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

63,045 篇 会议
448 册 图书
409 篇 期刊文献
1 篇 学位论文

馆藏范围

63,902 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

35,068 篇 工学
- 21,475 篇 计算机科学与技术...
- 14,439 篇 控制科学与工程
- 12,494 篇 软件工程
- 9,191 篇 信息与通信工程
- 8,858 篇 电气工程
- 3,783 篇 机械工程
- 2,904 篇 电子科学与技术（可...
- 2,285 篇 仪器科学与技术
- 1,948 篇 动力工程及工程热...
- 1,479 篇 生物工程
- 1,334 篇 交通运输工程
- 1,260 篇 生物医学工程（可授...
- 1,144 篇 安全科学与工程
- 978 篇 光学工程
- 873 篇 建筑学
- 846 篇 化学工程与技术
- 807 篇 网络空间安全
- 803 篇 土木工程
9,327 篇 理学
- 4,611 篇 数学
- 2,470 篇 物理学
- 1,895 篇 系统科学
- 1,642 篇 生物学
- 1,122 篇 统计学（可授理学、...
- 771 篇 化学
6,315 篇 管理学
- 5,138 篇 管理科学与工程(可...
- 1,948 篇 工商管理
- 1,461 篇 图书情报与档案管...
1,182 篇 医学
- 983 篇 临床医学
- 848 篇 基础医学(可授医学...
839 篇 法学
792 篇 经济学
- 788 篇 应用经济学
477 篇 农学
319 篇 教育学
221 篇 文学
161 篇 军事学
63 篇 艺术学
11 篇 历史学
8 篇 哲学

主题

3,732 篇 control systems
3,434 篇 automation
2,953 篇 communication sy...
2,596 篇 cloud computing
2,538 篇 wireless communi...
2,275 篇 protocols
1,943 篇 wireless sensor ...
1,746 篇 mobile communica...
1,614 篇 computational mo...
1,460 篇 real-time system...
1,426 篇 monitoring
1,416 篇 computer archite...
1,334 篇 internet of thin...
1,275 篇 process control
1,163 篇 automatic contro...
1,135 篇 mobile computing
1,069 篇 traffic control
974 篇 hardware
967 篇 bandwidth
916 篇 security

机构

114 篇 school of automa...
77 篇 school of mechat...
75 篇 shenyang institu...
60 篇 department of au...
59 篇 school of electr...
50 篇 maharishi school...
44 篇 jiangsu automati...
41 篇 karnataka bangal...
36 篇 department of co...
36 篇 university of ch...
33 篇 college of medic...
31 篇 state key labora...
31 篇 school of inform...
30 篇 school of automa...
30 篇 school of automa...
29 篇 school of electr...
28 篇 china electric p...
27 篇 school of inform...
27 篇 department of co...
27 篇 lovely professio...

作者

56 篇 singh bhim
45 篇 li li
38 篇 wang lei
32 篇 li yang
30 篇 jian wang
27 篇 jun wang
27 篇 yin zhenyu
26 篇 wang ping
24 篇 lei wang
24 篇 zhang lei
24 篇 wang jing
24 篇 valeriy vyatkin
22 篇 li peng
22 篇 yu wang
22 篇 yang jun
21 篇 alois zoitl
21 篇 li xin
19 篇 kastner wolfgang
18 篇 jun zhang
18 篇 jing zhang

语言

61,682 篇 英文
1,528 篇 其他
759 篇 中文
11 篇 西班牙文
11 篇 俄文
2 篇 葡萄牙文
1 篇 法文
1 篇 土耳其文

检索条件"任意字段=International Conference on Computing Communication Control and Automation"

共 63903 条记录，以下是991-1000 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：

AI-ML Trained Object Recognition System Development using Google Teachable Machine with the Help of Data Sciences 15

AI-ML Trained Object Recognition System Development using Go...

