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

13,794 篇 会议
7,643 篇 期刊文献
257 册 图书

馆藏范围

21,694 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

13,432 篇 工学
- 10,387 篇 计算机科学与技术...
- 8,664 篇 软件工程
- 3,407 篇 信息与通信工程
- 2,159 篇 控制科学与工程
- 1,904 篇 生物工程
- 1,591 篇 电气工程
- 1,407 篇 生物医学工程（可授...
- 1,170 篇 光学工程
- 1,168 篇 电子科学与技术（可...
- 830 篇 网络空间安全
- 791 篇 机械工程
- 677 篇 安全科学与工程
- 633 篇 动力工程及工程热...
- 592 篇 交通运输工程
- 584 篇 仪器科学与技术
- 556 篇 化学工程与技术
6,835 篇 理学
- 3,488 篇 数学
- 2,089 篇 生物学
- 1,771 篇 物理学
- 1,218 篇 统计学（可授理学、...
- 742 篇 系统科学
- 654 篇 化学
4,012 篇 管理学
- 2,426 篇 管理科学与工程(可...
- 1,767 篇 图书情报与档案管...
- 1,067 篇 工商管理
1,562 篇 医学
- 1,221 篇 临床医学
- 1,119 篇 基础医学(可授医学...
- 820 篇 公共卫生与预防医...
- 655 篇 药学(可授医学、理...
848 篇 法学
- 701 篇 社会学
373 篇 经济学
334 篇 农学
236 篇 教育学
183 篇 文学
32 篇 军事学
28 篇 艺术学
5 篇 哲学
3 篇 历史学

主题

921 篇 deep learning
849 篇 accuracy
534 篇 computational mo...
484 篇 machine learning
464 篇 feature extracti...
447 篇 training
393 篇 real-time system...
387 篇 predictive model...
370 篇 internet of thin...
317 篇 support vector m...
316 篇 convolutional ne...
285 篇 computer science
280 篇 semantics
271 篇 data models
256 篇 optimization
230 篇 neural networks
221 篇 computer archite...
214 篇 reliability
214 篇 scalability
204 篇 image segmentati...

机构

253 篇 department of co...
153 篇 school of comput...
140 篇 school of comput...
136 篇 school of comput...
127 篇 school of comput...
121 篇 department of co...
112 篇 school of comput...
111 篇 school of comput...
106 篇 department of co...
101 篇 college of compu...
101 篇 national enginee...
101 篇 department of co...
97 篇 school of comput...
95 篇 department of co...
95 篇 department of co...
93 篇 north-west unive...
93 篇 institut univers...
88 篇 national centre ...
87 篇 infn sezione di ...
83 篇 tno technical sc...

作者

123 篇 niyato dusit
96 篇 ferrara g.
96 篇 ardid m.
95 篇 calvo d.
92 篇 chen a.
89 篇 gal t.
89 篇 bozza c.
88 篇 anjali t.
88 篇 díaz a.f.
87 篇 boumaaza j.
85 篇 zheng wei-shi
85 篇 coleiro a.
84 篇 gozzini s.r.
82 篇 dallier r.
73 篇 kalekin o.
66 篇 anguita m.
64 篇 boettcher m.
63 篇 huang f.
61 篇 kulikovskiy v.
55 篇 enzenhöfer a.

语言

17,418 篇 英文
4,166 篇 其他
167 篇 中文
2 篇 法文
1 篇 德文
1 篇 日文
1 篇 朝鲜文
1 篇 斯洛文尼亚文

检索条件"机构=MTech Computer Science and Engineering School of Computing Science and Engineering"

共 21694 条记录，以下是781-790 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：

Robust Hybrid Model for Social Media Sentiment Analysis 15

Robust Hybrid Model for Social Media Sentiment Analysis

引用

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

作者： Jahnavi, Dingari Sami, Sasank Pulata, Sandeep Bharathi Mohan, G. Prasanna Kumar, R. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer science And Engineering Chennai India

ISBN: (纸本)9798350370249

Social media platforms are home to massive amounts of content created by users, which can offer insightful information on attitudes, beliefs, and feelings. In order to extract valuable information from the abundance of data, sentiment analysis is essential. This work presents a novel hybrid sentiment analysis model using the Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT Approach (RoBERTa) models. The strategy tries to improve sentiment classification performance by utilizing the advantages of both models. The complexities of social media text are often difficult for traditional sentiment analysis models, like rule-based systems and machine learning algorithms like logistic regression and support vector machines, to capture because of issues with contextual understanding, linguistic complexity, inherent data variability, and noise. This hybrid sentiment analysis, on the other hand, excels at understanding natural language semantics and gathering contextual information. Labelled data and an innovative training approach are combined to train the model. Reporting accuracy metrics is part of the performance evaluation process when using a test dataset. Additionally, a thorough classification report and confusion matrix are produced. A test dataset performance evaluation yields an accuracy of 82%. © 2024 IEEE.

