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

1,607 篇 会议
372 篇 期刊文献
2 册 图书

馆藏范围

1,981 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,014 篇 工学
- 785 篇 计算机科学与技术...
- 676 篇 软件工程
- 261 篇 信息与通信工程
- 208 篇 控制科学与工程
- 152 篇 电气工程
- 148 篇 生物工程
- 137 篇 生物医学工程（可授...
- 115 篇 光学工程
- 99 篇 电子科学与技术（可...
- 94 篇 安全科学与工程
- 92 篇 网络空间安全
- 68 篇 交通运输工程
- 66 篇 仪器科学与技术
- 65 篇 机械工程
- 54 篇 化学工程与技术
- 53 篇 动力工程及工程热...
541 篇 理学
- 252 篇 数学
- 168 篇 生物学
- 147 篇 物理学
- 107 篇 统计学（可授理学、...
- 71 篇 化学
319 篇 管理学
- 223 篇 管理科学与工程(可...
- 122 篇 工商管理
- 118 篇 图书情报与档案管...
167 篇 医学
- 124 篇 临床医学
- 123 篇 基础医学(可授医学...
- 108 篇 公共卫生与预防医...
- 61 篇 药学(可授医学、理...
76 篇 法学
- 67 篇 社会学
55 篇 经济学
- 55 篇 应用经济学
49 篇 农学
23 篇 教育学
13 篇 文学
2 篇 军事学
1 篇 艺术学

主题

239 篇 accuracy
158 篇 real-time system...
148 篇 deep learning
103 篇 convolutional ne...
97 篇 training
96 篇 predictive model...
96 篇 machine learning
82 篇 feature extracti...
75 篇 computational mo...
74 篇 machine learning...
70 篇 medical services
69 篇 support vector m...
66 篇 data models
63 篇 internet of thin...
55 篇 optimization
54 篇 reliability
50 篇 reviews
48 篇 artificial intel...
47 篇 prediction algor...
45 篇 monitoring

机构

50 篇 nitte meenakshi ...
42 篇 department of ar...
41 篇 lovely professio...
32 篇 department of ar...
32 篇 department of co...
25 篇 lamarr institute...
24 篇 rajalakshmi engi...
21 篇 department of ar...
20 篇 department of ar...
20 篇 machine learning...
19 篇 east west instit...
19 篇 department of co...
19 篇 new horizon coll...
18 篇 the department o...
18 篇 the lamarr insti...
18 篇 department of ar...
18 篇 vector institute...
18 篇 division of arti...
15 篇 college of techn...
15 篇 university of bo...

作者

42 篇 prateek verma
42 篇 piyush kumar par...
41 篇 pareek piyush ku...
36 篇 mohsen guizani
30 篇 stachniss cyrill
26 篇 verma prateek
23 篇 guizani mohsen
19 篇 behley jens
18 篇 von lilienfeld o...
16 篇 uma reddy
16 篇 cyrill stachniss
16 篇 vijay k.
14 篇 amandeep nagpal
14 篇 swapnil gundewar
13 篇 zhang kun
12 篇 aditya barhate
12 篇 madhura g.k.
12 篇 abhay tale
12 篇 reddy uma
11 篇 utkarsha pachara...

语言

1,449 篇 英文
530 篇 其他
6 篇 中文
1 篇 斯洛文尼亚文

检索条件"机构=Artificial Intelligence and Machine Learning Engineering"

共 1981 条记录，以下是221-230 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：

CRYPTOPASS - A Unified Password Manager

CRYPTOPASS - A Unified Password Manager

引用

2024 IEEE International Conference on Electronic Systems and Intelligent Computing, ICESIC 2024

作者： Samuel, Prithi Vijay, K. Dheephiga, A.M. Maarcus Reniero, L. SRM Institute of Science and Technology Kattankulathur Campus Department of Computational Intelligence India Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Worldline Global Services Chennai India UST Chennai India

ISBN: (纸本)9798331522988

In the present scenario, many people are unaware of the security risks when they store their passwords or keys directly as a text file without encryption. This leaves your password exposed to hackers who can access them easily. This software aims to create only one strong password to ease the pressure of remembering passwords is very efficient for us as users. A dedicated password manager will store your passwords in an encrypted form, help you generate secure random passwords, offer a more powerful interface, and allow you to easily access your passwords across all the different computers, smartphones, and tablets you use. Keeping the above scenario in mind, this application is designed to enhance the security of user's data. This application is based on password vaults or password managers which are programs that keep your passwords in a secure location. When you use this software, the passwords are encrypted, and you use a single master password to access them. The basic idea is to create only one password to help to remember it as well as for efficient access. This increases the security of our accounts as well as the regulation of our passwords in a secure manner. The key components of reusability and flexibility are implemented in this project which makes the project even more user friendly and makes the user more comfortable towards using Cryptopass. © 2024 IEEE.

