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

2,709 篇 会议
1,235 篇 期刊文献
22 册 图书

馆藏范围

3,966 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,155 篇 工学
- 1,665 篇 计算机科学与技术...
- 1,381 篇 软件工程
- 543 篇 信息与通信工程
- 396 篇 控制科学与工程
- 335 篇 生物工程
- 283 篇 生物医学工程（可授...
- 248 篇 电气工程
- 232 篇 光学工程
- 196 篇 网络空间安全
- 161 篇 电子科学与技术（可...
- 144 篇 仪器科学与技术
- 130 篇 安全科学与工程
- 114 篇 机械工程
- 103 篇 动力工程及工程热...
- 102 篇 交通运输工程
- 99 篇 化学工程与技术
1,207 篇 理学
- 530 篇 数学
- 403 篇 生物学
- 311 篇 物理学
- 215 篇 统计学（可授理学、...
- 169 篇 化学
691 篇 管理学
- 449 篇 管理科学与工程(可...
- 281 篇 图书情报与档案管...
- 221 篇 工商管理
351 篇 医学
- 278 篇 临床医学
- 243 篇 基础医学(可授医学...
- 197 篇 公共卫生与预防医...
- 131 篇 药学(可授医学、理...
141 篇 法学
- 124 篇 社会学
99 篇 农学
93 篇 经济学
- 92 篇 应用经济学
38 篇 教育学
20 篇 文学
6 篇 军事学
1 篇 艺术学

主题

362 篇 accuracy
262 篇 deep learning
204 篇 real-time system...
167 篇 machine learning
167 篇 convolutional ne...
157 篇 training
147 篇 feature extracti...
132 篇 predictive model...
119 篇 computational mo...
110 篇 support vector m...
109 篇 artificial intel...
94 篇 data models
93 篇 machine learning...
88 篇 internet of thin...
72 篇 scalability
71 篇 medical services
71 篇 optimization
71 篇 technological in...
68 篇 reliability
67 篇 security

机构

77 篇 maharishi school...
66 篇 department of ar...
59 篇 vishwakarma inst...
53 篇 centre of interd...
43 篇 department of ar...
42 篇 wangxuan institu...
36 篇 shenzhen institu...
35 篇 national institu...
34 篇 institute for ar...
32 篇 department of co...
31 篇 vishwakarma inst...
31 篇 department of el...
30 篇 gaoling school o...
30 篇 department of bi...
27 篇 institute of art...
26 篇 department of ar...
26 篇 university of ch...
26 篇 national enginee...
24 篇 school of artifi...
23 篇 centre of resear...

作者

30 篇 prateek verma
27 篇 mahalle parikshi...
23 篇 zhao dongyan
21 篇 parikshit n. mah...
20 篇 shen linlin
19 篇 hong shenda
15 篇 ishwarya m.v.
14 篇 mondal dipannita
14 篇 s. murugan
14 篇 yan rui
13 篇 seifedine kadry
13 篇 vimal s.
13 篇 liu qi
13 篇 dipannita mondal
13 篇 bhuvaneshwari k....
12 篇 aditya barhate
12 篇 liu yang
12 篇 murugan s.
12 篇 chen qingchao
12 篇 verma prateek

语言

2,876 篇 英文
1,075 篇 其他
26 篇 中文
2 篇 德文
2 篇 法文

检索条件"机构=Artificial Intelligence and Data Science Vishwakarma Institute of Technology"

共 3966 条记录，以下是21-30 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：

Attention Span and it's Correlation with Mental Health 1

Attention Span and it's Correlation with Mental Health

引用

1st International Conference on AIML-Applications for Engineering and technology, ICAET 2025

作者： Shah, Richa Bewoor, Laxmi Rak, Sarthak Patne, Ayush Vishwakarma Institute of Information Technology Artificial Intelligence and Data Science Pune India Vishwakarma Institute of Information Technology Computer Engineering Pune India

ISBN: (纸本)9798350355611

This paper delves into the correlation between attention span and mental health. Attention span is the ability to focus on a task before being distracted by certain factors. It ranges from 2 seconds to more than 20 minutes. Meanwhile, mental health constitutes a person's psychological, sociological, and emotional well-being. Using a clustering algorithm, this research seeks to provide a concrete relation between the two across an age group of 18-25. © 2025 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Next Word Prediction System Using NLP 1

Next Word Prediction System Using NLP

引用

1st IEEE International Conference on Smart Power Control and Renewable Energy, ICSPCRE 2024

