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

408 篇 期刊文献
42 篇 会议

馆藏范围

450 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

394 篇 理学
- 355 篇 物理学
- 35 篇 地球物理学
- 10 篇 天文学
- 8 篇 数学
- 7 篇 生物学
- 7 篇 统计学（可授理学、...
- 6 篇 化学
- 4 篇 海洋科学
- 4 篇 地质学
- 3 篇 大气科学
- 2 篇 系统科学
140 篇 工学
- 76 篇 核科学与技术
- 31 篇 仪器科学与技术
- 19 篇 计算机科学与技术...
- 17 篇 软件工程
- 12 篇 电子科学与技术（可...
- 7 篇 航空宇航科学与技...
- 6 篇 信息与通信工程
- 6 篇 生物工程
- 5 篇 光学工程
- 5 篇 控制科学与工程
- 4 篇 冶金工程
- 4 篇 化学工程与技术
- 3 篇 电气工程
- 3 篇 安全科学与工程
- 2 篇 材料科学与工程（可...
- 2 篇 动力工程及工程热...
14 篇 医学
- 12 篇 临床医学
- 7 篇 基础医学(可授医学...
- 3 篇 公共卫生与预防医...
3 篇 管理学
1 篇 农学

主题

51 篇 higgs bosons
47 篇 proton-proton in...
46 篇 hadron colliders
35 篇 large hadron col...
35 篇 standard model (...
29 篇 collisions (nucl...
29 篇 nuclear counters
23 篇 quarks
21 篇 supersymmetric m...
20 篇 cross sections (...
20 篇 hadron-hadron sc...
19 篇 leptons (nuclear...
19 篇 top quark
19 篇 extensions of hi...
19 篇 quark & gluon je...
18 篇 particle data an...
17 篇 supersymmetry
16 篇 particle product...
16 篇 relativistic hea...
15 篇 quantum chromody...

机构

339 篇 faculty of scien...
339 篇 department for p...
336 篇 kirchhoff-instit...
332 篇 institute of phy...
326 篇 department of ph...
326 篇 instituto de fís...
320 篇 department of ph...
318 篇 institute of phy...
311 篇 department of ph...
307 篇 department of ph...
304 篇 nikhef national ...
300 篇 fakultät für phy...
278 篇 dipartimento di ...
278 篇 department of ph...
262 篇 departamento de ...
256 篇 graduate school ...
256 篇 department of ph...
248 篇 faculté des scie...
239 篇 physics departme...
235 篇 department of ph...

作者

282 篇 c. alexa
282 篇 g. bella
282 篇 d. calvet
282 篇 c. amelung
280 篇 j. strandberg
280 篇 g. spigo
280 篇 f. siegert
279 篇 j. m. izen
275 篇 m. klein
275 篇 r. ströhmer
275 篇 m. rijssenbeek
275 篇 s. jin
275 篇 g. gaudio
275 篇 s. mohapatra
274 篇 h. a. gordon
273 篇 s. guindon
273 篇 a. kaczmarska
272 篇 j. schaarschmidt
268 篇 a. d. pilkington
264 篇 l. chevalier

语言

429 篇 英文
21 篇 其他

检索条件"机构=School of Computer Science and Engineering V.I.T"

共 450 条记录，以下是1-10 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：

Algorithms for Fault Detection and Diagnosis in Wireless Sensor Networks Using Deep Learning and Machine Learning - An Overview 10

Algorithms for Fault Detection and Diagnosis in Wireless Sen...

