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

632 篇 期刊文献
538 篇 会议

馆藏范围

1,170 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

660 篇 理学
- 543 篇 物理学
- 65 篇 数学
- 38 篇 生物学
- 25 篇 统计学（可授理学、...
- 18 篇 化学
514 篇 工学
- 255 篇 计算机科学与技术...
- 200 篇 软件工程
- 179 篇 核科学与技术
- 99 篇 信息与通信工程
- 81 篇 控制科学与工程
- 69 篇 电气工程
- 54 篇 电子科学与技术（可...
- 40 篇 动力工程及工程热...
- 32 篇 生物医学工程（可授...
- 30 篇 光学工程
- 30 篇 生物工程
- 28 篇 机械工程
- 28 篇 网络空间安全
- 26 篇 安全科学与工程
- 23 篇 仪器科学与技术
- 21 篇 环境科学与工程（可...
- 18 篇 交通运输工程
- 17 篇 石油与天然气工程
- 15 篇 材料科学与工程（可...
93 篇 管理学
- 70 篇 管理科学与工程(可...
- 34 篇 图书情报与档案管...
- 30 篇 工商管理
46 篇 医学
- 40 篇 临床医学
- 36 篇 基础医学(可授医学...
- 24 篇 公共卫生与预防医...
16 篇 法学
11 篇 农学
10 篇 经济学
4 篇 教育学
1 篇 军事学

主题

170 篇 hadron colliders
78 篇 higgs bosons
57 篇 accuracy
49 篇 w & z bosons
43 篇 deep learning
39 篇 relativistic hea...
38 篇 top quark
38 篇 convolutional ne...
34 篇 feature extracti...
33 篇 supersymmetric m...
31 篇 machine learning
30 篇 hadron-hadron sc...
30 篇 quark & gluon je...
26 篇 particle product...
25 篇 training
23 篇 real-time system...
23 篇 extensions of hi...
22 篇 internet of thin...
22 篇 support vector m...
21 篇 hypothetical par...

机构

331 篇 faculty of scien...
331 篇 department for p...
327 篇 kirchhoff-instit...
318 篇 department of ph...
314 篇 department of ph...
304 篇 department of ph...
304 篇 department of ph...
303 篇 yerevan physics ...
299 篇 fakultät für phy...
297 篇 institute of phy...
296 篇 graduate school ...
286 篇 institute of phy...
280 篇 department of ph...
279 篇 instituto de fís...
277 篇 dipartimento di ...
248 篇 department of ph...
245 篇 nikhef national ...
242 篇 irfu cea univers...
228 篇 marian smoluchow...
228 篇 department of ph...

作者

266 篇 c. alexa
264 篇 j. m. izen
262 篇 g. bella
258 篇 j. strandberg
257 篇 d. calvet
257 篇 c. amelung
243 篇 n. orlando
235 篇 y. tayalati
232 篇 s. veneziano
232 篇 g. spigo
232 篇 v. chiarella
225 篇 f. siegert
220 篇 r. ströhmer
218 篇 f. deliot
218 篇 m. rijssenbeek
217 篇 y. abulaiti
216 篇 s. jin
216 篇 g. gaudio
216 篇 s. mohapatra
216 篇 i. van vulpen

语言

1,115 篇 英文
52 篇 其他
4 篇 中文

检索条件"机构=M.Tech Computer Science and Engineering"

共 1170 条记录，以下是111-120 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：

Enhancing Accessibility for Visually Impaired on Integrating Object, Distance and Face Detection 8

Enhancing Accessibility for Visually Impaired on Integrating...