作者： Patil, Ratna Dolas, Vaishnavi Godse, Ritesh Waghmare, Soham Chopade, Aniket Vishwakarma Institute of Information Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798350377002

This study focuses on Natural Language Processing (NLP) by developing a Next Word Prediction system utilizing Long Short-Term Memory (LSTM) networks. The system is built to take advantage of LSTM's capacity to capture temporal dependencies in text data using TensorFlow's Keras package. The major objective is to enhance content development and writing aid by precisely predicting the following word in a series. This will facilitate various apps, including virtual assistants., and increase typing speed. The first portion of the paper examines several NLP techniques., with a focus on Recurrent Neural Networks (RNNs) and some of their variants., including LSTM. The effectiveness of different architectural configurations and training methods is investigated through comprehensive testing and review to maximize predicted accuracy. The literature review sheds light on current methods., such as hybrid models., inflected language processing strategies., and deep learning architectures like Transformers. The methodology is informed by these sources and consists of preprocessing the data., modeling with Sequential LSTM architecture, and carrying out a comprehensive evaluation with metrics such as top-k accuracy and perplexity. Additional validation for the suggested approach comes from comparative evaluations using ablation experiments and baseline models. The results show that the LSTM-based model's high accuracy over a variety of datasets indicates its capacity to understand intricate linguistic patterns. Analyzing intricate systems., adding context., and modifying models for certain domains are a few possible areas for development. The project's end highlights the importance of LSTM networks in language modeling. © 2024 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Quora Question Duplication Detection: An ML Approach for Identifying Semantically Equivalent Questions 1st

Quora Question Duplication Detection: An ML Approach for Ide...

引用

1st International Conference on artificial intelligence Towards Smart Sustainable Society, AISSS 2023

作者： Mundargi, Zarinabegam Kalal, Sahil Kashyap, Aryan Kamble, Omkar Pande, Soham Mhamane, Saniya Department of Artificial Intelligence and Data Science Vishwakarma Institute of Technology Pune411037 India

ISBN: (纸本)9789819775910

This research paper delves into the field of Natural Language Understanding (NLU) by tackling the problem of identifying duplicate questions, using the Quora dataset as the primary source of data. Our study involves a comprehensive examination of the dataset and the application of machine learning techniques, specifically Random Forest and XGBoost models. Importantly, our results emphasize the efficiency of a straightforward CBOW neural network model, outperforming the effectiveness of more complex recurrent and attention-based models. The previous problem on Quora, characterized by numerous duplicate questions, has led to increased ambiguity and a diminished user experience. We also rigorously conduct error analysis, revealing subtleties and subjectivity in the dataset's labeling process. This investigation underscores the value of neural network-based approaches in tackling the complexities of duplicate question detection, which significantly contributes to the broader landscape of NLU research. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Next Word Prediction System using NLP

Next Word Prediction System using NLP

引用

2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Shivnani, Hiya Sontakke, Rashmi Sisode, Bhushan Puri, Pranesh Patil, Ratna Vishwakarma Institute of Information Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798350378092

This research paper introduces a novel statistical trigram language model designed for text prediction tasks, implemented using the Natural Language Toolkit (NLTK). The model is trained on the renowned 'Alice in Wonderland' corpus, leveraging a weighted random probability approach to predict the subsequent word in a provided phrase. A distinctive feature of this model is its user-controlled prediction termination, allowing individuals to determine when the prediction process should halt. To ensure data quality, the text undergoes rigorous preprocessing stages, eliminating superfluous characters and ensuring standardized tokenization into trigrams through NLTK's robust capabilities. The research not only presents the predictive model but also includes comprehensive n-gram statistics, offering insights into the underlying linguistic structures. Additionally, a visually informative frequency distribution plot showcasing the top 30 most common trigrams enriches the analysis, aiding in understanding the corpus's textual patterns. This paper contributes to advancing text prediction methodologies by combining statistical modeling, NLTK proficiency, and user interactivity, offering a valuable tool for language enthusiasts, researchers, and developers alike. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

DocGenie: A Retrieval-Augmented Generation Chatbot for Interactive PDF Exploration 3

DocGenie: A Retrieval-Augmented Generation Chatbot for Inter...

