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

57,155 篇 会议
8,941 篇 期刊文献
393 册 图书

馆藏范围

66,489 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

41,536 篇 工学
- 26,530 篇 计算机科学与技术...
- 22,046 篇 软件工程
- 11,510 篇 信息与通信工程
- 7,169 篇 电子科学与技术（可...
- 6,957 篇 电气工程
- 6,923 篇 控制科学与工程
- 3,747 篇 生物工程
- 3,146 篇 生物医学工程（可授...
- 3,053 篇 光学工程
- 2,734 篇 机械工程
- 2,642 篇 动力工程及工程热...
- 2,458 篇 仪器科学与技术
- 1,973 篇 化学工程与技术
- 1,433 篇 材料科学与工程（可...
- 1,415 篇 安全科学与工程
- 1,323 篇 交通运输工程
- 1,175 篇 建筑学
21,372 篇 理学
- 11,398 篇 数学
- 6,822 篇 物理学
- 4,085 篇 生物学
- 3,625 篇 统计学（可授理学、...
- 2,599 篇 系统科学
- 2,056 篇 化学
9,289 篇 管理学
- 5,629 篇 管理科学与工程(可...
- 4,104 篇 图书情报与档案管...
- 3,118 篇 工商管理
2,515 篇 医学
- 2,179 篇 临床医学
- 2,043 篇 基础医学(可授医学...
- 1,363 篇 药学(可授医学、理...
1,668 篇 法学
- 1,368 篇 社会学
1,121 篇 经济学
762 篇 教育学
737 篇 农学
277 篇 文学
178 篇 军事学
66 篇 艺术学
6 篇 哲学
3 篇 历史学

主题

1,624 篇 accuracy
1,443 篇 computational mo...
1,279 篇 feature extracti...
1,143 篇 training
903 篇 deep learning
869 篇 real-time system...
834 篇 machine learning
763 篇 predictive model...
718 篇 computer science
700 篇 optimization
657 篇 computer archite...
632 篇 support vector m...
611 篇 data models
576 篇 internet of thin...
567 篇 neural networks
552 篇 wireless sensor ...
515 篇 monitoring
514 篇 data mining
510 篇 convolutional ne...
454 篇 bandwidth

机构

166 篇 dept. of electri...
82 篇 north-west unive...
81 篇 institut univers...
79 篇 infn sezione di ...
76 篇 infn sezione di ...
76 篇 institute of inf...
76 篇 national centre ...
66 篇 università di ca...
61 篇 dept. of electr....
58 篇 dept. of electri...
56 篇 dept. of compute...
56 篇 dept. of informa...
52 篇 dept. of electri...
52 篇 school of automa...
49 篇 leiden universit...
44 篇 dept. of compute...
42 篇 infn lnf via enr...
42 篇 in2p3 lpc campus...
39 篇 dept. of compute...
37 篇 dept. of electri...

作者

85 篇 ferrara g.
85 篇 ardid m.
84 篇 calvo d.
82 篇 gal t.
81 篇 chen a.
81 篇 bozza c.
63 篇 kalekin o.
52 篇 kulikovskiy v.
45 篇 huang f.
41 篇 benoit d.m.
41 篇 eddymaoui a.
40 篇 gagliardini s.
40 篇 labalme m.
40 篇 díaz a.f.
37 篇 androulakis g.
34 篇 de palma m.
34 篇 khatun a.
32 篇 eirini eleni tsi...
27 篇 kougianos elias
27 篇 david reigosa

语言

63,095 篇 英文
2,332 篇 其他
749 篇 中文
247 篇 朝鲜文
68 篇 日文
9 篇 土耳其文
5 篇 德文
2 篇 俄文
2 篇 斯洛文尼亚文
1 篇 阿拉伯文
1 篇 西班牙文
1 篇 法文
1 篇 葡萄牙文

检索条件"机构=dept. of Computer Computer Systems Engineering"

共 66489 条记录，以下是191-200 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：

Efficiency Comparison of Dataset Generated by LLMs using Machine Learning Algorithms 6

Efficiency Comparison of Dataset Generated by LLMs using Mac...

