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

10,830 篇 会议
2,079 篇 期刊文献
67 册 图书

馆藏范围

12,976 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

7,997 篇 工学
- 4,801 篇 计算机科学与技术...
- 4,037 篇 软件工程
- 2,152 篇 信息与通信工程
- 1,725 篇 控制科学与工程
- 1,391 篇 电气工程
- 1,391 篇 电子科学与技术（可...
- 740 篇 机械工程
- 734 篇 生物工程
- 665 篇 生物医学工程（可授...
- 609 篇 光学工程
- 607 篇 仪器科学与技术
- 525 篇 动力工程及工程热...
- 463 篇 化学工程与技术
- 349 篇 交通运输工程
- 314 篇 安全科学与工程
- 301 篇 建筑学
- 281 篇 材料科学与工程（可...
- 273 篇 土木工程
4,293 篇 理学
- 2,275 篇 数学
- 1,413 篇 物理学
- 782 篇 生物学
- 696 篇 统计学（可授理学、...
- 602 篇 系统科学
- 440 篇 化学
1,770 篇 管理学
- 1,207 篇 管理科学与工程(可...
- 651 篇 图书情报与档案管...
- 573 篇 工商管理
536 篇 医学
- 454 篇 临床医学
- 420 篇 基础医学(可授医学...
- 278 篇 药学(可授医学、理...
278 篇 法学
211 篇 农学
209 篇 经济学
123 篇 教育学
53 篇 文学
32 篇 军事学
12 篇 艺术学
2 篇 哲学
1 篇 历史学

主题

263 篇 feature extracti...
246 篇 accuracy
200 篇 computational mo...
197 篇 deep learning
178 篇 predictive model...
177 篇 real-time system...
155 篇 support vector m...
154 篇 optimization
144 篇 neural networks
136 篇 machine learning
130 篇 wireless communi...
126 篇 internet of thin...
126 篇 monitoring
114 篇 reliability
114 篇 training
110 篇 wireless sensor ...
104 篇 visualization
103 篇 quality of servi...
101 篇 data mining
97 篇 signal to noise ...

机构

71 篇 dept. of informa...
52 篇 dept. of compute...
51 篇 dept. of electri...
51 篇 dept. of electro...
47 篇 dept. of informa...
39 篇 university of th...
36 篇 dept. of electri...
31 篇 dept. of informa...
27 篇 dept. of control...
26 篇 lovely professio...
26 篇 dept. of informa...
25 篇 dept. of electri...
24 篇 school of automa...
22 篇 institute of inf...
21 篇 ieee
19 篇 delft center for...
19 篇 dept. of control...
18 篇 chitkara univers...
17 篇 dept. of materia...
17 篇 dept. of compute...

作者

26 篇 nasmin jiwani
26 篇 ketan gupta
26 篇 magno michele
26 篇 fotiadis dimitri...
25 篇 jiwani nasmin
21 篇 bin zou
19 篇 logeshwaran j.
18 篇 ye zhang
17 篇 widyawan
16 篇 lo hoi-kwong
16 篇 tom oomen
15 篇 balázs benyó
15 篇 oomen tom
14 篇 chen yen-lin
14 篇 hongyi yu
13 篇 zhang ye
13 篇 loeliger hans-an...
12 篇 horng shi-jinn
12 篇 han ji-hoon
12 篇 masaki yamakita

语言

12,336 篇 英文
269 篇 其他
216 篇 中文
81 篇 日文
81 篇 朝鲜文
1 篇 斯洛文尼亚文

检索条件"机构=Dept. of Control Engineering and Information Technology"

共 12976 条记录，以下是321-330 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：

A Comparative Study in Pedestrian Detection for Autonomous Driving Systems

A Comparative Study in Pedestrian Detection for Autonomous D...

引用

2022 OPJU International technology Conference on Emerging Technologies for Sustainable Development, OTCON 2022

作者： Ramchandani, Monica Sahu, Satya Prakash Dewangan, Deepak Kumar National Institute of Technology Dept. of Information Technology Raipur India Tiet Dept. of Computer Science and Engineering Punjab India

ISBN: (纸本)9781665492942

technology development has altered how people live. Intelligent vehicles are being developed as a result of technological advancements in the automobile industry. Pedestrians are the most vulnerable road users, accounting for more than half of all traffic fatalities. Thus, the key thing to take into account is pedestrian detection. In order to safeguard both drivers and pedestrians, an intelligent vehicle system can detect pedestrians in front of moving vehicles and either loudly warn the driver of the risk or automatically slow down the vehicle. The purpose of this study is to examine different sensor-based pedestrian detection techniques, weigh their benefits and drawbacks, and determine how they may be enhanced to make them more useful in real-world situations. Radar, vision sensors, and LiDAR are the mechanisms employed. This study analyses the datasets utilized in the research and identifies numerous state-of-the-art methodologies. © 2023 IEEE.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

information technology Risk Management Model for Remote control Vehicles 14

Information Technology Risk Management Model for Remote Cont...