关键词： Accuracy metrics BERT Confusion Matrix Hybrid model Machine learning RoBERTa Sentiment Analysis Transformers

来源：评论

学校读者我要写书评

暂无评论

Bert-Based Transformer Model for Hate Speech Detection 5

Bert-Based Transformer Model for Hate Speech Detection

引用

5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Vardhan, Puvvadi Harsha Prasad, Hari Swaroop, Bandi Vishnu Reddy, Busa Thanuj Sathwik Venugopalan, Manju Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350376685

Hate speech recognition has emerged as a key problem in social media and should be addressed using multiple models. Machine learning models like CNN and LSTM have been used recently in creating successful hate-speech detection models that have been developed in the recent past but they have not proved to be highly discriminative. The use of BERT or any other transformer model will give increased performance owing to the ability of these models to grasp context. Other potential improvements include using new feature engineering techniques and ensemble methods in conjunction with these models. The datasetused for experimentation in the proposed work is annotated considering three categories hate, offensive, or normal. The proposed methodology has incorporated a data-balancing mechanism and experimented with a range of classifier models that belong to ML and DL models and the best results were reported for Bert based transformer model which is F1-score of 0.76. © 2024 IEEE.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Travel Destination Recommendation System based on Machine Learning by Analyzing Instagram Review Comments and Hashtags 5

Travel Destination Recommendation System based on Machine Le...

引用

5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Sruthi, M.S. Krishna, Arathy Anu Prabhar, S. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798350376685

This project aims to develop an advanced hybrid travel recommendation system that leverages emotion extraction from user comments and visual recognition from images to provide personalized travel suggestions. The system integrates three distinct datasets an image dataset, a custom dataset containing location details, sublocation information, user comments, and hashtags, and a user interaction dataset comprising user IDs, locations, and ratings. Emotion extraction is performed exclusively on user comments to capture sentiments, while visual recognition is applied to images to identify and classify visual *** recommendation system employs a hybrid approach, combining collaborative filtering and content-based filtering techniques. Collaborative filtering utilizes user interaction data to identify similarities between users and recommend locations based on their ratings. Content-based filtering, on the other hand, analyzes user posts, comments, and hashtags to recommend locations and sublocations that match the user's preferences and *** enhance user engagement and accessibility, a user interface is developed, allowing users to input their posts (images and captions) and receive personalized travel recommendations. This interface not only makes the system user-friendly but also facilitates seamless interaction, providing users with insightful travel suggestions based on their unique ***, this project demonstrates the effectiveness of integrating emotion extraction and visual recognition into a hybrid recommendation system, offering a sophisticated solution for personalized travel planning and exploration. © 2024 IEEE.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Cookie Analysis Using Web Crawling and Web Scraping 14

Cookie Analysis Using Web Crawling and Web Scraping

引用

14th International Conference on Cloud computing, Data science and engineering, Confluence 2024

作者： Bhatraju, Gowtham Pushkar Vikas, Chilakala Saranya, G. Amrita School of Computing Amrita Vishwa Vidhyapeetham Department of Computer Science Engineering Chennai India

ISBN: (纸本)9798350344837

On the contemporary web, cookies are pervasive and serve as crucial instruments used by developers of websites, marketers, and companies to improve user experience and acquire useful data. Because of concerns over user privacy and data security, the moral use of cookies has come under examination. This paper presents a new approach to cookie analysis. This paper's primary objective is to develop an approach for analyzing cookies on websites to assess their compliance with privacy regulations, potential security risks, and overall impact on user experience. The effective use of web crawlers and web scrapers to gather cookies and examine their behavior is covered in this paper. © 2024 IEEE.

