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

22,374 篇 会议
3,583 篇 期刊文献
210 册 图书

馆藏范围

26,167 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

16,013 篇 工学
- 11,279 篇 计算机科学与技术...
- 9,442 篇 软件工程
- 4,331 篇 信息与通信工程
- 2,540 篇 控制科学与工程
- 2,175 篇 电子科学与技术（可...
- 2,157 篇 电气工程
- 1,538 篇 生物工程
- 1,320 篇 生物医学工程（可授...
- 1,135 篇 光学工程
- 1,033 篇 机械工程
- 895 篇 仪器科学与技术
- 863 篇 动力工程及工程热...
- 743 篇 化学工程与技术
- 637 篇 安全科学与工程
- 531 篇 交通运输工程
- 473 篇 材料科学与工程（可...
8,287 篇 理学
- 4,554 篇 数学
- 2,430 篇 物理学
- 1,705 篇 生物学
- 1,393 篇 统计学（可授理学、...
- 932 篇 系统科学
- 758 篇 化学
4,054 篇 管理学
- 2,442 篇 管理科学与工程(可...
- 1,851 篇 图书情报与档案管...
- 1,286 篇 工商管理
1,077 篇 医学
- 952 篇 临床医学
- 886 篇 基础医学(可授医学...
- 572 篇 药学(可授医学、理...
716 篇 法学
- 565 篇 社会学
454 篇 经济学
- 452 篇 应用经济学
354 篇 教育学
326 篇 农学
110 篇 文学
73 篇 军事学
26 篇 艺术学
4 篇 哲学
3 篇 历史学

主题

730 篇 accuracy
543 篇 feature extracti...
502 篇 deep learning
493 篇 computational mo...
389 篇 training
385 篇 support vector m...
370 篇 computer science
326 篇 internet of thin...
311 篇 computer archite...
300 篇 real-time system...
289 篇 machine learning
248 篇 predictive model...
229 篇 reliability
226 篇 routing
221 篇 convolutional ne...
217 篇 optimization
206 篇 neural networks
205 篇 data mining
204 篇 throughput
188 篇 image segmentati...

机构

86 篇 dept. of compute...
84 篇 institut univers...
84 篇 université de st...
83 篇 north-west unive...
83 篇 tno technical sc...
82 篇 infn sezione di ...
81 篇 national centre ...
80 篇 nikhef national ...
76 篇 infn sezione di ...
66 篇 università di ca...
66 篇 university würzb...
53 篇 leiden universit...
51 篇 dept. of compute...
50 篇 school of automa...
49 篇 university of jo...
48 篇 university moham...
43 篇 in2p3 lpc campus...
42 篇 infn lnf via enr...
42 篇 university of gr...
42 篇 university moham...

作者

95 篇 ardid m.
93 篇 ferrara g.
92 篇 kalekin o.
92 篇 díaz a.f.
91 篇 boumaaza j.
91 篇 coleiro a.
89 篇 calvo d.
83 篇 gal t.
82 篇 bozza c.
80 篇 chen a.
78 篇 gozzini s.r.
76 篇 huang f.
75 篇 dallier r.
72 篇 anguita m.
61 篇 enzenhöfer a.
60 篇 kulikovskiy v.
59 篇 boettcher m.
55 篇 celli s.
52 篇 aly z.
48 篇 dornic d.

语言

23,310 篇 英文
2,487 篇 其他
271 篇 中文
80 篇 日文
21 篇 朝鲜文
4 篇 斯洛文尼亚文
1 篇 阿拉伯文
1 篇 德文
1 篇 法文
1 篇 土耳其文

检索条件"机构=Dept. Computer Architecture and Computer Technology"

共 26167 条记录，以下是251-260 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：

Zero-shot industrial anomaly detection and localization via reweighted density estimation 9

Zero-shot industrial anomaly detection and localization via ...

引用

9th International Symposium on Advances in Electrical, Electronics, and computer Engineering, ISAEECE 2024

作者： Fan, Wei Shen, Yaomin Zuo, Jiali Dept. Computer Science and Technology Jiangxi Normal University Nan chang China

ISBN: (纸本)9781510683303

To achieve high quality industrial Anomaly Detection (AD) is difficult as there are no anomalous samples in the training set and one need to treat the defective region in the test images as outliers. Recently, some researchers even propose to perform the AD in a zero-shot manner. The algorithm is required to predict the defective state of each test image without the training phase. Surprisingly, the pioneering work has achieved relatively high accuracy in this challenging scenario thanks to the smart low density assumption of the anomalous patches in the feature space. In this paper, we propose to improve the successful zero-shot method by introducing the dynamic density estimation of the patch features. The experiment results illustrate a significant performance gain in all the involved 4 metrics for anomaly detection or localization. © 2024 SPIE.