引用

14th International Conference on information and Knowledge technology, IKT 2023

作者： Naji, Hamid Reza Ayati, Aref Graduate University of Advanced Technology Dept. of Computer Engineering and Information Technology Kerman Iran

ISBN: (纸本)9798350349412

This paper presents a lightweight and quick IT risk management model for Remote control Vehicles (RCVs). The increasing use of RCVs in many fields and the existence of different threats are the main reasons for having an efficient risk management method in this field. This paper will cover the information technology risks based on a continuous, iterative, and cyclic flow. This structure is adaptable to agile methods and decreases the chance of losing data, failing any equipment or system, and losing the reputation of the enterprise. Our risk management model is based on qualitative measures and can cover most IT-based risks in this area. © 2023 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Agri-Guard: IoT-Based Network for Agricultural Health Monitoring with Fault Detection 10

Agri-Guard: IoT-Based Network for Agricultural Health Monito...

引用

10th International Conference on Internet of Things, Big Data and Security, IoTBDS 2025

作者： Singh, Kushagra Momin, Kafil Abbas Nishal, M. Sultania, Chinmay Rao, Madhav Dept. of Electronics and Communication Engineering International Institute of Information Technology Bangalore Karnataka India

ISBN: (纸本)9789897587504

Agricultural sector is increasingly adopting advanced technologies to enhance crop productivity and sustainability. Precision agriculture leverages IoT devices, sensors, and data analytics to monitor and manage various environmental parameters, addressing challenges such as global food demand, climate change, and resource optimization. Previous research has demonstrated the efficacy of wireless sensor networks (WSNs) and remote sensing technologies in improving irrigation efficiency and early disease detection. However, these systems often assume that all components continue to operate, thereby offering an incomplete view. This study presents an advanced agricultural monitoring system referred to as Agri-Guard that integrates a wide array of sensors to measure temperature, humidity, soil moisture, and gases like CO2, methane and ammonia. By utilizing an ESP8266 microcontroller and IoT connectivity, the system ensures seamless data transmission and real-time processing. Additionally, a centralized hub, equipped with a Raspberry Pi 5 and a thermal camera, enhances the detection of crop anomalies, and an inoperative sensor hub. The sensor hub in the form of a cone is optimally designed to detect environmental parameters besides being rainproof. The proposed Agri-Gaurd setup clearly demonstrated the lack of manure and water from the sensors’ data, whereas thermal imaging showcased the classification of 92.7% between a dead and alive plant. The anomaly between an operating and non-operating Agri-cone was found to be in complete agreement (100%). The proposed system represents a significant improvement over existing solutions, empowering farmers with precise data and faulty hub detection, leading to quick recovery and more sustainable farming practices. Copyright © 2025 by SCITEPRESS - Science and technology Publications, Lda.

关键词： Agricultural robots

来源：评论

学校读者我要写书评

暂无评论

Partial Discharge Classification With 1D Convolutional Neural Network 14

Partial Discharge Classification With 1D Convolutional Neura...

引用

14th International Conference on the Properties and Applications of Dielectric Materials, ICPADM 2024

作者： Cheypoca, Thepjit Promphanich, Wiboon Thway, Aung Ye Hankae, Angelina Phimpissada Jeenmuang, Siwakorn Pattanadech, Norasage School of Engineering King Mongkut's Institute of Technology Ladkrabang Instrumentation and Control Engineering Dept. Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Computer Engineering Dept. Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Electrical Engineering Dept. Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Mechatronics Engineering Dept. Bangkok Thailand

ISBN: (纸本)9798350374605

This paper introduces a novel approach for classifying with the 1D Convolutional Neural Network model for partial discharge patterns, that consists of corona discharge, surface discharge and internal discharge. The PD measuring circuit suggested in IEC 60270:2000 is used to record Partial discharge signals. Independent parameters such as phase and charge of PD patterns were recorded. The Artificial Neural Network for the classification model was constructed. Moreover, 2×1D CNN feature extraction was utilized to reduce the curse of dimensionality in the dense layer of the proposed PD classification model. 80% of the recorded data will be used as a training data and 20% recorded data was used for testing of the classification models. Impacts of neuron numbers and network architecture on the PD classification performance will be observed. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Advancements in EEG-Based Emotion and Consciousness Recognition: Techniques, Challenges, and Innovations 1

Advancements in EEG-Based Emotion and Consciousness Recognit...