关键词： Websites

来源：评论

学校读者我要写书评

暂无评论

Enhancing Bird Species Classification with PaliGemma and Custom EfficientNet Architectures 8

Enhancing Bird Species Classification with PaliGemma and Cus...

引用

8th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2024

作者： Bayyapureddi, Medhovarsh Harshitha, Lakshmi Sri Anjali, T. Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798350367904

Bird species classification is a critical task in biodiversity studies, ecological research, and conservation efforts. Our research presents a comprehensive approach to bird species classification using a custom-modified EfficientNet-B0 model, enhanced with a Squeeze-and-Excitation (SE) block to improve feature sensitivity. The dataset used comprises a diverse collection of bird images, which are preprocessed and split into training, validation, and test sets. The custom model incorporates the SE block into the EfficientNet-B0 structure, with a dropout layer and a connected layer added for classification. Using an additional Squeeze-and-Excitation (SE) block to improve feature sensitivity and a specifically tailored EfficientNet-B0 model, our work provides a comprehensive approach to bird species classification. The dataset consists ofseveral hundred preprocessed images of birds, split into test, validation, and training sets. For classification, the dropout layer and connected layer are added, and the custom model integrates the SE block into the EfficientNet-B0 framework. In our model design, the learning rate is adjusted as needed using a learning rate scheduler, and SGD is employed for model training. The findings show that the custom EfficientNet-B0 model boosts classification accuracy highlighting how well the SE block works to improve model *** paper shows deep learning methods for animal tracking and conservation. Index Terms- Convolutional Neural Networks (CNNs), Squeeze-and-Excitation block, Deep learning, EfficientNet-B0,Fine-grained Image Classification Bird Species Classification neural networks wildlife monitoring pali jewel © 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

TripleACrypt: Cryptography and Steganography for the Preservation of Ancient Discoveries 8

TripleACrypt: Cryptography and Steganography for the Preserv...

引用

8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： George, Angelina Ashik, F. Jose, Alphonsa Kavitha, C.R. Amrita School of Computing Department of Computer Science & Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331505462

'Steganocryptic Repositories' is an idea that incorporates cryptographic techniques with steganographic ones to preserve India's manuscript heritage in the digital age. Ancient manuscripts are encrypted with the AES technique, guaranteeing their security. An additional degree of protection is added by using the RSA technique to encrypt the key used in the AES encryption process. Additionally, this combination requires encoding the colors of high-resolution digital scans with the RSA encryption key including the encrypted manuscript, which is accomplished by hiding detailed metadata related to the manuscripts using the Least Significant Bit (LSB) approach. Use of Streamlit and ngrok allow for safe and easy to use frontend for the application. While Streamlit creates an interactive Graphical User Interface (GUI) for the application, ngrok ensures secure access to it. This method preserves and makes available the vast cultural knowledge contained in India's manuscripts by giving researchers and scholars access to decryption keys, ensuring secure access. This also preserves and reveals the mysteries of India's literary and historical heritage for the benefit of future generations. © 2024 IEEE.

关键词： AES Encryption Digital Preservation Least Significant Bit (LSB) Approach Manuscript Heritage Metadata Encryption ngrok RSA Encryption Steganography Streamlit

来源：评论

学校读者我要写书评

暂无评论

An Ensemble based Convolutional Neural Network modelling for Classifying Marine Animal types 15

An Ensemble based Convolutional Neural Network modelling for...

引用

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

作者： Talluri, Charitha Sagi, Shriya Samitha, V. Kavitha, C.R. Amrita Vishwa Vidyapeetham Amrita School of Computing Dept of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350370249

Studying Biodiversity and ecological monitoring, in classification of marine animal's category is important. This paper tells how comprehensive analysis and comparison is done among the deep learning models that have been implemented. InceptionV3, MobileNetv1, EfficientNetB0 and Vision Transformer(ViT) are the four convolutional neural network models used in this process. DataSet was taken from kaggle with 13,512 images of 23 different categories in different environmental conditions. Each model is trained independently with dataset and evaluated with the marine animal images. After comparing all these four individual models using their metrics, we considered to build an ensemble approach that sums up the advantages of these models which helps in enhancing the performance. This study not only showcases how advance the models are, but also the explains the use of ensemble approaches for increasing the efficiency. © 2024 IEEE.