引用

15th international conference on Advances in computing, control, and Telecommunication Technologies, ACT 2024

作者： Prasad, Rajneesh Pavithra, G. Manjunath, T.C. Department of Electronics & Communication Engineering Dayananda Sagar College of Engineering Karnataka Bangalore560111 India

ISBN: (纸本)9798331300579

Object recognition is a crucial task in computer vision and artificial intelligence, as it plays a vital role in many applications such as autonomous vehicles, surveillance systems, and *** this paper, we present an overview of AI Trained object recognition using Google Teachable *** Teachable Machine is a web-based platform that allows users to train machine learning models without any coding or programming *** explore the steps involved in training an object recognition model using Google Teachable Machine and evaluate the performance of the model on a real-world *** results show that Google Teachable Machine is a powerful and user-friendly tool for training object recognition models with high *** research focuses on the development of an AI-ML trained object recognition system using Google Teachable Machine, enhanced by data science *** objective is to create a robust and efficient system capable of accurately identifying and classifying various objects in *** the user-friendly interface of Google Teachable Machine, the system is trained with diverse datasets, incorporating advanced machine learning algorithms and data preprocessing *** approach ensures high accuracy and reliability in object recognition *** integration of data science principles allows for thorough analysis and optimization of the training data, improving the system's performance and *** resulting system demonstrates significant potential for applications in areas such as security, automation, and augmented reality, showcasing the synergy between AI, machine learning, and data sciences in solving complex recognition problems. © Grenze Scientific Society, 2024.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

AQI Prediction Using Human-AI Teaming 2

AQI Prediction Using Human-AI Teaming

引用

2nd IEEE international conference on IoT, communication and automation Technology, ICICAT 2024

作者： Jha, Abhinav Gupta, Harshit Sandhia, G.K. Srm Institute of Science and Technology School of Computing Chennai India

ISBN: (纸本)9798350368109

The paper aims to enhance the prediction of the Air Quality Index (AQI) by incorporating human-AI interaction in conjunction with Random Forest Regression (RFR). Although ML techniques have been applied in PA, these methods are highly susceptible to the complexity of variables in domains like air quality. To tackle this problem, the approach proposed in this paper relies on the Human-In-the-Loop approach where the confidence levels of the ML predictions are evaluated in conjunction with their accuracy. In situations where the output of the ML model is below a certain dynamic value, which is an indication that the model is not certain about the next course of action, the system reroutes the control back to a Human Expert for manual intervention. This approach is beneficial as it is more accurate than the base model when no human input is required in the algorithm's prediction process. In addition, it also opens channels for feedback where the base model can improve itself over time through learning and modification. In the present work, we are concerned with Using a Historical Air Pollution Dataset for Oragadam, Tamil Nadu and we are particularly focusing on the year 2023. This choice is made based on the Random Forest regression's ability to provide more stability and better capture of the non-linear nature of the data inherent in air quality. Our approach aims to address the weakness of purely automated prediction systems while addressing the strong points of both human knowledge and computational modeling to improve the accuracy of the AQI forecast. This study provides value to the enhancement of the field of collaboration between Human and Artificial Intelligence in environmental prediction with the prospect of enhancing the health of the public and the environment. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Accurate and Optimized Labelling of Fashion Products Through Attention Based Spiking Neural Networks 10

Accurate and Optimized Labelling of Fashion Products Through...

引用

10th international conference on Advanced computing and communication Systems, ICACCS 2024

作者： Vithyatharshana, N. Thrinayani, Yedhoti Kulkarni, Yogeshwar Nitin Singh, Rimjhim Padam Kanchan, Sneha Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Universiti Tunku Abdul Rahman Department of Internet Engineering and Computer science Malaysia

ISBN: (纸本)9798350384369

automation of garment classification has become the backbone of e-commerce, influencing product search, personalization, and customer experience. This paper uses the Fashion MNIST dataset, a rich collection of clothing images to investigate the potential of Spiking Neural Networks (SNNs) for accurate and efficient classification. SNNs are an excellent choice for widespread usage and real-world integration due to their low power consumption and biomimicry. With the intention of revolutionizing product search, personalization, and customer experience, SNNs are made to address style differences, perspectives, and illumination. In order to fully utilize Fashion MNIST, this paper suggests strategic improvements to the SNN architecture. By addressing key challenges and introducing novel optimizations, our research contributes to a more robust and intelligent future for automated fashion product labelling. An SNN model with 93.6% accuracy has been developed as the base model for all the applications for the same. This data-driven approach leads the way to flawless product searches, highly customized recommendations, and a more intelligent fashion technology in future. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Face Detection and Recognition Based Intelligence Surveillance Robot for Attendance System 2

Face Detection and Recognition Based Intelligence Surveillan...