引用

6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Pawade, Premraj Kulkarni, Mohit Naik, Shreya Raut, Aditya Wagh, K.S. AISSMS IOIT Dept. of Computer Engineering Pune India

ISBN: (纸本)9798350306613

The constantly expanding field of Large Language Models (LLMs) offers exciting opportunities for various domains. These powerful models, such as GPT-3.5, Bard, and Bing, can produce massive amounts of text-based data, creating new avenues for generating synthetic datasets. The primary focus of this research is to explore the effectiveness of LLMs in creating high-quality, structured datasets for different ML applications. Specifically, this study concentrates on password strength prediction. It compares the performance of three prominent LLMs-Bard, ChatGPT, and BingAI-in generating datasets of text-based passwords with their corresponding strength levels. This research uses a diverse set of ML models, including traditional algorithms like XGBoost, Random Forest, etc., to evaluate the generated datasets. The evaluation process assesses their performance, generalization, and adaptability. This research contributes to the growing field of LLM-based data generation by demonstrating their effectiveness in creating valuable datasets for specific machine learning applications. The findings of this study pave the way for further exploration of LLMs' capabilities for diverse data types and tasks, potentially unlocking new avenues for advancements in various machine learning domains. © 2024 IEEE.

关键词： Artificial Data Generation Data Augmentation Evaluation Metrics Generative AI Large Language Models (LLMs) Machine Learning password-strength

来源：评论

学校读者我要写书评

暂无评论

Distributed Key Value Store for IoT Edge Devices 9

Distributed Key Value Store for IoT Edge Devices

引用

9th International Conference on computer Science and engineering, UBMK 2024

作者： Aslantaş, Burak Pektaş, Elif Nurdan Baydere, Şebnem Yeditepe University Dept. of Computer Engineering Istanbul Turkey

ISBN: (纸本)9798350365887

The proliferation of the Internet of Things (IoT) requires efficient and scalable data management solutions at the edge of the network. Edge devices play a critical role in processing data and making real-time decisions, thereby minimizing latency and reducing the load on central servers. However, these devices face challenges such as scalability, latency, and fault tolerance. This paper proposes a distributed key-value store specifically designed for IoT edge devices to address these challenges. By integrating distributed key-value stores with IoT edge devices, we aim to enhance data access and management efficiency. Our approach includes the development of optimal methodologies and architectural standards for this integration, addressing key issues such as data consistency, fault tolerance, and low latency. Through prototype creation and testing, we demonstrate significant improvements in data processing speed and system reliability. The ultimate objective of this research is to advance edge computing for IoT, fostering more robust, scalable, and efficient systems. © 2024 IEEE.

关键词： Data consistency

来源：评论

学校读者我要写书评

暂无评论

Accelerating Disaster Response with Deep Learning and Image Processing Techniques

Accelerating Disaster Response with Deep Learning and Image ...

引用

2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2024

作者： Karakaş, Çağrı Aydin, İlhan Akin, Erhan Dept. of Computer Engineering Firat University Elazığ Turkey

ISBN: (纸本)9798331533137

This study examines the use of artificial intelligence-based image segmentation and image processing techniques in disaster management. The aim of the study is to integrate artificial intelligence and image processing techniques for fast and effective response in disaster areas to facilitate disaster management. Our hypothesis is that fast and accurate analysis can be performed with high-performance and fast AI-based segmentation models and image processing techniques on images taken from UAVs and satellites in disaster areas. In this process, important regions in the images are identified by applying segmentation processes and masks are created. Then, using these masks, numerical results can be obtained with image processing techniques with low computational cost. Thus, it is aimed to make fast and accurate decisions in disaster management. In this study, popular segmentation models were compared and analyzed using 2343 images obtained from Floodnet dataset. The results show that the SegFormer model provides detailed damage analysis and contour area or connected component analysis, which can provide both detailed and numerically accurate results for disaster management. This study reveals that the use of image processing and artificial intelligence in disaster management can improve response processes by increasing operational efficiency. ©2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Model for Detecting the Presence of Neurological Conditions in MRI and CT Scans 2

Deep Learning Model for Detecting the Presence of Neurologic...