引用

10th international Conference on Communication and Signal Processing, iCCSP 2024

作者： iswarya, P. Manikandan, K. School of Computer Science and Engineering V.I.T TamilNadu Vellore India

ISBN: (纸本)9798350353068

the integration of artificial intelligence (Ai) with wireless sensor networks (WSN) has created several possibilities, making it a highly discussed topic in the technological realm and holds promise for optimizing data gathering, analysis, and decision-making across diverse domains. the amalgamation of Artificial intelligence (Ai) and Wireless Sensor Networks (WSN) possesses immense potential for diverse sectors and domains. incorporating Artificial intelligence (Ai) with Wireless Sensor Networks (WSN) can revolutionize many sectors, enhancing their efficiency, productivity, and sustainability. WSNs are made up of numerous low-power and affordable sensor nodes placed in surroundings for a range of military and commercial uses. WSNs are susceptible to various types of faults, including interaction errors, equipment errors, defects in software, link errors, node defects, energy discharge, and physical damage. Due to inexpensive chips, sensor nodes can become unreliable or defective. When faulty nodes lose the ability to interact with the remaining nodes in the wireless system. Even though they may still be operational, they can start transmitting incorrect data to the other nodes, ultimately impacting the operational efficiency of WSNs. to ensure successful networking, sensor nodes need reliable fault identification and diagnosis techniques. the study on fault diagnosis will prioritize data quality, enhance response time, and prolong the network lifetime. this paper explores different fault identification and diagnosis methods and algorithms across various industries over the past five years. this paper assesses the effectiveness of current artificial intelligence-driven fault identification algorithms and suggests potential areas for future research in artificial intelligence. © 2024 iEEE.

关键词： Fault detection

来源：评论

学校读者我要写书评

暂无评论

Content-Based Radar image Retrieval Using CNN Models

Content-Based Radar Image Retrieval Using CNN Models

引用

2024 international Conference on intelligent Computing and Sustainable innovations in technology, iC-Sit 2024

作者： Choudhury, Bishal Rajakumar, K. Sarkar, Uddipan Barnawal, Aman Kasetty, Sai Bhargav Manikandan, S. V.I.T School of Computer Science and Engineering Tamilnadu Vellore India DRDO Karnataka Bangalore India

ISBN: (纸本)9798350369175

this study introduces a technique, for content based image retrieval (CBiR) specifically designed for radar image datasets, which are known for their complexity and high dimensionality. Achieving an precision (mAP) of 93.6% and an impressive retrieval accuracy of 94.8% the proposed system leverages advanced machine learning methods to enhance retrieval precision and efficiency. Additionally the system demonstrates a 35% reduction in retrieval time compared to state of the art approaches. A comprehensive evaluation was conducted, encompassing performance metrics, confusion matrices and detailed tabular analysis to validate these findings. For applications requiring accurate image retrieval these studies underscore the systems ability to handle radar image datasets with increased precision and speed thereby substantiating its effectiveness. the robustness and efficacy of the proposed method indicate its potential for application across disciplines where radar imaging is essential. © 2024 iEEE.

关键词： Radar imaging

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Advanced Models for Satellite-Based Aircraft identification

Comparative Analysis of Advanced Models for Satellite-Based ...

引用

2024 international Conference on Smart Systems for Electrical, Electronics, Communication and computer engineering, iCSSEEC 2024

作者： Choudhury, Bishal Rajakumar, K. Badhale, Anshul Anand Roy, Aadrit Sahoo, Riddhiman Margret, issac Neha School of Computer Science and Engineering V.I. T Tamilnadu Vellore India

ISBN: (纸本)9798350378177

in modern aviation, accurate aircraft identification from satellite imagery is critical in the defense, security, and environmental monitoring sectors. Still, distinguishing between different types of aircraft in intricate visual datasets is a difficult task. this study addresses this by optimizing seven well-known models-inception, vGG, AlexNet, ResNet, DenseNet, MobileNet, and EfficientNet-for image classification, with an emphasis on aircraft imagery from Kaggle datasets. this is done by applying cutting-edge deep learning techniques. Four stages of the research are described in detail: building and training these architectures-based Convolutional Neural Networks (CNNs), conducting a thorough model evaluation using metrics such as accuracy and precision, investigating prediction visualization, and showcasing various visualizations. through the integration of cutting-edge algorithms, theoretical foundations, and empirical verification, the research introduces a novel and revolutionary method for aircraft identification using satellite imagery. in addition to advancing computer vision, the approaches and insights have great potential to improve the effectiveness and precision of aircraft identification systems, which will benefit industries that depend on aerial intelligence. © 2024 iEEE.