引用

2nd international conference on Recent Trends in Microelectronics, automation, computing, and communications Systems, ICMACC 2024

作者： Sowjanya, G. Durga Rajunaik, M. Nitya Pushkala, V. MLR Institute of Technology Department of Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9798350366570

Proposed paper implements face detection and recognition based video surveillance robot model for attendance system. Proposed paper uses approach that detects and recognizes individual information from predefined database using Haar detection within Wi-Fi connectivity. Proposed paper implements a robot using Raspberry Pi controller and web camera for face detection and face recognition. It uses OpenCV libraries for python and database management system. Proposed method can replace old method of using passwords and minimizes real time human errors. Proposed paper implements robot for moving to different places to detect and recognizes faces in any background. Proposed system is tested on various datasets with various backgrounds and results will validate the accuracy of face recognition method. With its faster and authentic performance, it is suitable for applications of automation, educational institutions, industrial applications etc. © 2024 IEEE.

关键词： Wi-Fi

来源：评论

学校读者我要写书评

暂无评论

PyAIM: Pynq-Based Scalable Analog In-Memory computing Prototyping Platform 6

PyAIM: Pynq-Based Scalable Analog In-Memory Computing Protot...

引用

6th international conference on AI Circuits and Systems (AICAS)

作者： Yu, Minsang Hong, Minuk Lee, Sugil Kim, Seungsu Lee, Jongeun Ulsan Natl Inst Sci & Technol UNIST Dept Elect Engn Ulsan South Korea Ulsan Natl Inst Sci & Technol UNIST Grad Sch Ulsan South Korea

ISBN: (纸本)9798350383638;9798350383645

Analog in-memory computing (IMC) has become increasingly popular along with the success of AI applications, especially in highly constrained environments such as IoT devices. However, many unique challenges of analog IMC including variability, faults, noise, endurance, programming disturbance, etc. make validation by hardware prototyping highly desirable. In this paper we present a reusable, extensible, and scalable prototyping platform called PyAIM, where several analog IMC devices can be connected with one another as well as with digital processors via digital interfaces and a communication network. We use a number of Pynq boards to make use of their build-in Python support and affordability as well as their decent CPUs to run some software tasks other than MVM kernels. We overcome the timing control and communication management issues by extending Python with custom C functions, while maintaining convenience of Python. We also demonstrate a high-throughput network inference system as an example of PyAIM, using multiple ReRAM chips with compute-communication pipelining.

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

IoT Home control an Android Application for Appliance Management 15

IoT Home Control an Android Application for Appliance Manage...

引用

15th international conference on Advances in computing, control, and Telecommunication Technologies, ACT 2024

作者： Rao, M.S.P.Durga Harshitha, M. Kumar, V.N.V.Rithvik Harika, A.Sai Harika, B.Sai Madanapalle Institute of Technology & Science Department of Computer Science & Engineering Annamayya Dist Andhra Pradesh Madanapalle517326 India

ISBN: (纸本)9798331300579

This paper is mainly focusing on building an automated home for a small family in low cost *** Internet of things has gained much popularity due to easy connection establishment between electrical appliances, which makes our lives easy and helps in many ways such as reducing power consumption by automating devices, providing *** product is mainly designed for bachelors who live by *** study suggests a low-cost smart home automation solution that uses Bluetooth to control using an Android-based application, devices may be controlled remotely via an Arduino Uno microcontroller, Bluetooth, Wi-Fi, and many sensors, including an LDR, an LM-35 temperature sensor, and a smoke *** a keypad-based security has been provided to open the *** proposed system can help us to efficiently control home appliances using Bluetooth and android application. © Grenze Scientific Society, 2024.

关键词： Microcontrollers

来源：评论

学校读者我要写书评

暂无评论

Multilingual and Mixed-lingual Digit Speech Recognition System for Indian Context 14

Multilingual and Mixed-lingual Digit Speech Recognition Syst...

引用

14th international conference on computing communication and Networking Technologies, ICCCNT 2023

作者： Lalitha, S. Rachana, N. Vinay Bhargav, J. Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350335095

Voice assistants, customer service center automation, and voice-controlled devices all rely heavily on digit speech recognition. For multilingual countries like India, Canada, and Belgium to communicate in more than one language, there is a need for multilingual and mixed-lingual digit speech recognition (DSR) systems. This is the main emphasis of the proposed work. An extensive database of digit utterances from 0 to 9 for various Indian languages of Telugu, Kannada, Hindi & Tamil are self-recorded and used for the experimental work. Following the initial preprocessing by noise elimination from the self-recorded samples, spectrographic characteristics were extracted, and finally, a Convolutional Neural Network (CNN) is applied for classification to identify the digits. The proposed multilingual DSR model resulted in an accuracy of range 89% to 96% and a loss value between 0.144 to 0.878 varying for each language whereas the mixed-lingual DSR model resulted in an accuracy of 92% and a loss value of 0.615. © 2023 IEEE.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Context-aware robot control using gesture episodes