引用

2nd IEEE International Conference on Recent Advances in Information Technology for Sustainable Development, ICRAIS 2024

作者： Kanchan, Jayapadmini Ananya, H.N. Anoksha, N.A. Hegde, Sarika Dept. of Computer Science and Engineering Nitte Karkala India

ISBN: (纸本)9798350354461

An AI-powered MRI/CT analysis solution for medical professionals can significantly enhance diagnostic accuracy and efficiency. By harnessing deep learning algorithms, this solution can minimize human error and accelerate image interpretation. The incorporation of a Convolutional Neural Network (CNN) model empowers the solution to identify abnormalities in MRI/CT images with high consistency and reliability. This solution supports intricate case evaluations and integrates effortlessly with electronic health records, making high-quality diagnostic capabilities available to a wider range of healthcare professionals. The solution is meticulously designed to detect various abnormalities, including tumors, Alzheimer's, and hemorrhages from MRI images, as well as COVID-19 and checking for squamous conditions from CT images. Ultimately, this solution aims to improve patient outcomes through precise and prompt diagnoses, while also serving as an educational resource and contributing to ongoing medical research and innovation. The brain tumor MRI model achieved an accuracy of 87.5% after 100 epochs, while the chest CT scan model attained 95.65% accuracy in just 50 epochs. Brain hemorrhage MRI model accomplished 88.45% accuracy in 30 epochs, and the COVID-19 dataset model reached 78.9% accuracy in 40 epochs. Lastly, the Alzheimer's model obtained an accuracy of 80.70% after 40 epochs. © 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

Smart Garden Watering and Lighting System Integrated with Machine Learning Model to Maintain Urban Gardens

Smart Garden Watering and Lighting System Integrated with Ma...

引用

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

作者： Shahapure, Arsheyee Siddha, Rishika Tewary, Tanmay Shahapure, Aniruddha Mantri, Shamla Kamble, Aparna Dept. Computer Science and Engineering MIT-WPU Pune India

ISBN: (纸本)9798331512965

Garden maintenance may be a difficult task, particularly in urban settings. Many people are not skilled enough to determine their plants' precise requirements for lighting and watering. Conventional gardening techniques frequently result in underwatering or overwatering, wasting resources, and producing unhealthy plants. Our completely automated smart garden watering and lighting system offers a fully automated solution to these problems. With its sophisticated sensors, this system keeps an eye on the quantity of moisture in the soil and the amount of sunshine it receives, making sure plants get the correct amount of both for healthy growth. Traditional gardening involves guesswork and physical effort, which our solution avoids by automating the irrigation and lighting operations. You may have the advantages of a flourishing garden without the trouble of ongoing upkeep with our intelligent gardening system. Our method offers a dependable and effective solution to care for your plants and improve your urban green space, regardless of experience level. © 2025 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Enhancing Artificial Intelligence and Machine Learning Understanding Through EnVision: A Virtual Reality Approach 1

Enhancing Artificial Intelligence and Machine Learning Under...

引用

1st International Conference on Pioneering Developments in computer Science and Digital Technologies, IC2SDT 2024

作者： Patra, Louise Kumari, Manisha Gopalapillai, Radhakrishnan Dept. of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350365016

The quality of teaching and learning process can be improved through innovative methods like use of virtual reality. We introduce EnVision, a groundbreaking Virtual Reality based approach to revolutionize Artificial Intelligence and Machine Learning (AI/ML) education. EnVision offers a unique approach where users build models through immersive learning experiences. Using interactive tutorials mixed with real-time data integration and visualization, users learn AI/ML concepts with ease. Through qualitative and quantitative methods, we evaluate EnVision's effectiveness and user satisfaction, contributing to the advancement of innovative educational gaming technologies. The evaluation results show that EnVision provides the AI/ML practitioners engaging learning experiences. © 2024 IEEE.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

XAI and computer Vision: Interpretable Deep Learning Approach with Explainable Artificial Intelligence for Brain Tumor Classification

XAI and Computer Vision: Interpretable Deep Learning Approac...

引用

2024 International Conference on Artificial Intelligence and Emerging Technology, Global AI Summit 2024

作者： Moodely, Govana Vetrimani Amiree, S. M. Ihtasham Hossain Ravikumar, R.N. Wanglen, Soram Chauhan, Shailendrasinh Singh, Sushil Kumar Marwadi University Dept. of Computer Engineering Rajkot India