引用

3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Gawli, Palomi Kulkarni, Gauri More, Swapnil Mukkawar, Mitali Munde, Om Nachankar, Saloni Vishwakarma Institute of Technology Department of Artificial Intelligence and Data Science Pune India Vishwakarma University Department of Management Pune India

ISBN: (纸本)9798331509675

In order to overcome the drawbacks of conventional PDF readers, this article presents DocGenie, a cutting-edge tool that allows for dynamic and interactive document study. DocGenie improves user engagement and accessibility in document-intensive workflows by enabling effective querying, summarization, and contextual interaction through the use of Retrieval-Augmented Generation (RAG) and Google Gemini Pro. The accuracy, efficiency, and user satisfaction of DocGenie surpass those of traditional tools because to the use of cutting-edge techniques including document chunking, FAISS-based embedding storage, and real-time natural language processing. The platform is a major breakthrough in AI-driven document interaction because of its distinctive characteristics, which include multi-document querying, adaptive summarization, and multilingual support. This paper also identifies opportunities for improvement, such as support for a variety of file formats and improved multilingual capabilities, while highlighting DocGenie's potential uses in fields including education, legal research, and digital libraries. © 2025 IEEE.

关键词： AI Chatbot PDF Interaction Retrieval-Augmented Generation

来源：评论

学校读者我要写书评

暂无评论

Machine Learning in Action: Supervised Learning Models for Classifying Credit Card Fraud

Machine Learning in Action: Supervised Learning Models for C...

引用

2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Pendalwar, Rishab Verma, Aditya Patil, Ratna Vishwakarma Institute of Information Technology Dept. of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798350378092

Financial institutions face a relentless battle against fraudulent credit card transactions. Machine learning (ML) offers a promising approach for tackling this challenge. This paper explores six supervised machine learning models (Support Vector Machine (SVM), Random Forest, Naive Bayes, K-Nearest Neighbours (KNN), XGBoost, and LIGHT GBM) for detecting credit card fraud using a benchmark dataset. We explore the impact of dimensionality reduction with Principal Component Analysis (PCA) and data balancing with Generative Adversarial Networks (GANs) on imbalanced class distributions. The assessment relies on metrics such as accuracy, precision, recall, and F1-score. The results indicate that Random Forest demonstrates the best overall performance, especially when paired with GAN-based data balancing techniques. This study highlights the importance of addressing class imbalance and exploring dimensionality reduction techniques for enhancing credit card fraud detection capabilities. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Advanced Driving Assistance System: Real-Time Traffic Sign Detection and Driver Drowsiness Monitoring 15

Advanced Driving Assistance System: Real-Time Traffic Sign D...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Bailke, Preeti Khedkar, Sanskruti Kumbhar, Sanket Mohod, Khushi Mandalpure, Shantanu Vishwakarma Institute of Technology Department of Information Technology Pune India Vishwakarma Institute of Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798331300579

The Advanced Driver Assistance System (ADAS) has emerged as a critical technology for enhancing road safety and preventing *** research paper aims to provide a comprehensive study on the development and implementation of an ADAS through the utilization of a traffic sign detection Android *** of the key functionalities of the ADAS is real-time updates on the current speed of the *** constantly monitoring the speed, the system can provide timely warnings to the driver in case they exceed the speed limit, thereby reducing the likelihood of ac-accidents caused by *** integrates driver drowsiness detection using smart spectacles equipped with eye activity *** spectacles can monitor the driver's eye movements and identify signs of drowsiness or *** such cases, the system can issue alerts or recommendations to the driver, encouraging them to take a break or refocus their attention on the *** integrating these functionalities, the ADAS aims to enhance road safety, assist drivers with timely information and warnings, and ultimately reduce the risk of accidents on the roads. © Grenze Scientific Society, 2024.

关键词： Advanced driver assistance systems

来源：评论

学校读者我要写书评

暂无评论

IntelliMap: AI-Driven Terrain Exploration and Mapping 5

IntelliMap: AI-Driven Terrain Exploration and Mapping

引用

5th IEEE International Conference for Emerging technology, INCET 2024

作者： Adsul, Sanjivini Shah, Palak Pathak, Aneesh Pathak, Yadnesh Patil, Aditi Patil, Kundan Department of Artificial Intelligence and Data Science Vishwakarma Institute of Technology Maharashtra Pune411037 India