关键词： Detection and tracking algorithms Feature extraction Histograms Education and training Defect detection Statistical modeling

来源：评论

学校读者我要写书评

暂无评论

Driving Sustainability using Big Data Analytics

Driving Sustainability using Big Data Analytics

引用

2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024

作者： Dhriti Ashtekar, T. Khamesra, Nishit Bhargavi, M.S. Bangalore Institute of Technology Dept. of Computer Science & Engg. Bangalore India

ISBN: (纸本)9798350372229

With the explosion of data in the digital age, Big Data Analytics (BDA) has been embraced as a powerful technology for businesses to gain insights and make data-driven decisions. Its impact is evident across various industries, from fast-food chains utilizing it for personalized marketing to healthcare institutions employing it for improved patient care. This research explores the burgeoning field of BDA concerning sustainability by employing case studies to illuminate the powerful ways BDA empowers companies to move towards sustainability, aiming to demonstrate its transformative potential in achieving environmental and social goals. A humongous amount of data is generated, estimated at 2.5 quintillion bytes daily, which provides a fertile ground for BDA applications. Harnessing this data will help companies gain valuable insights into their environmental footprint, optimize resource utilization, and frame ingenious solutions for sustainability challenges. As a case study, we will be delving into Allbirds, a company that has sustainability as a core concept, that has identified pivotal areas for enhancement and incorporated data-driven solutions to optimize resource utilization and minimize the environmental impact to cope with issues such as climate changes and global warming. As another case study, we will explore Siemens which demonstrates the transformative power of big data in achieving broader environmental and social goals using their MindSphere platform. © 2024 IEEE.

关键词： Big Data Analytics Data-Driven Solutions Green technology Sustainability Sustainable Organizations

来源：评论

学校读者我要写书评

暂无评论

Youtube Comments Sentiment Analysis 1

Youtube Comments Sentiment Analysis

引用

1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kant, Shashi Upadhyay, Raushan Kumar Gupta, Palak Tiwari, Raghav Kumar, Honey Sharda University Dept. of Computer Science and Engg. Greater Noida India Greater Noida Institute of Technology Dept. of Computer Science and Engg. Noida India

ISBN: (纸本)9798350356816

Over the years, there has been a significant surge in textual information, leading to a burgeoning research interest. The contemporary focus lies in the intriguing field of sentiment analysis on YouTube comments. Despite the substantial volume of user comments and reviews on many videos, limited efforts have been directed towards extracting meaningful trends due to the inherent inconsistency and variable quality of *** this study, we perform sentiment analysis on YouTube comments concerning popular topics, with a selection of various machine learning techniques and algorithms. The aim will be to highlight how sentiment analysis can show trends, seasonality, and forecasts, and offer an insightful view into the effects of real-world events on the public mood. The results display strong correlation views between users' sentiments toward corresponding keywords and the real-world *** primary aim of this research is to assist scholars in identifying high-quality research papers on sentiment analysis. Our approach involves sentiment analysis of YouTube comments using citation sentences based on an existing annotated corpus consisting of 1500 citation sentences. Data cleansing involved the application of various normalization rules to eliminate noise from the comments in the corpus. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Smart Healthcare - IoT and Artificial Neural Network(ANN) 15

Smart Healthcare - IoT and Artificial Neural Network(ANN)

引用

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

作者： Sutar, Laxmikanta Chinara, Suchismita National Institute of Technology Rourkela Dept. of Computer Science and Engineering Rourkela India

ISBN: (纸本)9798350370249

With the use of the Internet of Medical Things (IoMT), the growing accessibility of wearable devices, and the continual reduction in the cost of sensor-based technologies and green computing, internet-connected sensors allow users to track, analyze, and share welfare information employing a cloud-based platform. Artificial Neural Networks (ANN) find extensive use across various applications, including healthcare systems, drawing inspiration from the biological concept of neurons. This study explores the prediction of heart attack risks using a combination of Internet of Things (IoT) sensors and artificial neural networks (ANN). Through the integration of IoT sensors such as the pulse sensor and LM35 temperature sensor, essential physiological data related to heart rate and body temperature was collected. An ANN model was developed, focusing on predictive capabilities using the sigmoid function, feedforward and backpropagation techniques, and random weight initialization. The investigation further utilized Keras with TensorFlow and optimized model parameters using Adam Optimization and Later with One Hot Encoding plus a Genetic Algorithm (GA). Additionally, the study involved training neural networks on higher-quality UCI datasets to evaluate performance. Scatterplots were generated to visualize relationships between variables. Results demonstrated promising performance improvements, with the model achieving close to 90% accuracy on the testing dataset. Encoding techniques were employed to handle categorical variables effectively, contributing to the model's robustness and generalization. Overall, this research offers valuable insights into leveraging IoT sensors and ANN for heart attack risk prediction. © 2024 IEEE.