关键词： Cross-Platform Compatibility Cryptopass Master Password Password Encryption Password Vault Secure Access User-Friendly Interface

来源：评论

学校读者我要写书评

暂无评论

Effective Prediction of Cardiovascular Disease Using Deep learning 8th

Effective Prediction of Cardiovascular Disease Using Deep Le...

引用

8th International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023

作者： Annabel, L. Sherly Puspha Sruthi, B. Sai Rohini, M. Svetha, B. Sai Department of Artificial Intelligence and Machine Learning St. Joseph’s College of Engineering Chennai600119 India Department of Information Technology St. Joseph’s College of Engineering Chennai600119 India

ISBN: (纸本)9789819702091

Today's leading cause of death worldwide is cardiovascular disease, which has risen to the top of the list of diseases in terms of diagnostic difficulty. Cardiovascular disease is more likely to occur in a person with chest pain, depression, hypertension, smoking, women with early menopause, diabetes, high cholesterol, and over drinking. Early prediction of cardiovascular disease is needed to save more lives. Here comes the saviour machine learning algorithms that are less expensive with more accuracy. Some of the common machine learning algorithms are implemented to predict the disease. Different techniques provide different accuracies depending on the attributes, dataset, and tools used for implementation. Using the ECG dataset, we create an 11-layer Convolutional Neural Network 2D in this study. We have proposed two models namely Cardiovascular Disease Detection—machine learning (CVD-ML) that can predict Cardiovascular Disease using real-time numerical data and Cardiovascular Disease Detection—Deep learning (CVD-DL) using the ECG Image. By using ensembling technique, we have attained the highest accuracy of 94.6% for real-time numerical data and by using Convolutional Neural Network we have attained the accuracy of 99.9% for ECG data. Therefore, artificial intelligence techniques used are highly reliable and effective in providing accuracy for cardiovascular disease prediction. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Blockchain-based Booth-less Tolling System using GPS and Image Processing

Blockchain-based Booth-less Tolling System using GPS and Ima...

引用

2023 IEEE World AI IoT Congress, AIIoT 2023

作者： Thosar, Keshav Singh, Hargobind Chatterjee, Sreejit Ambawade, Dayanand Sardar Patel Institute of Technology Electronics and Telecomm. Engineering Mumbai India Sardar Patel Institute of Technology Artificial Intelligence and Machine Learning Engineering Mumbai India

ISBN: (纸本)9798350337617

India as a country is aggressively investing in building better roads and highways, but due to the costly nature of these projects, they are done in the form of a Public Private Partnership. This makes the efficient collection of toll tax highly important to incentivize further development of infrastructure. Currently, the FASTag system of tolling is employed in India which is resulting in unorganized and inaccurate revenue collection, physical problems like tags getting damaged, traffic congestion and reduced fuel efficiency. To solve these problems, a blockchain-based virtual tolling system using GPS and Image processing is proposed. In this paper, appropriate hardware and software designs were involved to develop a GPS-based highway toll collection system further complemented with image processing to get the number plate data. A blockchain-based technology to implement a decentralized, secure toll collection mechanism that uses blockchain smart contracts to store data. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Deep learning-Based Age and Gender Prediction through Feature Extraction from Facial Images using Convolutional Neural Networks 5

Deep Learning-Based Age and Gender Prediction through Featur...

引用

5th IEEE International Conference on Communication, Computing and Industry 6.0, C2I6 2024

作者： Manasa, S.M. Ramamoorthy, Raghu Velu, Anitha Angel Donny, F. Chaitrashree, S. Ramaiah Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India The Oxford College of Engineering Department of Computer Science and Engineering Bengaluru India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350379884

In recent years, age estimation and gender classification have been focal points in the field of pattern recognition and computer vision. This paper introduces an automated approach for predicting age and gender by extracting features from human facial images. In contrast to conventional methods that operate on unfiltered facial images, our study demonstrates significant improvements in these tasks through the use of deep convolutional neural networks (CNNs). The employed feedforward neural network method enhances robustness for highly variable unconstrained recognition tasks, specifically targeting gender identification and age group estimation. The research methodology involves the analysis and validation of gender prediction and age estimation on two benchmark datasets: the Essex face dataset and the Adience benchmark dataset. Results indicate a substantial performance enhancement, showcasing the proposed approach's efficiency and state-of-the-art performance in both age and gender detection. The model achieves remarkable accuracy, positioning it as a notable advancement in the realm of age and gender prediction using deep learning techniques. © 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

A Review on the Developments in the Field of AI-Based Gait Analysis 2

A Review on the Developments in the Field of AI-Based Gait A...