引用

8th International Conference on I-SmAC (IoT in Social, mobile, Analytics and Cloud), I-SmAC 2024

作者： Selvarathi, C. Kannan, R. muthumanickam, K. Pandiaraja, P. Venkateswaran, T.S. Arunraj, R. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Tamilnadu Chennai600 062 India Saranathan College of Engineering Department of Computer Science and Business Systems Tamilnadu Tiruchirapalli620 012 India Kongunadu College of Engineering and Technology Department of Information Technology Tamil Nadu Trichy621215 India M. Kumarasamy College of Engineering Department of Computer Science and Business Systems Tamilnadu Karur639113 India K. Ramakrishnan college of Engineering Department of Information Technology Tamilnadu Samayapuram621112 India

ISBN: (纸本)9798350376425

This research presents a novel assistive technology system designed to empower visually impaired individuals by providing enhanced object, facial, and distance detection capabilities. The system aims to replace traditional electronic travel aids with a more comprehensive and cost-effective solution. By combining object and facial recognition with distance detection, the system enables users to navigate their surroundings independently and confidently. Additionally, the system incorporates threat detection capabilities, alerting users to potential dangers and triggering SOS alerts to contacts or authorities. This innovative system offers a more reliable and accessible solution for visually impaired individuals, providing them with the freedom and independence to navigate their daily lives with greater confidence and security. © 2024 IEEE.

关键词： Assistive technology

来源：评论

学校读者我要写书评

暂无评论

Data Visualization for Corona Patients Globally using Real-Time APIs 2

Data Visualization for Corona Patients Globally using Real-T...

引用

2nd International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023

作者： Durai, S. Iqbal, m. mohamed Kumar, S Niresh Alagappan, Chockalingam Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Avadi Dept. of Cse Chennai India VIT-AP University School of Computer Science and Engineering Amaravati India Dhanalakshmi Srinivasan College of Engineering and Technology Department of Computer Science and Engineering Mamallapuram India M.Kumarasamy College of Engineering Department of Electrical and Electronics Engineering Tamilnadu Karur639113 India

ISBN: (纸本)9781665491990

All the nations' administrative units are concerned about the COVID-19 outbreak in different regions of the world. India is also trying to control the spread of the virus with strict measures and has managed to slow down its growth rate. The administration of each country faces the challenge of maintaining records of corona patients. To address this challenge, this work builds a website from scratch using real-time APIs for data visualization. The website provides information on the number of active cases, death cases, recovery cases, and total cases of COVID-19 patients in each country. The data can be visualized using graphs, making it easier to compare the situation in different countries. The website allows for monitoring which country has a higher number of deaths, patients, favorable recovery rates, and a large number of active cases. The COVID-19 status regarding patients can be analyzed through graphical representation using real-time data. © 2023 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Development of Recommender Systems for Better Services and Products using Data science 4

Development of Recommender Systems for Better Services and P...

引用

4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023

作者： Padmapriya, S. Thamizhamuthu, R. Jagadeesh, S. Kalai Selvi, D.m. Ahsan Shariff, m. Velammal Institute of Technology Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Campus-Chengalpattu Tamil Nadu Chennai India Sridevi Women's Engineering College Department of Electronics and Communication Engineering Telangana Hyderabad India R.M.D. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India M. Tech - Computer Science and Engineering Sri Sairam Engineering College Tamil Nadu Chennai India

ISBN: (纸本)9798350300093

Online social networking and e-commerce are becoming increasingly popular. Recommender Systems (RS) let users find relevant information from several possibilities. Internet applications currently need RS. This technology uses huge data to provide customized suggestions to improve customer happiness. Concerns and ideas help customers choose items. Sentiment Analysis (SA) may increase RS recommendation accuracy by improving user behaviour, views, and responses. RS solves information overload in information retrieval, but data sparsity remains a big problem. SA is notable for reading text and expressing user preferences. It helps E-Commerce to monitor product feedback and to understand what client wants and their preferences. This research presents a hybrid recommendation approach to increase RS accuracy and correctness. The hybrid approach beats standard models in several assessment criteria. modern retailing businesses' e-commerce operations are impossible without RSs. The content-based and context-aware techniques are hybridized for providing promising results. Content-based approaches connect consumers to new things based on prior ratings and activities. Create user profiles and classify it. Knowledge-based algorithms propose customized items with minimal use history. These systems use case-based recommendations or limitations to make recommendations. Finally, ensemble recommender systems combine data source prediction power. © 2023 IEEE.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Facial Emotion Analysis using Deep Learning for Seamless Human-computer Interaction 2

Facial Emotion Analysis using Deep Learning for Seamless Hum...