ISBN: (纸本)9798350361155

This study aims to explain the rationale and necessity of modelling 3D images of different landscapes and terrains in order to analyse their features and gain an overview of them using real-time techniques. As soldiers and intelligence agencies are known to constantly spy on one another, being able to see the topography and geography of their enemy's region in three dimensions would be extremely advantageous to them. In essence, these are all raised maps that are frequently utilised for mobile robot navigation in unfamiliar and unstructured *** navigator's primary responsibility is to update elevation maps dynamically in real time. The real-time photos we will be feeding our model are all the input data we receive from the security cameras mounted on it and the drone. Real-time mapping technology for digital elevation maps (DEMs) allows to comprehend the deformation of the continental crust at length scales of few metres. The combination of interactive rendering and interactive mapping directly onto the 3D surface, with the flexibility to travel the landscape and change viewpoints at will during mapping, is the primary strength of a model that transforms or provides a picture with 3D raised models. Consequently, several perspectives of the same landscape region or terrain can be *** automatic extraction of different types of information from images is the focus of computer vision. Allowing machines to see and interact with the world as people do is the primary goal of machine vision. However, the military and intelligence services can spy in enemy territory thanks to the advantages of computer vision. An army needs precise and accurate information about every move it will make as well as the surrounding conditions, as the latter are crucial to the operation or mission. For their operation to be successful, therefore, these real-time 3-D models that they have access to are crucial. They can interact with these three-dimensional models and extract any

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

AyUR-bot: A Revolutionary Ayurvedic Chatbot Empowered by Generative AI 8

AyUR-bot: A Revolutionary Ayurvedic Chatbot Empowered by Gen...

引用

8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Patil, Ratna Yeolekar, Suyash Khade, Omkar Kadam, Yash Ingole, Prajwal Patil, Suraj Vishwakarma Institute of Information Technology Department of Artificial Intelligence and Data Science Maharashtra Pune India

ISBN: (纸本)9798350391770

This study introduces AyUR-bot, a 24/7 Ayurvedic expert chatbot designed for prompt addressing of user queries on nutrition, remedies, and overall wellness. Project objectives include developing an Ayurvedic chatbot using NLP and deep learning, providing accurate responses, optimizing model efficiency, educating users about Ayurveda, and contributing to health and wellness through interactive conversations. The user-friendly chat interface allows effortless query submission. AyUR-bot leverages NLP tools, integrating the Llama 2 Large Language Model (LLM) and implementing Retrieval Augmented Generation (RAG) for question answering, optimizing Ayurvedic knowledge accessibility. The development process involves curating a specialized Ayurvedic document repository and utilizing the Llama 2 LLM model from Hugging Face. AyUR-bot ensures precise responses with unique stopping conditions. Components like the conversational retrieval chain, recursive character text splitter, and embeddings generator synergize for comprehensive responses. Evaluation with BERT Score validates AyUR-bot's effectiveness in delivering context-aware insights. The user-friendly interface enables interactive engagement, facilitating personalized Ayurvedic guidance. This research converges chatbot technology, NLP, and Ayurveda, aligned with project objectives, catering to the growing interest in traditional wellness, democratizing access to Ayurvedic wisdom. AyUR-bot results in a significant advancement in personalized Ayurvedic assistance. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

FitTip: Merging technology and Fitness for Posture Improvement 3

FitTip: Merging Technology and Fitness for Posture Improveme...

引用

3rd International Conference on Trends in Electrical, Electronics and Computer Engineering, TEECCON 2024

作者： Tembhurnikar, Atharv Sarvankar, Girish Yadav, Gitanjali Vaidya, Rohan Shelar, Aditya Bhage, Kartik Vishwakarma Institute of Information Technology Dept. of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798331505714

Poor form is a primary contributor to exercise-related accidents, which can result in permanent physical handicap and deter people from maintaining a regular fitness regimen. This study suggests FitTip, an intelligent posture identification and correction device that uses computer vision and machine learning, as a means of preventing these kinds of injuries. Using a proprietary dataset of yoga and gym routines, we developed a convolutional neural network (CNN) integrated with the Mediapipe framework to accurately categorize and correct workout positions in real time. Position analysis is used in FitTip' s design to provide real-time feedback and change recommendations. The algorithm was evaluated on a dataset of five workout poses, and the results indicated that it could get 98.73% training and validation accuracy. These findings show how well algorithm works to improve overall fitness results and workout safety. The suggested algorithm offers a framework that is scalable for enhancing posture during activity, and it may eventually be integrated with wearables and fitness applications. It includes a real-time camera feed for pose detection, a key-point detection module, and a feedback algorithm that suggests corrections based on the angles between body joints. This paper also addresses challenges such as limited dataset size and variability in user movements, proposing solutions through enhanced preprocessing and pose analysis techniques. FitTip algorithm makes training safer and more accessible for people of all fitness levels, which adds to the expanding field of fitness technology. © 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

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397页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：