algorithms that use deep learning for real-time object recognition and authentication, rats may be accurately identified. In addition, the sensors augment optical detection by using non-visual methods to detect motion and activity, providing full surveillance regardless of regions that are completely concealed. The system’s network of carefully positioned imaging devices and sensors allows for constant, continuous surveillance of the warehouse ambiance. The system activates and displays an indication once it recognises a rat, and it logs the precise time and place of the event. To ensure prompt action and response, warehouse administrators get updates in real time via email, SMS, or a mobile app. Through the application of artificial intelligence (AI), this initiative seeks to improve the security of food, reduce monetary damage, and revolutionize pest control at storage facilities for grain.

关键词： Deep learning Tracking Surveillance Neural networks Real-time systems sensor systems Optical sensors Object recognition Artificial intelligence intelligent sensors

来源：评论

学校读者我要写书评

暂无评论

A CNN-based Fog Node Data processing Method and Application inWearable Heart Detection Equipment 22

A CNN-based Fog Node Data Processing Method and Application ...

引用

6th International conference on Control Engineering and Artificial Intelligence, CCEAI 2022

作者： Wu, Hailiang Kang, Yuyun Wang, Baiyang Huo, Dongyue Chen, Dongping School of Logistics Linyi University China School of Mechanical Engineering Shandong University China School of Information Science and Engineering Linyi University China

ISBN: (纸本)9781450385916

With the amount increase of sensors and collection data, a large number of low-value data will be directly uploaded to the cloud server without screening in the application process of the Internet of Things, which will waste a lot of network resources. This paper proposes an intelligent processing method of Internet of Things data based on fog computing. Firstly, fog nodes are introduced into the sensor network in the edge of the Internet of Things, and then deep neural network is used as the data processing method in the fog nodes to conduct preliminary classification and screening of the sensor data collected in the edge network. Finally, the processed data is sent to the cloud according to the demand. By comparison, using fog nodes to screen data can greatly reduce the amount of data transmission and meet the needs of data analysis, which is conducive to reducing the cost of the Internet of Things. © 2022 ACM.

关键词： Fog

来源：评论

学校读者我要写书评

暂无评论

Implementation of Yolo-Based Object Detection and sensor Integration Model for Visually Challenged Person

Implementation of Yolo-Based Object Detection and Sensor Int...

引用

Innovative Computing, intelligent Communication and Smart Electrical Systems (ICSES), International conference on

作者： M. Kamarunisha K. Jayasri S. Sharin M. Priyadharshini T. Anusuya R. Malathi Department of Computer Applications Dhanalakshmi Srinivasan College of Arts and Science for Women Autonomous Perambalur

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

It is suggested that visually impaired individuals use an assistive device to receive automatic direction and navigation. The gadget may provide obstacle-free navigation and use real-time image processing to detect impediments. The goal of the strategy is to maximise information flow by completing all activities in real-time and gathering all the information regarding path impediments. The suggested navigation stick is an inexpensive item, obstacle, and obstacle identifier. For safety and navigation, the suggested assistance system for the blind makes use of cutting-edge technology such as tilt and ultrasonic sensors, as well as YOLO(YouOnly Look Once) object recognition. It updates its location via GPS, haptic feedback, and real-time object detection. The user interface is independent and accessible through non-visual means. The suggested work focuses on a multi-label method for detecting items in indoor and outdoor settings utilising vision technology. It improves accuracy and cuts down on recognition time by using classification and clustering techniques.

关键词： YOLO Image resolution Accuracy Navigation Computational modeling Visual impairment sensor systems Real-time systems Object recognition intelligent sensors

来源：评论

学校读者我要写书评

暂无评论

Soldier Surveillance using Wireless sensor Network (SS-WSN)

Soldier Surveillance using Wireless Sensor Network (SS-WSN)

引用

intelligent Algorithms for Computational Intelligence Systems (IACIS), International conference on

作者： Ramachandra A.C Prashantha B Shashanka L.R. Shreyas Nayak H S Jagadeesh Department of EEE Nitte Meenakshi Institute of Technology Bengaluru India Department of Information Science and Technology Nitte Meenakshi Institute of Technology Bengaluru India Nitte Meenakshi Institute of Technology Bengaluru India Department of ECE Nitte Meenakshi Institute of Technology Bengaluru India Department of ECE Atria Institute of Technology Bengaluru India

ISBN: (数字)9798350360660

ISBN: (纸本)9798350360677

In today’s world, warfare or the military is playing a major role in a country’s safety. Monitoring of the soldier’s safety and risk management plays a vital role. At present only wireless communication is used to get connected, the problem is if the solder is not in a condition to talk then the communication is lost. With the advancement of technology, the concept of monitoring soldier health in real-time has gained significant attention to ensure their well-being and performance on the battlefield. This work proposes a Soldier Surveillance using Wireless sensor Network (SS-WSN) to continuously monitor vital physiological parameters of soldiers during mission operations. The system integrates sensors to measure parameters such as heart rate, altitude, gas concentration around the soldier and temperature. These sensors are wirelessly connected to a central monitoring unit which collects, processes, and analyzes the data in real-time. This helps to minimize the time, and the rescue operation, this system allows the military to keep track of the whereabouts and monitor the well-being of their personnel. The proposed system is designed using wireless communication technology Wi-Fi or Bluetooth to keep the subjected connected and exchange information. The Efficiency of the system is 98% and better compared to existing. It is tested in normal conditions and may vary in very cold conditions.