引用

1st International Conference on Innovations in Communications, Electrical and Computer engineering, ICICEC 2024

作者： Jadekar, Ranjana B. Poornima, B. Gowramma, B.H. Puneeth, S.P. Visvesvaraya Technological University Bapuji Institute of Engineering and Technology Dept. of Computer Science and Engineering Karnataka Belagavi India Visvesvaraya Technological University Bapuji Institute of Engineering and Technology Dept. of Information Science and Engineering Karnataka Belagavi India

ISBN: (纸本)9798350376517

This study delves into the application of Electroencephalogram (EEG)-based techniques for emotion and consciousness recognition, focusing on disorders of consciousness (DOC). By evaluating existing approaches in terms of techniques, methodologies, and accuracies, the research highlights the efficacy of both machine learning and deep learning models. The key challenges were identified such as noise removal due to artifacts and variability in patient responses. The findings underscore the potential of advanced computational methods in enhancing the reliability and precision of EEG-based diagnostic tools, paving the way for better clinical interventions and deeper understanding of human emotions. Also, the findings show that using deep learning, the current works have achieved better results for identification of emotion. © 2024 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

A Multistage Cascaded Neural Network Model to Identify the Severity of Epileptic Attack

A Multistage Cascaded Neural Network Model to Identify the S...

引用

2024 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, SPICES 2024

作者： Simon, Martha Thampi, Lidiya Lilly Dept. of Computer Science College of Engineering Trivandrum India Indian Institute of Information Technology Kottayam Dept. of Computer Science Kottayam India

ISBN: (纸本)9798350376135

Epilepsy is a neurological disorder characterized by recurrent seizures, impacting the quality of life for millions of individuals worldwide. Timely and accurate detection of epileptic seizures is crucial for proper diagnosis and effective treatment. Electroencephalogram (EEG) signals provide vital information about brain activity and serve as a valuable tool for epilepsy detection. The methodology opted for this study was an enhanced multilayer feed forward neural network for automatic detection of epilepsy from EEG signals and hence predicting the severity. The authors build a multistage cascaded neural network model for achieving the same. Initially a Simple Artificial Neural Network (SimpleANN) is designed to classify EEG segments into seizure, healthy and interictal. Later a Multilayer Feed Forward Neural Network (MFFNN) is employed for detecting the severity of epileptic patients and hence can be classified into primary and secondary stages. The experimental results showed that the proposed SimpleANN classifier had provided noticeable results, and outperforms all tested classifiers. The study involves the collection of EEG data from a diverse group of patients, including those with epilepsy and healthy individuals. This automated epilepsy identifying system passes through different stages including decomposition, feature extraction for achieving a better performance model. The proposed system was tested and compared with SVM, KNN, MLP and Decision Tree under different measurement metrics. ANN has managed to give an accuracy of 80 - 90% which is significantly higher as compared to other machine learning models. The proposed work can automatically learn complex patterns from EEG data provides an advantage in identifying subtle seizure related features that may not be evident through manual analysis. Furthermore, the model offers real-time capabilities, making it suitable for continuous monitoring of patients at risk of seizures. © 2024 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Enhancing Early Detection of Pancreatic Cancer: A Machine Learning Approach with Explainable AI Insights

Enhancing Early Detection of Pancreatic Cancer: A Machine Le...

引用

2024 IEEE International Conference on Computer Vision and Machine Intelligence, CVMI 2024

作者： Pattanashetti, Neeraj V Mayur, R. Prakash, Adarsh Adiga, Tryambaka B Kodipalli, Ashwini Rao, Trupthi Global Academy of Technology Dept. of Computer Science & Engineering Karnataka Bangalore India Global Academy of Technology Dept. of Information Science & Engineering Karnataka Bangalore India Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bangalore India