关键词： Adam Optimisation ANN Back Propagation Dense Layers Feed Forwarding Fuzzy Genetic Algorithm HTTP IoT MQTT One Hot Encoding Protocols UCI Heart Data

来源：评论

学校读者我要写书评

暂无评论

Image Segmentation based Approach for Skin Disease Detection and Classification using Machine Learning Algorithms 2

Image Segmentation based Approach for Skin Disease Detection...

引用

2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Sany, Nazmul Hasan Chandra Shill, Pintu Khulna University of Engineering & Technology Dept. of Computer Science and Engineering Khulna Bangladesh

ISBN: (纸本)9798350317558

Skin disorders are ubiquitous, stemming from causes including fungus, germs, allergies, and viruses. Although laser and photonics medical technologies have revolutionised rapid and precise diagnosis, their exorbitant prices restrict accessibility. To address this, this paper describes an image processing strategy for dermatological screening and procedure that comprises obtaining digital photographs of damaged skin patches and applying image processing to detect the disease type. Moreover, when conducted manually by medical specialists, identifying skin illnesses is time-intensive and subjective. As a consequence, both patients and physicians want automated skin disease prediction, which makes the treatment plan faster. This cost-effective approach depends on a basic setup: a camera and a computer. Operating on colour photos, a solution combines resizing for feature extraction using a pertained convolutional neural network, followed by classification using a multiclass SVM. The technology efficiently recognises four separate skin illnesses with an astonishing 90.8% accuracy, giving users complete findings spanning disease kind, extent, and severity. © 2024 IEEE.

关键词： Decision Tree Image Processing K-NN Machine Learning Skin Disorder SVM

来源：评论

学校读者我要写书评

暂无评论

A Novel Method to Detect Oral Carcinoma Using Box Annotation Based on YOLO Model

A Novel Method to Detect Oral Carcinoma Using Box Annotation...

引用

2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Laila, Shahara Ema, Romana Rahman Galib, Syed Md. Jamil, Abu Rafe Md Uddin, A. F. M. Shahab Jashore University of Science and Technology Dept. of Computer Science and Engineering Jashore Bangladesh

ISBN: (纸本)9798350350289

Oral carcinoma affects millions of individuals globally and is a major public health problem due to its high fatality rate. Treatment effectiveness depends on early detection and improves survival rates. An effective method for automated oral cancer screening is deep learning. The paper's primary goal is to use deep learning techniques to advance the state of oral cancer diagnosis, specifically YOLOv5 and YOLOv7. We aimed to achieve accurate detection by leveraging bounding box annotations for both two distinct types of data: collected clinical data and benchmark data of oral carcinoma. The proposed methodology encompasses data collection, preprocessing, expert-driven bounding box annotation and the use of cutting-edge deep learning models for lesion identification, YOLOv5 and YOLOv7. Bounding box serving as expert annotations are meticulously added to pinpoint cancerous regions within the images. Subsequently, a comprehensive evaluation is conducted, measuring the performance of both models based on precision, recall rate (sensitivity) and mean average precision (mAP). Our findings reveal that YOLOv5 outperforms YOLOv7 in terms of oral cancer detection, demonstrating superior precision and recall rates. In the evaluation of this research, the YOLOv5 model demonstrated strong performance metrics on both clinical and lip and tongue cancer datasets. For the lip and tongue cancer dataset, the YOLOv5 model achieved a precision of 97.2%, a mAP (mean Average Precision) of 97.7% and a recall of 96.3%. © 2024 IEEE.

关键词： Clinical research

来源：评论

学校读者我要写书评

暂无评论

Transformer-Based Self-Supervised Imputation for Medical Data 4

Transformer-Based Self-Supervised Imputation for Medical Dat...

引用

4th International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2024

作者： Singh, Aryan Kumar Saikia, Arpit Baro, Pranita Borah, Malaya Dutta National Institute of Technology Silchar Dept. of Computer Science and Engineering Cachar India

ISBN: (纸本)9798350391183

Dealing with missing data is necessary to develop a solid predictive medical research model. This work presents a hybrid dynamic imputation method devoted to addressing the challenge of missing data, specifically focusing on medical datasets. In this work, we investigate the incompleteness of the dataset using a sophisticated measure called the Incompleteness Factor. This metric is used to guide a hybrid dynamic approach. A novel Transformer-based Self-Supervised imputation method is employed to learn complex data dependencies to impute missing data. This paper introduces one potential solution to obtain model-level accuracy increase for tasks like disease prediction, patient prognosis, etc., over medical datasets. The proposed method aims to remove the measurement biases caused by incompleteness and preprocess the data to enhance the credibility and clinical relevance of the experimental results. © 2024 IEEE.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Security Enhancement in Tea Supply Chain using Blockchain with Hyperledger 2

Security Enhancement in Tea Supply Chain using Blockchain wi...