关键词： Classification CNN Dropout layers EfficientNetB0 InceptionV3 MobileNetV1 Optimizer Vision Transformer(ViT) Ensemble model

来源：评论

学校读者我要写书评

暂无评论

Music Recommendation System based on Big Data using Pyspark 9

Music Recommendation System based on Big Data using Pyspark

引用

9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Jain, Nikunj Sah, Nabin Kumar Hawari, Jawed Khare, Sangita Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350394474

In the evolving landscape of digital music consumption, personalized song recommendation systems play a pivotal role in enhancing user engagement and satisfaction. This article presents an in-depth exploration and analysis of an innovative song recommendation framework designed to address the challenges of delivering tailored music experiences. Utilizing advanced machine learning techniques, especially K-Means Clustering Algorithm and data analytics, the proposed system aims to offer song suggestions according to user preferences. The proposed system introduces a hybrid song recommendation system that combines the two distinct approaches i.e. Content and Collaborative based filtering. Various algorithms were implemented for Content based filtering whereas Hadoop and Pyspark was used for implementation of Collaborative filtering. Wide research and Evaluations based on various metrics were considered. The research also draws the strengths and drawbacks or limitations of Content based Recommendation over Collaborative based Recommendation System. The results highlight the system's capability to overcome limitations eventually enhancing user experience by offering a better experience. © 2024 IEEE.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Crypto Prophets: Machine Learning Oracles for Price Forecasting

Crypto Prophets: Machine Learning Oracles for Price Forecast...

引用

2024 International Conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Baghavathi Priya, S. Srinivasan Anusha, Janani Priyanga, S. Chatiyode, Veda Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331541170

Cryptocurrency has emerged as a revolutionary financial asset, captivating investors and researchers alike with its volatile nature and potential for high returns. As the market continues to evolve, there is an increasing need for sophisticated tools to predict price movements and inform investment decisions. This research work delves into a predictive assessment of cryptocurrency price fluctuations, using thorough machine learning techniques to project future prices for Monero, Ethereum, Wrapped Bitcoin, and Bitcoin - the four leading cryptocurrencies. Using historical price data, our methodology includes data preprocessing, feature selection, and the application of various machine learning models such as Linear Regression, Extreme Gradient Boosting (XGBoost), K-Nearest Neighbors (KNN), Random Forest, and Support Vector Regression (SVR). The models' predictive performance was meticulously evaluated using Mean Squared Error (MSE), R-squared (R2), and Mean Absolute Percentage Error (MAPE). Linear Regression achieved superior performance for Bitcoin with an R2 score of 0.9823 and Wrapped Bitcoin with an R2 score of 0.9780, while XG-Boost excelled in Monero predictions with the lowest MSE of 325.33. This research offers critical insights for investors, market strategists, and financial analysts, underscoring the prominent impact of machine learning in enhancing the market analysis of cryptocurrencies and informing decision-making processes. The work immensely contributes to the flourishing area of financial technology, suggesting various ways to move forward with integrated advanced predictive models and sentiment analysis of markets and economic indicators to redefine investment strategies in the highly volatile cryptocurrency domain. © 2024 IEEE.

关键词： Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Space Debris Clustering and Avoidance Using Chrono-Spatial Computational Frameworks

Space Debris Clustering and Avoidance Using Chrono-Spatial C...

引用

2024 IEEE International Conference on Intelligent computing and Emerging Communication Technologies, ICEC 2024

作者： Reddy V, Sathvik Kothapalli, Aditya Sahithya Varshini, K Sai Nandhan R, Raghu Vineetha, K.V. Ullas, S. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508432

This paper investigates the utilization of Spatio-Temporal data structures, their applications and how they can be implemented. This study also explores the temporal data management of spatial data that is dynamic in nature. Moreover, this integration of appropriate temporal aspects to the spatial data structures like Quad Tree is explored, thus the concept of Spatio-temporal data structures is developed. One of the primary takeaways from this paper is that it incorporates convex hull algorithm into the cluster management systems. This integration is exemplified in the context of spacecraft path optimization during orbital missions and the clustering of space debris in the atmosphere of the earth. The interaction will allow users to model rocket trajectories, so it would be possible to identify the optimum outputs. © 2024 IEEE.

关键词： Space debris

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 << < 75 76 77 78 79 80 81 82 83 84 > >>

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：