关键词： Satellite imagery

来源：评论

学校读者我要写书评

暂无评论

A Meta-Analysis of Machine Learning Models in Pregnancy Care and Applications 10

A Meta-Analysis of Machine Learning Models in Pregnancy Care...

引用

10th international Conference on Communication and Signal Processing, iCCSP 2024

作者： Margret, issac Neha Rajakumar, K. V. I. T School of Computer Science & Engineering Tamilnadu Vellore India

ISBN: (纸本)9798350353068

Examining the efficacy of machine learning-based box models in pregnancy care, this meta-analysis delves into diverse models - white, grey, and black box variants - to predict childbirth types, delivery modes, and mortality risks. the methodology integrates Random Forest, Logistic Regression, Neural Networks, and others, analyzing data ranging from demographics to genetic information. Results showcase model versatility in the accurate risk assessments for maternal and fetal health. Challenges include interpretability, healthcare system integration, and data quality. in conclusion, the study underscores machine learning's transformative potential in pregnancy care, emphasizing the need for ongoing research to enhance interpretability, address limitations, and optimize integration into routine prenatal care for improved outcomes. © 2024 iEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

Understanding Satellite image Processing and Black Box Models with Ante-Hoc and Post-Hoc Explanations in Deep Learning 10

Understanding Satellite Image Processing and Black Box Model...

引用

10th international Conference on Communication and Signal Processing, iCCSP 2024

作者： Kasetty, Sai Bhargav Rajakumar, K. V. I. T School of Computer Science & Engineering Tamilnadu Vellore India

ISBN: (纸本)9798350353068

this research aims to investigate the challenges of using black box models in deep learning and analyzing satellite images through a thorough meta-analysis. the main goal of the study is to improve transparency and interpretability, with a focus on providing explanations both before and after model training. transparency elements are integrated into models during the initial stages to enhance their clarity. Following the completion of training for complex models, explanations are utilized to comprehend how decisions are made. the research focuses on using both of these approaches to tackle the issues linked with deep learning models in satellite image processing. through the use of design-time and post-modeling methods, Ai can be used for analyzing satellite images in a way that is easier to understand and accountable. © 2024 iEEE.

关键词： transparency

来源：评论

学校读者我要写书评

暂无评论

Algorithms for Fault Detection and Diagnosis in Wireless Sensor Networks Using Deep Learning and Machine Learning - An Overview

Algorithms for Fault Detection and Diagnosis in Wireless Sen...

引用

international Conference on Communications and Signal Processing

作者： P iswarya K Manikandan School of Computer Science and Engineering V.I.T Vellore TamilNadu India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

关键词： Fault diagnosis Deep learning Wireless communication Wireless sensor networks Machine learning algorithms Fault detection Signal processing algorithms

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Driven Black Box Approach For image Segmentation 1

Deep Learning-Driven Black Box Approach For Image Segmentati...

引用

1st iEEE international Conference on Advances in Computing, Communication and Networking, iCAC2N 2024

作者： Sudha, Nuthalapati Kasetty, Sai Bhargav Madhuri, K. Sai Nikitha, Jajala Margret, issac Neha Rajakumar, K. Mahindra University School of Engineering Telangana Hyderabad India V.I.T - University School of Computer Science and Engineering Tamilnadu Vellore India BVRIT Narsapur Dept. of Computer Science and Data Science Telangana Hyderabad India VNR VIET Dept. of CSE - AIML and IoT Telangana Hyderabad India

ISBN: (纸本)9798350356816

the diagnosis of a range of eye disorders needs to categorize the retinal vessels. computerized implementation of this process is becoming increasingly essential for automated screening systems for retinal diseases. to achieve a more accurate extraction of the retinal vessels, a new pre-processing step is proposed. these proposed pre-processes are also compared to other algorithms to assess their impact. the proposed pre-processing process consists of two phases. the first phase is the implementation and validation of the pre-processing modules, and the second phase is the implementation of these pre-processes onto the retinal vessels that were to be extracted. to achieve a significantly improved segmented vessel image, the proposed pre-process phase employs a common image-processing technique. in recent years, there has been a great deal of focus on retinal vessel identification studies, and the importance of assessing and confirming the findings of retinal vessel segmentation. © 2024 iEEE.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Machine Learning and Deep Learning Approach for Diabetes Prediction with a tkinter-Based User interface

A Hybrid Machine Learning and Deep Learning Approach for Dia...