引用

2nd DMIHER International Conference on artificial intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Wankhede, Vidhi Verma, Prateek Gahane, Shailesh Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha442001 India Datta Meghe Institute of Higher Education and Research Faculty of Sciences and Technology Maharashtra Wardha442001 India

ISBN: (纸本)9798331528713

The examination of human gait is essential for comprehending motor function, the evolution of diseases, and the effectiveness of rehabilitation in different clinical and research environments. artificial intelligence (AI) advancements have recently improved gait analysis methodologies, resulting in increased accuracy, efficiency, and therapeutic effectiveness. This review article compiles the existing literature on AI-based gait analysis. The review emphasizes the role of AI in gait analysis, namely via the use of vision-based approaches, wearable sensor technologies, markerless motion capture systems, and inertial sensor-based methodologies. AI has shown potential in identifying musculoskeletal problems including osteopenia and sarcopenia, forecasting the start of Parkinson's disease, assessing the effects of post-stroke rehabilitation, and diagnosing neurological conditions. In addition, the integration of AI with new technologies such as augmented reality (AR), smart sensors, and wearable devices presents intriguing opportunities to improve gait rehabilitation, enable individualized therapies, and facilitate remote patient monitoring. Although there have been significant breakthroughs, there are still obstacles in creating AI models that can be easily understood for clinical decision-making, establishing standardized procedures for collecting data, and verifying AI algorithms across various populations. This study underlines the transformational potential of AI-based gait analysis in customized healthcare, rehabilitation techniques, and clinical results. In order to fully harness the potential of AI in enhancing human health and well-being, it is imperative to do more research and foster multidisciplinary cooperation. © 2024 IEEE.

关键词： Clinical research

来源：评论

学校读者我要写书评

暂无评论

A Novel Generative AI-Powered Approach for Sentiment Analysis: Enhancing Deep learning Models with Contextual Understanding 3

A Novel Generative AI-Powered Approach for Sentiment Analysi...

引用

3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Naik, Mahendra Shridhar Chaitra, S.N. Shashikala, K.S. New Horizon College of Engineering Department of Electronics & Communication Bengaluru India Gm Institute of Technology Department of Electronics & Communication Davangere India New Horizon College of Engineering Department of Artificial Intelligence & Machine Learning Bengaluru India

ISBN: (纸本)9798331515911

Sentiment analysis, a pivotal aspect of natural language processing (NLP), has seen notable advancements with the advent of deep learning models. Despite these advancements, challenges persist in accurately capturing nuanced emotions and understanding context-dependent sentiments. This paper introduces an innovative method that integrates generative adversarial networks (GANs) into deep learning architectures to enhance sentiment analysis. By leveraging GAN's ability to generate contextually relevant text, the proposed approach enriches the training data, thereby improving the model's ability to discern subtle sentiment variations. Our extensive experiments on benchmark datasets reveal that our method surpasses traditional deep learning models, achieving a 5% improvement in accuracy, a 7% higher F1-score, and demonstrating superior robustness to sarcasm and irony. © 2025 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Partial Convolution U-Net for Inpainting Distorted Images 15

Partial Convolution U-Net for Inpainting Distorted Images

引用

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

作者： Rashmi Adyapady, R. Annappa, B. Sagar, Prem Nmam Institute of Technology Department of Artificial Intelligence and Machine Learning Karnataka Nitte India National Institute of Technology Karnataka Discover Lab Department of Computer Science and Engineering Karnataka Mangalore India

ISBN: (纸本)9798350370249

Image inpainting is a domain in which researchers have shown considerable interest, and when it comes to deep learning techniques, realistic problems become interesting and challenging. In image inpainting, a corrupted facial image with missing holes or significant holes can be restored and compared to the original image to see if it is real or fake. In addition to fixing the texture of the image and getting the image's high-level abstract properties, it may also recover semantic images such as human faces. In the field of image-inpainting models, the Attention model with features learned through semantic approaches and progressive networks has become particularly popular. The proposed model introduces (i) Attention blocks in each decoder layer of U-Net architecture and (ii) a hybrid loss function leveraging both Mean Square Error (MSE) and Mean Absolute Error (MAE). The proposed Attention-based U-Net showed remarkable performance with SSIM and PSNR by 0.1067 and 13.63, respectively, compared to the previous approaches. © 2024 IEEE.

关键词： Distorted Images Image Inpainting Partial Convolution U-Net

来源：评论

学校读者我要写书评

暂无评论

Hybrid Deep learning with TSOA Model for Predicting the Parkinson Disease using Speech Features 2

Hybrid Deep Learning with TSOA Model for Predicting the Park...