ISBN: (纸本)9798350376876

Among the most deadly and complex illnesses in the world, pancreatic cancer is typified by its early asymptomatic stage and subsequent discovery of the disease when it has progressed to an advanced stage. Getting the patients in a correct treatment path at the earliest point is important for suitable intervention and patient outcomes in the long run. We utilized advanced algorithms and model prediction techniques includes, feature extraction, hyperparameter tuning and explainability methods which aims to enhance both the comprehension and predictive accuracy of models employed. The goal is to assess patient health status and diagnose pancreatic diseases (cancer vs. non-cancer) by developing a learning algorithm. We obtained a dataset containing demographic information and urine biomarkers to start the investigation. First stage of our analysis employs a single classifier and later we apply bagging and boosting algorithms to achieve ensemble models. Hyperparameter fine-tuning has got a positive outcome, which has Gradient Boosting and Cat Boosting as its top performing models. The ensemble model produced excellent results (92.02 %), demonstrating the usefulness of the suggested approach. LIME and SHAP techniques play the key role in model outcome interpretability providing an insight of algorithmic decision-making process. Such a wide range of combinations of biomarkers have a potential of pancreatic cancer detection in early stages and thus will help shape diagnostics strategies in near future. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Efficient Development of Gesture Language Translation System using CNN 15

Efficient Development of Gesture Language Translation System...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Mukhedkar, Moresh Deshmukh, Dilip P. Chaudhari, Om Shinde, Harshala Shinde, Amruta Kadam, Abhijeet D.Y.Patil University School of Engineering & Technology Dept. of Computer Engineering Ambi Pune India D.Y.Patil University School of Engineering & Technology Dept. of Mechanical Engineering Ambi Pune India D.Y.Patil University School of Engineering & Technology Dept. of Information Technology Ambi Pune India

ISBN: (纸本)9798350370249

Gesture Language Translation System (GLTS) is an interdisciplinary research field that intersects computer vision, machine learning, also human-machine interaction. This study offers a extensive exploration regarding current technologies, methodologies, and challenges in GLTS. The paper explores the evolution of sign communication recognition systems and their applications across diverse domains, such as human-computer interaction, virtual reality, and healthcare. Particular emphasis is given to sign communication translation, an emerging concept facilitating the translation of gestures into meaningful language, thereby enabling more intuitive communication. Challenges associated with translating gestures into language are discussed, and potential solutions are explored to enhance the accuracy and efficiency of GLTS. The research underscores the real-world impact of GLTS, showcasing its potential to revolutionize human-machine interactions across various contexts. The inclusion of case studies and examples of successful GLTS implementations provides practical insights and lessons learned from these instances. The methodology section details the research approach, encompassing the dataset, tools, and algorithms utilized for evaluating GLTS system effectiveness. The presentation and analysis of experimental results, along with relevant metrics and performance evaluations, form a critical component of this study. The discussion part analyses the results in light of the body of previous research, considers field implications, and suggests possible directions for further study and advancement. © 2024 IEEE.

关键词： Machine translation

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based Force-Sensor-Like Reaction Force Observer for Realization of Intelligent Force Sensing

Deep Learning Based Force-Sensor-Like Reaction Force Observe...

引用

18th IEEE International Conference on Advanced Motion control, AMC 2024

作者： Phuong, Thao Tran Ohishi, Kiyoshi Yokokura, Yuki Miyazaki, Toshimasa Nagaoka University of Technology Dept. of Electrical Electronics and Information Engineering Nagaoka Japan

ISBN: (纸本)9798350342819

This paper proposes a new approach to realize a force-sensor-like reaction force observer based on deep learning. The reaction force observer is designed by a long short-term memory deep neural network model to achieve the intelligent force sensation capable of imitating a force sensor's measuring performance with high accuracy. To reproduce the reaction force similar to that measured by a force sensor, the deep neural network is trained by force information provided by a force sensor, motor position, and motor current reference. Practical implementation of the proposed reaction force observer only employs position and current reference information of the motor, without using a force sensor. The effectiveness of the proposed method is validated by numerical simulation results. The numerical simulation results verify that the proposed deep learning based reaction force observer generates the reaction force information highly coincident to that provided by the force sensor. The accuracy of reaction force estimation of the proposed method is superior to the conventional sensorless force observer based on disturbance observer, especially during transient responses. © 2024 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Passive FSR Development for Cars Detection Crossing a Railroad 3

Passive FSR Development for Cars Detection Crossing a Railro...

引用

3rd International Conference on Green Communication, Network, and Internet of Things, CNIoT 2023

作者： Wang, Rutao Dept. Electronic Information Engineering Zhonghuan Information College Tianjin University of Technology Tianjin China

ISBN: (纸本)9781510668867

Forward Scatter Radar is a cutting-edge technical Radar to detect target across the baseline. In the first part, simply introduce some background of FSR application area. According to the calculation of the power budget, we can verify the data of the FSR system. Then it is the most crucial part, target signature, after simulation in Matlab we can get some figures regarding output, after low-pass filter and matched filter figures. © 2023 SPIE.

关键词： Matched filters

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 << < 29 30 31 32 33 34 35 36 37 38 > >>

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：