引用

2nd IEEE International Conference on Networks, multimedia and Information technology, NmITCON 2024

作者： Sangeetha, S. Saini, Poonam Banupriya, R. Srimathi, S. Kiruthiga, S. Aarthi, R. Srm Arts and Science College Department of computer Applications and Technology Kattankulathur Changelpattu603203 India Sir Padampat Singhania University Dept. of Computer Science & Engineering Vil. Bhatewar Teh. Vallabhnagar Rajasthan Udaipur India Pgp College Of Engineering and Technology Dept. of Electrical and Electronics Engineering India Saveetha School of Engineering Simats Department of Bio Technology Tamilnadu Chennai India Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science & Technology School of Computing Department of Computer Science & Engineering Chennai India R.M.D Engineering College Department of Ece India

ISBN: (纸本)9798350372892

HCII, or human-computer intelligent interaction, is a new academic subject that tries to make computer use more intuitive. Some say machines need human-level social abilities before interacting with people. These skills include reading emotions. Due to its exponential expansion, facial emotion recognition is becoming essential to face recognition. According on photographs, machine learning can recognise expressions. This paper discusses expression recognition model training datasets. Deep learning for Facial Emotion Recognition (FER) is used in this research to teach robots to recognise and adapt to human emotions. An extensive review of deep learning models, including CNNs and CNNR, emphasises their ability to extract spatial and temporal data needed for emotion classification. FER pipeline components like data collection, preprocessing, and model architecture are examined in the paper. Transfer learning, pre-trained models, and data augmentation are studied to address low-labeled dataset concerns. Detailed model training, validation, and evaluation metrics emphasise performance assessment. This study uses the enlarged CohnKanade (CK+) dataset from a face emotion recognition experiment. The system averaged 92.81% accuracy. Eight emotions were successfully detected by the algorithm. The proposed method for emotion recognition has proven useful. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Approach for Automated Skin Disease Classification and Diagnosis 2

A Deep Learning Approach for Automated Skin Disease Classifi...

引用

2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Suresh, Helina Rajini Amutha, m. Tamizharasi, A. Jaya Krishna, A.P. Lalitha, S. Nithya, P. Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Sona College of Technology Department of ECE Tamil Nadu Salem India R.M.D. Engineering College Department of Computer Science and Engineering Kavarapettai Tamil Nadu Chennai India Sona College of Technology Department of Electronics and Communication Engineering Tamilnadu Salem India Arunai Engineering College Department of Computer Science and Engineering Tamil Nadu Tiruvannamalai India

ISBN: (纸本)9798350317558

Everyone is ware that a wide range of problems affect skin structure, function, and appearance. Dermatological issues or dermatoses are common names used to represent the skin related illness. Early detection of skill llness is possible by employing Artificial Intellengence. A wide range of artificial intelligence techniques have been devised to promptly detect and diagnose skin problems. In this article we are proposing mobilenetv2 and LSTm algorithms to identify skin disorders at an early stage. The combination of mobileNetV2 and LSTm (Long Short-Term memory) for skin disease detection involves leveraging a convolutional neural network (CNN) for image feature extraction and a recurrent neural network (RNN) with LSTm units for sequence modeling, this architecture aims to capture both spatial and temporal dependencies in skin image data, making it well-suited for skin disease detection tasks. The method shown in this study can identify five distinct diseases with ease, and with accuracy rates of 99.2%. © 2024 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Cloud Computing: Innovations and Impacts on Global Data Infrastructure

Cloud Computing: Innovations and Impacts on Global Data Infr...