ISBN: (纸本)9798350379716

Explainable Artificial Intelligence (XAI) plays a crucial role in the field of healthcare by enhancing transparency and decision-making processes in computer vision applications. In our research, we utilized two Convolutional Neural Network (CNN) models, SeparableConvNet and ConvNet, for the classification of brain tumors using computer vision techniques. These models were evaluated using a dataset consisting of 7023 human brain MRI scans collected from figshare, SARTAJ and Br35H datasets on Kaggle. The images were categorized into four groups: Gliomas, meningiomas, no tumor and pituitary. Both models underwent preprocessing steps including data normalization and augmentation to improve reliability and generalizability. The SeparableConvNet achieved a test accuracy of 96.64%, outperforming the ConvNet's test accuracy of 95.19%. To enhance interpretability and gain insights into the models' decision-making processes, 'Local Interpretable Model-agnostic Explanations (LIME)' were employed. Our results highlight the effectiveness of CNN models in classifying brain tumors using computer vision and underscore the importance of XAI techniques in understanding these models' predictions. © 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

Implementation of Fuzzy Logic Model to Solve Traffic Congestion Problem at Road Intersections

Implementation of Fuzzy Logic Model to Solve Traffic Congest...

引用

2024 IEEE International Conference on Automation and Computation, AUTOCOM 2024

作者： Negi, Vinay Jha, Sundaram Kumar Behl, Rachna Mriirs Dept. of Computer Science & Engineering Faridabad India

ISBN: (纸本)9798350382723

This research aims to tackle traffic congestion at intersections, primarily caused by static traffic light timings that don't adapt to changing traffic conditions. The proposed solution involves using adaptive fuzzy controllers, which can adjust their decisions based on fuzzy IF-THEN rules. These controllers employ both Mamdani and Sugeno fuzzy logic. The Mamdani method considers factors like the number of vehicles, queue length, emergency vehicle access, and road width to optimize traffic light timings and reduce unnecessary green signals. The Sugeno-type fuzzy logic enhances controller efficiency and decreases waiting times. The study also explores the application of direct adaptive fuzzy controllers to manage unstable systems, which is relevant in optimizing traffic control. Ultimately, the goal is to develop a simulator capable of predicting the right traffic light timings in real-time. This involves extending green light timings for lanes with high vehicle volumes and also for the emergency vehicles to alleviate congestion at intersections. © 2024 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Advancing Multilingual Speaker Identification and Verification for Indo-Aryan and Dravidian Languages 1

Advancing Multilingual Speaker Identification and Verificati...

引用

1st Workshop on Natural Language Processing for Indo-Aryan and Dravidian Languages, IndoNLP 2025

作者： Sritharan, Braveenan Thayasivam, Uthayasanker Dept. of Computer Science & Engineering University of Moratuwa Sri Lanka

ISBN: (纸本)9798891762145

Multilingual speaker identification and verification is a challenging task, especially for languages with diverse acoustic and linguistic features such as Indo-Aryan and Dravidian languages. Previous models have struggled to generalize across multilingual environments, leading to significant performance degradation when applied to multiple languages. In this paper, we propose an advanced approach to multilingual speaker identification and verification, specifically designed for Indo-Aryan and Dravidian languages. Empirical results on the Kathbath dataset show that our approach significantly improves speaker identification accuracy, reducing the performance gap between monolingual and multilingual systems from 15% to just 1%. Additionally, our model reduces the equal error rate for speaker verification from 15% to 5% in noisy conditions. Our method demonstrates strong generalization capabilities across diverse languages, offering a scalable solution for multilingual voice-based biometric systems. © 2025 Association for Computational Linguistics.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Share-a-Meal: A Mobile App-based Food Sharing System 6

Share-a-Meal: A Mobile App-based Food Sharing System

引用

6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Uddin, Mohammad Salah Ansary, Fozlay Rabby Dept. of Computer Science and Engineering East West University Bangladesh

ISBN: (纸本)9798331522667

Many problems have been solved using the internet of things (IoT). Waste management, resource management, traffic management, financial services (e.g. stock rate prediction), logistics services, agriculture, etc. are the major sectors where IoT has played a fruitful role. The use of IoT is increasing day by day due to its immense advantages. This paper presented an IoT-based system for sharing leftover food with others or hungry people. The system consists of a mobile application and an embedded system. Cloud service is used as middle-ware between the mobile application and embedded system. Mobile application is used for sending and receiving notifications. The rectangular-shaped box type embedded system is responsible for food collecting and distribution. The development and prototype implementation of our proposed system are discussed throughout this paper. The system helps to share leftovers (food) with others which can reduce food wastage. © 2025 IEEE.

关键词： Cloud-Food Food waste Food-sharing internet of things Leftover food

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 << < 16 17 18 19 20 21 22 23 24 25 > >>

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：