引用

2nd International Conference on Data Science and Information System, ICDSIS 2024

作者： Pareek, Piyush Kumar Zanke, Pankaj Prasad, Anoop N. Mohan, B.R. Nitte Meenakshi Institute Of Technology Artificial Intelligence And Machine Learning Bengaluru India Sapiens International Corporation Israel East West Institute Of Technology Department Of Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350381665

True early identification of Parkinson's illness (PD) is absolutely fundamental to stopping the ill health course and planning affected role with access to disease-modifying medications. To do this, significant attention should be paid to the premotor stage of PD. Based on premotor characteristics, a unique deep-learning algorithm is provided to swiftly detect whether or not a person has PD. By identifying and assessing indicators that indicate speech attribute and degree of worsening, a voiced numerical biomarker may supplement the laborious traditional physical test. The project attempts to develop a revolutionary end-to-end deep learning model using speech data for Parkinson's disease identification. The current study employs a mixed deep learning model to evaluate and identify PD. The study's objectives were to identify vocal anomalies in PD patients and create an automatic test technique that can distinguish concerning PD patients' voices and those of fit informs while also grading voice quality. his study investigates the effectiveness of utilizing deep learning architectures for speech data analysis in the context of [insert context]. Specifically, we employ a convolutional neural network (CNN) architecture with recurrent layers (e.g., Long Short-Term Memory, LSTM) to extract hierarchical features from raw speech signals. Our methodology involves preprocessing the raw audio data to extract relevant acoustic features, such as mel-frequency cepstral coefficients (MFCCs) and spectrograms. These features are then fed into the CNN-LSTM model, which learns discriminative representations for various speech tasks, including [mention specific tasks, e.g., speech recognition, emotion recognition, etc.].The category accurateness was evaluated using the Italian PVS speaking quantities and the Lithuanian PD voice dataset. With values of 0.92 showing that the results are medically adequate, the findings demonstrated that the suggested model is highly generalizable. © 2024

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

From 5G to 6G: The Role of AI, machine learning, and Deep learning in Wireless Systems 4

From 5G to 6G: The Role of AI, Machine Learning, and Deep Le...

引用

4th International Conference on Sentiment Analysis and Deep learning, ICSADL 2025

作者： Gote, Pradnyawant M. Kumar, Praveen Verma, Prateek Yesankar, Prajyot Pawar, Adesh Saratkar, Saniya Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India

ISBN: (纸本)9798331523923

The swift progression of wireless communication technologies-specifically from 5G to 6G is an approach that could be the most significant revolutionary leap towards changing connectivity and data transmission forever. Additionally, algorithms of machine learning (ML) and deep learning (DL) in 5G and 6G can offer promising advancements toward predictive maintenance, dynamic spectrum management, and enhanced security. The review of the potentially transformative nature of these technologies underlines the need for future directions of research efforts called for in circumventing challenges towards making full capability exploitation of 6G possible. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Analyzing the Feasibility of Bert Model for Toxicity Analysis of Text 6th

Analyzing the Feasibility of Bert Model for Toxicity Analysi...

引用

6th International Conference on Innovative Computing and Communication, ICICC 2023

作者： Chakraverty, Yuvraj Kaintura, Aman Kumar, Bharat Khanna, Ashish Sharma, Moolchand Pareek, Piyush Kumar Department of Computer Science and Engineering Maharaja Agrasen Institute of Technology New Delhi India Department of Artificial Intelligence and Machine Learning and IPR Cell Nitte Meenakshi Institute of Technology Bengaluru India

ISBN: (纸本)9789819940707

Online comments can often be toxic, offensive, and harmful to individuals and communities. In recent years, there has been a growing need to automatically identify and mitigate these toxic comments. For this problem, NLP models are often used to identify such toxicity and harshness but each model has its own efficiency and performance limitations. In this paper, we propose the use of the bidirectional encoder representations from transformers (BERT) algorithm for toxicity classification of online comments. BERT is a state-of-the-art natural language processing model developed by Google in 2018 that has shown strong results on a variety of tasks. In this paper, we used the BERT algorithm for toxicity classification and evaluated its performance on a real world dataset and performed comparative analysis with conventional NLP models, logistic regression (TF-IDF) over which BERT showed an improvement of 6.9% in accuracy, 26.1% in f1-score, 21.5% in ROC score;logistic regression (BOW) over which BERT showed an improvement of 9.1% in accuracy, 70.6% in f1-score, 39.8% in ROC score;multinomialNB (BOW) over which BERT showed an improvement of 9.2% in accuracy, 25.9% in f1-score, 10.6% in ROC score. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Natural language processing systems

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199页 << < 19 20 21 22 23 24 25 26 27 28 > >>

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：