引用

2025 IEEE International Conference on Computational, Communication and Information technology, ICCCIT 2025

作者： Banumathi, S. Sivajothi, E. Indumathi, G.S. Kefyalew, Enku Yosef Sivakumar, J. Priya, V. Banu Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai India St Joseph's College of Engineering OMR Department of MBA Chennai India Technical and Vocational Training Institute Department of Electrical and Electronics Technology Addis Ababa Ethiopia St.Joseph's College of Engineering Department of Electronics and Communication Engineering Chennai India R.M.K. College of Engineering and Technology Department of Mathematics Thiruvallur District India

ISBN: (纸本)9798331512965

Cloud computing has transformed global data infrastructure with unparalleled scale, flexibility, and accessibility. This study examines how cloud computing innovations have changed data storage, processing, and management worldwide. By examining the progression of cloud services from simple storage and computing to sophisticated platforms and SaaS, we examine how they have transformed corporate operations, economic growth, and societal development. Virtualization, containerization, serverless architectures, and edge computing are the main cloud computing advancements, which we investigate through a literature study and case studies. Data security, privacy, and regulatory frameworks are also considered while adopting the cloud. Cloud computing promotes digital transformation in banking, healthcare, education, and government, according to study. The industry's sustainability and green computing efforts and data centers' environmental impacts are also covered. We found that cloud computing continues to spur innovation by enabling new business models, global connectivity, and data-driven application growth. Cloud technologies' integration with AI, IoT, and 5G networks is likely to change the global data infrastructure, opening new research and development options. This report covers the cloud computing landscape, its advancements, and its potential to shape global data management and digital ecosystems. © 2025 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

A Brief Review on Accuracy Level of Smart and micro Grid Systems Use of mL and DL Algorithms Through Hybrid Integration

A Brief Review on Accuracy Level of Smart and Micro Grid Sys...

引用

International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Pitamber Adhikari Febin Prakash Brajehdra Sharma Department of Information Technology & M.Tech Integrated Noida Institute Of Engineering and Technology Greater Noida Uttar Pradesh India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Department of Computer Science and Engineering Tula's Institute Dehradun India

Forecasting of energy is a crucial component in overcoming the challenges of smart grid mechanisms, which include functions such as demand-side management, load reduction, and desirable allocation. The most significant obstacle battling today's grid has to do with efficient forecasting management for restricted predictive inconsistencies. This paper provides a comprehensive and application-focused review of advanced prediction strategies for smart grid systems, as well as the latest advances in the use of machine Learning (mL) and Deep Learning (DL) approaches. It also discusses the significance of hybridized techniques in improving the accuracy of forecasts. A study of comparison using an hourly energy consumption database has been carried out to evaluate the effectiveness of mL and DL techniques. The analysis' findings highlight hybrid methods' superior efficiency when compared to individual mL, DL, and standard statistical methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

AI algorithms for Autonomous Robotics Navigation 2

AI algorithms for Autonomous Robotics Navigation

引用

2nd International Conference Computational and Characterization techniques in engineering and sciences, IC3TES 2024

作者： Komala, C.R. Raja, J. marotrao, Sarange Shreepad Neelima, Nalla Sujatha, R. Chidambarathanu, K. East Point College of Engineering and Technology Department of Information Science and Engineering Karnataka Bengaluru560049 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering School of Computing Tamil Nadu Chennai600062 India Ajeenkya D Y Patil School of Engineering Department of Mechanical Engineering Maharashtra Pune412105 India R.V.R & J.C. College of Engineering Department of Information Technology Andhra Pradesh Chowdavaram522019 India Subbalakshmi Lakshmipathy College of Science Department of Computer Science Tamil Nadu Madurai625022 India R.M.K. Engineering College Department of Computer Science and Business Systems Tamil Nadu Chennai601206 India

ISBN: (纸本)9798350364699

Robotic systems depend much on autonomous navigation since it allows them to operate on their own in environments constantly changing and lacking clarity. The most evolved artificial intelligence (AI) techniques applied in self-driving robot navigation are briefly reviewed in this work. These approaches call for classical methodologies, machine learning, and deep learning as well. We examine the advantages and drawbacks of numerous approaches applied in route planning, location finding, map creation, obstacle avoidance. We investigate how neural networks, sensor fusion, and reinforcement learning may be applied to provide increased dependability and flexibility for guiding systems. Case examples illustrating the advantages and drawbacks of applying artificial intelligence (AI) in practical contexts including service robots, drones, and self-driving cars abound. Combining modern AI algorithms with conventional approaches indicates that it is feasible to create self-driving robots more dependable and efficient based on the increased tracking performance. © 2024 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Exploring Augmented Reality Triage Tools to Support mass Casualty Incidents 66th

Exploring Augmented Reality Triage Tools to Support Mass Cas...