引用

2024 international Conference on intelligent Computing and Sustainable innovations in technology, iC-Sit 2024

作者： Kasetty, Sai Bhargav Margret, issac Neha Madhuri, K. Sai Ojha, Rajesh Kumar Sudha, Nuthalapati Rajakumar, K. V.I.T University SCOPE Tamilnadu Vellore India Data Science BVRIT Narsapur Dept. of CSE Telangana Hyderabad India Silicon University Dept. of Computer Science & Engineering Odisha Bhubaneswar India Mahindra University School of Engineering Telangana Hyderabad India

ISBN: (纸本)9798350369175

Diabetes prediction is a critical task in healthcare that can significantly benefit from advancements in machine learning and deep learning technologies. this paper presents a hybrid approach combining deep learning and traditional machine learning models for diabetes prediction. the proposed system integrates a tkinter-based Graphical User interface (GUi) to make it easier for users to interact and make predictions. in our discussion, we will cover the design and implementation of the system, and evaluate the performance of different models using precision, F1 score, recall, and, accuracy to provide insights into their effectiveness. Results demonstrate the efficacy of the hybrid approach, with a focus on model accuracy and user experience. © 2024 iEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Content-Based Radar image Retrieval Using CNN Models

Content-Based Radar Image Retrieval Using CNN Models

引用

intelligent Computing and Sustainable innovations in technology (iC-Sit), international Conference on

作者： Bishal Choudhury K Rajakumar Uddipan Sarkar Aman Barnawal Sai Bhargav Kasetty S Manikandan School of Computer Science and Engineering V.I.T Vellore Tamilnadu India DRDO Bangalore Karnataka India

ISBN: (数字)9798350369175

ISBN: (纸本)9798350369182

关键词： Measurement technological innovation Accuracy Computational modeling image retrieval Confusion matrices Machine learning Radar imaging Robustness Complexity theory

来源：评论

学校读者我要写书评

暂无评论

Advanced Deep Learning Approaches for Content-Based image Retrieval System in Skin Cancer Diagnostics

Advanced Deep Learning Approaches for Content-Based Image Re...

引用

2024 international Conference on intelligent Computing and Sustainable innovations in technology, iC-Sit 2024

作者： Margret, issac Neha Kasetty, Sai Bhargav Sudha, Nuthalapati Ojha, Rajesh Kumar Madhuri, K. Sai Rajakumar, K. V.I.T University SCOPE Tamilnadu Vellore India CYS VNR VJIET Dept. of CSE - DS AI&DS Telangana Hyderabad India Silicon University Dept. of Computer Science & Engineering Odisha Bhubaneswar India BVRIT Dept. of CSE - Data Science Telangana Narsapur Hyderabad India

ISBN: (纸本)9798350369175

the objective of this paper is to develop and assess the performance of a deep learning model-based content skin cancer detection image retrieval system. in this regard, CNN, vGGNet, ResNet, DenseNet, inceptionNet, and MobileNet were tested on recall, accuracy, mean average precision, F1, and precision metrics. vGGNet performed best among them, with an accuracy of 92.3%, outperforming all other models in precision, F1-score, and recall. CNN also gave the best performance with 91.5% accuracy. the CBiR system retrieved relevant images for the given lesions, especially melanoma lesions, which were relevant and high in precision within the top 5 retrieved images. these results also confirm the efficiency of CNN and vGGNet in enhancing accuracy during the retrieval of skin cancer diagnosis images. © 2024 iEEE.

关键词： Contrastive Learning

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45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：