Context-aware robot control using gesture episodes

引用

IEEE international conference on Robotics and automation (ICRA)

作者： Vanc, Petr Behrens, Jan Kristof Stepanova, Karla Czech Tech Univ Czech Inst Informat Robot & Cybernet Prague Czech Republic

ISBN: (纸本)9798350323658

Collaborative robots became a popular tool for increasing productivity in partly automated manufacturing plants. Intuitive robot teaching methods are required to quickly and flexibly adapt the robot programs to new tasks. Gestures have an essential role in human communication. However, in human-robot-interaction scenarios, gesture-based user interfaces are so far used rarely, and if they employ a one-to-one mapping of gestures to robot control variables. In this paper, we propose a method that infers the user's intent based on gesture episodes, the context of the situation, and common sense. The approach is evaluated in a simulated table-top manipulation setting. We conduct deterministic experiments with simulated users and show that the system can even handle the personal preferences of each user.

关键词： User interfaces

来源：评论

学校读者我要写书评

暂无评论

Exploring Innovations in Autonomous Robotics and Mechatronics: Application in Manufacturing and Healthcare 5

Exploring Innovations in Autonomous Robotics and Mechatronic...

引用

5th international conference on Smart Electronics and communication, ICOSEC 2024

作者： Shalini, T.Grace Ganeshabu, L. Chemudugunta, Priyanka Yamsani, Nagendar Kumar, Ch.Ashok Athiraja, A. School of Computing Department of Computational Intelligence Chengalpattu Tamil Nadu Kattankulathur India Rajalakshmi Engineering College Department of Robotics and Automation Thandalam Mevalurkuppam Rajalakshmi Nagar Tamil Nadu Chennai India Karpaga Vinayaga College of Engineering and Technology Department of Robotics and Automation Tamil Nadu Chengalpattu India Sr University Department of School of Computer Science and Artificial Engineering Warangal India Malla Reddy Engineering College Department of Mechanical Engineering Main Campus Hyderabad Telangana Maisammaguda India Telangana Secunderabad India

ISBN: (纸本)9798331504403

Autonomous robotics and mechatronics have drastically changed the manufacturing and healthcare sectors by increasing productivity, precision, and flexibility. This work addresses the pressing need for new methods to advance these sectors by merging intelligent algorithms with autonomous systems. A hybrid strategy was employed, combining Deep Reinforcement Learning (DRL) and Adaptive control Systems (ACS), to develop and optimize robotic operations. Extensive studies were conducted to assess the success of this strategy, which demonstrated a 25% reduction in operating expenses and a 30% increase in production efficiency in manufacturing settings. The method produced a precision rate of about 99% in the healthcare industry, which is significantly better than the 93% average of current systems. It also reduced patient recovery times by an estimated 20%. These results highlight the improved performance and promise of ACS with DRL combination in autonomous robotics, which may have revolutionary implications for the manufacturing and healthcare industries. The success, highlighted by economic and medical benefits, demonstrates the efficacy of our methodology and provides a strong platform for future developments in autonomous robotics and mechatronics. © 2024 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Integrating Deep Learning with the Gemini API for Improved Pest Management 3

Integrating Deep Learning with the Gemini API for Improved P...

引用

3rd international conference on automation, computing and Renewable Systems, ICACRS 2024

作者： Manoj, Milan Ihsan, Faraz Devadath, G.K. Anjali, T. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798331532420

This study uses the Gemini API and deep learning algorithms to provide a novel approach to agricultural pest management. Pests pose serious difficulties to agriculture, thus prompt and precise pest management is crucial. The method combines the ability of the Gemini API to generate pertinent information on pesticides, home remedies, and nearby retail locations with deep learning models for pest classification. By using user-uploaded photos to identify pests, the deep learning model is taught to make recommendations for pest management tactics. The Gemini API also provides location-based information for nearby retailers carrying suggested products, as well as comprehensive details on safe pesticides and DIY cures. The strategy provides a comprehensive solution for agricultural pest management through integration, giving farmers practical insights for efficient pest control and increased crop output. © 2024 IEEE.

关键词： Agricultural Pest Management Agricultural Sustainability Deep Learning Gemini API Home Remedies Location-Based Services Pest Classification Pesticide Information

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 << < 96 97 98 99 100 101 102 103 104 105 > >>

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：