引用

2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Gupta, Amritesh Kumar Dwivedi, Rajendra Kumar Madan Mohan Malaviya University of Technology Dept. of Information Technology and Computer Application Gorakhpur India

ISBN: (纸本)9798350327533

With the advancement of technology and emergence of blockchain, it has become quite a popular tool which is often integrated with systems and processes that require decentralization, traceability, consistency etc. One such area is of supply chain management. Often the raw materials used to make a final product do not come from a single source and hence there has been always a risk of making counterfeit, cloned item of the same. Same goes in the case of tea powder production too. Seeds used and leaves planted come from different sources which collectively determine the quality of the end tea powder. The proposed work tackles issues not only by providing traceability but also contributes in the overall security of the system by making use of Hyperledger fabric and Elliptic Curve Digital Signature Algorithm (ECDSA). In addition to these features, cross platform payment is also made possible by integrating the system with bridges. By making use of Hyperledger fabric and Interplanetary File System (IPFS), latency is decreased as well as throughput is increased. Additionally, making use of ECDSA provides same level of security with smaller key size and generates signature faster as compared to other cryptographic algorithms like Rivest-Shamir-Adleman (RSA). © 2024 IEEE.

关键词： Blockchain Elliptic Curve Digital Signature Algorithm (ECDSA) Internet of Things (IoT) Interplanetary File System (IPFS) Supply Chain Management Tea Supply Chain

来源：评论

学校读者我要写书评

暂无评论

Lip Reading Into Text Using Deep Learning 14

Lip Reading Into Text Using Deep Learning

引用

14th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2024

作者： Manglani, Krishna Bahuguna, Utkarsh Gupta, Subhash Chand Amity School of Engineering and Technology Dept. of Computer Science Uttar Pradesh India

ISBN: (纸本)9798350344837

An essential part of computer vision, lip reading, has grown significantly and is now used in autonomous driving, public safety, and hearing-impaired communication. This work provides an in-dept. analysis of both conventional and deep learning-based lip reading systems, examining their development over time, difficulties encountered, and critical role in human communication. The suggested LipNet model, which leverages the complementary abilities of Long Short-Term Memory networks (LSTMs) for temporal modelling and Convolutional Neural Networks (CNNs) for spatial feature extraction, is a central focus of this research. When LipNet is tested using the GRID Corpus dataset, it outperforms baseline models in terms of performance. Saliency maps and viseme analysis highlight LipNet's ability to capture phonologically relevant areas in lip motions, providing insight into the network's attention processes. Apart from examining the importance of datasets such as OuluVs2and GRID Corpus, this study presents GhostNet, a lightweight model that tackles the requirement for effective network designs. The testing results highlight LipNet's competitive Character Error Rate (CER) and Word Error Rate (WER) in comparison to baseline models, proving that it is the best method for real-world use. The research ends with a summary of potential future developments in lip reading technology, such as modal integration, realtime applications, personalisation, ethical issues, and the goal of creating a communication environment that is more inclusive. This study highlights the effectiveness of LipNet and paves the way for future developments in the ever-evolving area of lip reading by examining a variety of methodologies. © 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

Generative Adversarial Approach for Medical Image Synthesis with Context Aware Deep Convolutional Networks

Generative Adversarial Approach for Medical Image Synthesis ...

引用

2024 IEEE International Conference on Emerging Technologies in computer Science for Interdisciplinary Applications, ICETCS 2024

作者： Bhogade, Vaibhav Nithya, B. National Institute of Technology Dept. of Computer Science and Engg. Tiruchirappalli India

ISBN: (纸本)9798350372502

Medical imaging plays a crucial role in various clinical applications. However, due to factors like cost and radiation dose, acquiring certain image modalities may be limited. Therefore, medical image synthesis can be highly advantageous as it estimates desired imaging modalities without the need for actual scans. In this paper, a generative adversarial approach is used to address this challenging problem. To create a target image from a source image, a fully convolutional network (FCN) is specifically trained. An adversarial learning approach is used to improve the FCN's capacity to simulate the nonlinear mapping from source to target and generate more accurate target images. Additionally, an image-gradient-difference based loss function is added into the architecture of the FCN to prevent hazy target images. Investigating long-term residual units helps to enhance the network's training procedure. An Auto-Context Model is also used to develop a context-aware deep convolutional adversarial network. The correctness and reliability of the proposed method for creating target images from corresponding source photos are shown by experimental findings. The proposed methodology is assessed using datasets for the tasks of producing CT pictures from MRI and producing 7T MRI images from 3T MRI data. The results will demonstrate how well this technique handles picture generation for a variety of medical imaging tasks © 2024 IEEE.

关键词： Medical imaging

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 << < 22 23 24 25 26 27 28 29 30 31 > >>

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：