关键词： Temperature sensors Temperature measurement Wireless communication Wireless sensor networks Surveillance Real-time systems sensors Safety Biomedical monitoring Wireless fidelity

来源：评论

学校读者我要写书评

暂无评论

intelligent Route Planning Algorithm based on Genetic Neural Network 22

Intelligent Route Planning Algorithm based on Genetic Neural...

引用

3rd Asia-Pacific conference on Image processing, Electronics and Computers, IPEC 2022

作者： Ning, Yihan Yang, Chongjun Wuhan Business University Wuhan430056 China

ISBN: (纸本)9781450395786

With the development of modern industry towards large-scale and integration, the production process is becoming more and more complex. The process is seriously nonlinear, time-varying, uncertain and the strong combination of variables, which makes many systems lack accurate mathematical description and difficult to analyze and control with traditional theoretical methods. Therefore, it is necessary to study new intelligent control strategies. Real-time and efficient solution of the optimal path in a large-scale road network is a research difficulty in the field of dynamic path induction. During path planning, the robot's own sensors are required to continuously collect and analyze environmental data, so that the robot can find the target point and update it continuously path. Aiming at the shortcomings of the basic GA, such as low efficiency, when calculating the optimization problems of large-scale networks. In this paper, an intelligent route planning algorithm based on genetic neural network is proposed. The environmental information is obtained by five sensors loaded on the front end. The obtained obstacle, pose and target information are used as the input of neural network, and then the weights of neural network are trained and adjusted by GA. Finally, the output of neural network after training and adjustment is used as the driving control force of robot. On this basis, referring to some conclusions of fixture verification, the stability and deformation characteristics of the workpiece are simulated through some parameters, and the GA is used for combinatorial optimization to determine the optimal positioning point. The algorithm proposed in this paper has the advantages of simple calculation and fast convergence, can avoid some local extremum, and the planned collision free path reaches the shortest collision free path. Finally, through the experimental simulation of the algorithm, the results show that the proposed intelligent route planning algorithm based

关键词： Combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

Enhancing Performances of Deep Neural networks with Ensemble Learning Methods for Complex Human Activity Recognition Using Wearable sensors 10

Enhancing Performances of Deep Neural Networks with Ensemble...

引用

10th International conference on Digital Arts, Media and Technology and 8th ECTI Northern Section conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI DAMT and NCON 2025

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

ISBN: (纸本)9798331543273

sensor-based human activity recognition (HAR) is a widely explored research area focused on identifying human behaviors by analyzing sensor-generated data, particularly one-dimensional time series signals. Such HAR systems have many real-world applications, including elderly health monitoring and athlete performance evaluation. This paper presents Ens-DeepNet, a novel ensemble learning approach designed for recognizing complex human activities using data from wearable sensors. While deep neural networks have proven effective for HAR tasks, their performance can be further improved through ensemble strategies. To this end, we propose an ensemble architecture that combines five distinct deep learning models - convolutional neural network (CNN), long short-term memory (LSTM), bidirectional LSTM (BiLSTM), gated recurrent unit (GRU), and bidirectional GRU (BiGRU). These models are integrated using a majority voting scheme to boost classification accuracy. The proposed method is evaluated using the UTwente dataset, which includes sensor data collected from ten individuals via tri-axial accelerometers and gyroscopes. Experimental findings demonstrate that the ensemble model achieves an impressive accuracy of 99.28%, surpassing the performance of each standalone model, whose accuracies range from 92.77%to 97.34%. This performance gain is particularly notable in recognizing complex activities such as eating, drinking coffee, smoking, and conversing. © 2025 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

On-Chip Implementation of intelligent Signal Recognition in Fiber-Optic DAS

On-Chip Implementation of Intelligent Signal Recognition in ...

引用

International conference on Optical Communications and networks (ICOCN)

作者： Yiyu Liu Yongxin Wu Xiben Jiao Huijuan Wu Yunjiang Rao Key Laboratory of Optical Fiber Sensing and Communications (Ministry of Education) School of Information and Communication Engineering University of Electronic Science & Technology of China Chengdu Sichuan China

ISBN: (数字)9798350367652

ISBN: (纸本)9798350367669

The accelerator implementation method of intelligent signal recognition is proposed for fiber-optic DAS in this paper. The processing time can achieve at 0.398ms on the FPGA platform of ZCU102 for the signal at each fiber sensing node, which is equivalent to 0.7212s for a total fiber length of 18.7km with a spatial resolution of 10.32m. This processing time is much faster than 3.47ms and 6.288s on the desktop workstation (CPU:13400, Memory:16G) for one node and the whole monitoring line respectively. With this significant increase in the processing speed, the recognition accuracy for four types of real field events can achieve at as high as 97.37% on FPGA, which is only 0.81 % lower than that on CPU, while the maximum power consumption is only 25W, which is just 1/6 of the typical operating power for CPU. It provides a fast, accurate and power efficient on-chip processing solution for various safety monitoring applications of DAS.

关键词： Accuracy Power demand Optical fiber networks System-on-chip Workstations sensors Safety

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 << < 90 91 92 93 94 95 96 97 98 99 > >>

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：