引用

66th International Annual meeting of the Human Factors and Ergonomics Society, HFES 2022

作者： Nelson, Cassidy Rae Conwell, Joseph Lally, Samuel Cohn, madelyn Tanous, Kyle moats, Jason Gabbard, Joseph L. Department of Industrial and Systems Engineering Virginia Tech United States Department of Mathematics Virginia Tech United States Electrical and Computer Engineering Virginia Tech United States School of Visual Arts Virginia Tech United States Department of Computer Science Virginia Tech United States Texas A and M Engineering Extension Service Texas A and M University United States

ARTTS is a head-worn Augmented Reality (AR) Triage Tool Suite containing an initial sorting tool, virtual assessment tool, and virtual triage tag to assist first responders in mass casualty incidents. The initial sorting tool prompts stunned responders through first-wave tasks to aid recalibration from shock to triage. The virtual assessment tool provides novice responders, potentially confused by the chaos, with a walkthrough of the SALT triage flowchart. Finally, current emergency medical triage processes leverage static paper tags susceptible to loss or illegible damage. ARTTS’ virtual triage tags are dynamic, can be updated automatically with vital sensors or manually through responder interaction, and employ user interface emergent features based on individual patient conditions. This paper describes the UX process used to develop ARTTS. © 2022 by Human Factors and Ergonomics Society. All rights reserved.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

An Automatic Error Recognition approach for machine Translation Results based on Deep Learning

An Automatic Error Recognition approach for Machine Translat...

引用

computer, Communication and Control (IC4), International Conference on

作者： m N Rekha mudarakola Lakshmi Prasad Saptarshi mukherjee Sudam Vasant Nikam Swati Sharma Pundru Chandra Shaker Reddy Electrical and Electronics Engineering Sri Jayachamarajendra College of Engineering JSS Science and Technology University Mysore Karnataka India Computer Science and Engineering Institute of Aeronautical Engineering Dundigal Telangana India M.Tech-Bioinformatics Maulana Abul Kalam Azad University of Technology West Bengal India Instrumentation Engineering Bharati Vidyapeeth College of Engineering Navi Mumbai India School of Computer Science Engineering and Information Science Presidency University Bangalore Karnataka India School of Computer Science and Artificial Intelligence SR University Warangal Telangana India

At present, the speedy growth of natural-language-processing(NLP) has produced considerable evolution for the topic of machine-translation. There have been many deep neural network–based machine-translation(mT) methods that have become increasingly broad. Still, there currently lacks reliable automatic-error-detection(AED) systems for mT outcomes. One important metric for gauging the efficacy of an engineering English translation application is the accuracy of the corresponding deep learning model’s translation. This research presents a deep learning-based solution for automatic mistake identification in machine translation results as a means of closing this gap. In this research, we propose a deep generative model to synthesis the training data that will be utilized to train a model to correct grammatical errors in English used in international trade. Next, the learner’s corpus is corrected using the grammatical fault alteration approach, and “error-correct” sentence pairs are created using the exacted aim sentences and by hand interpreted standard sentences and fed back to the error generation technique for retraining. The model’s error detection and correction capabilities are enhanced through the establishment of a connection amid the grammatical error recognition and correction model. The suggested error recognition method has been shown to considerably increase the stealthiest of the trigger, guarantee the efficacy of the backdoor assault, and make the trigger resistant to specific data augmentation operations in experiments using datasets like GTRSB.

关键词：

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117页 << < 8 9 10 11 12 13 14 15 16 17 > >>

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：