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

59,230 篇 会议
10,347 篇 期刊文献
546 册 图书
34 篇 科技报告

馆藏范围

70,157 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

45,740 篇 工学
- 35,326 篇 计算机科学与技术...
- 29,451 篇 软件工程
- 10,772 篇 信息与通信工程
- 6,531 篇 控制科学与工程
- 4,419 篇 电气工程
- 4,307 篇 生物工程
- 4,154 篇 电子科学与技术（可...
- 3,360 篇 生物医学工程（可授...
- 2,608 篇 光学工程
- 2,413 篇 机械工程
- 1,894 篇 仪器科学与技术
- 1,785 篇 动力工程及工程热...
- 1,734 篇 化学工程与技术
- 1,417 篇 安全科学与工程
- 1,301 篇 建筑学
- 1,190 篇 交通运输工程
23,714 篇 理学
- 14,734 篇 数学
- 5,318 篇 物理学
- 4,808 篇 生物学
- 4,361 篇 统计学（可授理学、...
- 2,624 篇 系统科学
- 1,864 篇 化学
12,135 篇 管理学
- 6,563 篇 管理科学与工程(可...
- 6,196 篇 图书情报与档案管...
- 3,807 篇 工商管理
2,635 篇 医学
- 2,313 篇 临床医学
- 2,180 篇 基础医学(可授医学...
- 1,421 篇 药学(可授医学、理...
2,139 篇 法学
- 1,789 篇 社会学
1,242 篇 经济学
- 1,241 篇 应用经济学
1,154 篇 教育学
883 篇 农学
285 篇 文学
149 篇 军事学
86 篇 艺术学
37 篇 哲学
17 篇 历史学

主题

1,772 篇 computer science
1,547 篇 accuracy
1,499 篇 computational mo...
1,437 篇 feature extracti...
1,192 篇 training
961 篇 deep learning
934 篇 machine learning
818 篇 data mining
769 篇 semantics
754 篇 predictive model...
708 篇 real-time system...
696 篇 artificial intel...
692 篇 support vector m...
675 篇 data models
653 篇 computer archite...
563 篇 optimization
563 篇 visualization
550 篇 internet of thin...
524 篇 neural networks
517 篇 convolutional ne...

机构

90 篇 institute of inf...
84 篇 dept. of compute...
83 篇 north-west unive...
82 篇 dept. of compute...
81 篇 infn sezione di ...
76 篇 infn sezione di ...
76 篇 institut univers...
70 篇 national centre ...
66 篇 università di ca...
65 篇 dept. of compute...
60 篇 dept. of compute...
56 篇 dept. of compute...
55 篇 dept. of informa...
52 篇 school of automa...
46 篇 leiden universit...
42 篇 infn lnf via enr...
42 篇 in2p3 lpc campus...
39 篇 dept. of compute...
38 篇 dept. of compute...
38 篇 dept. of compute...

作者

94 篇 ardid m.
93 篇 ferrara g.
87 篇 calvo d.
80 篇 chen a.
79 篇 gal t.
78 篇 bozza c.
67 篇 kalekin o.
62 篇 ahmad jalal
60 篇 kulikovskiy v.
47 篇 huang f.
43 篇 díaz a.f.
41 篇 gagliardini s.
40 篇 benoit d.m.
40 篇 eddymaoui a.
40 篇 labalme m.
36 篇 androulakis g.
34 篇 de palma m.
30 篇 guru prasad m.s.
30 篇 khatun a.
29 篇 boumaaza j.

语言

68,121 篇 英文
1,324 篇 其他
524 篇 中文
106 篇 日文
58 篇 朝鲜文
11 篇 德文
7 篇 西班牙文
7 篇 法文
3 篇 葡萄牙文
2 篇 斯洛文尼亚文

检索条件"机构=Dept. of Computer Languages and Computer Science"

共 70157 条记录，以下是31-40 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：

Maskify: Precision Detection and Fit Assessment for Mask Compliance 6

Maskify: Precision Detection and Fit Assessment for Mask Com...

引用

6th IEEE International Conference on Image Processing, Applications and Systems, IPAS 2025

作者： Pathak, Prakrit Garg, Ayush Kumar Chaurasia, Priyesh IIIT-Delhi Dept. of Computer Science India

ISBN: (纸本)9798331506520

We introduce Maskify, an innovative tool designed to automatically detect and evaluate the use of face masks. Amid the challenges of the COVID-19 pandemic, wearing masks has emerged as a crucial strategy to limit the virus's spread, especially in environments where mask mandates are enforced. Reliable systems for monitoring mask usage are therefore vital for public *** solution leverages deep learning to not only determine if a person is wearing a mask but also to assess how well the mask fits using a specialized metric called the "wearable score."This score quantifies the extent to which the mask properly covers essential areas of the face. Developing Maskify involved creating a diverse dataset that includes images of both masked and unmasked *** process begins with advanced pre-trained models that accurately identify faces in images. Once a face is detected, key landmarks on the lower face are extracted to assist in classifying the mask. We utilize ResNet-based architectures, known for their robust image classification performance, to enhance the detection accuracy. The wearable score is then computed by segmenting the mask region and calculating the percentage of the face that is effectively *** summary, Maskify offers a robust approach for monitoring mask compliance and ensuring proper fit, thereby supporting ongoing public health efforts to mitigate the spread of COVID-19. © 2025 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Semantic Masking in a Needle-in-a-haystack Test for Evaluating Large Language Model Long-Text Capabilities 1

Semantic Masking in a Needle-in-a-haystack Test for Evaluati...

引用

1st Workshop on Writing Aids at the Crossroads of AI, Cognitive science and NLP, WRAICOGS 2025

作者： Shi, Ken Penn, Gerald Dept. of Computer Science University of Toronto Canada

ISBN: (纸本)9798891762213

In this paper, we introduce the concept of Semantic Masking, where semantically coherent surrounding text (the haystack) interferes with the retrieval and comprehension of specific information (the needle) embedded within it. We propose the Needle-in-a-Haystack-QA Test, an evaluation pipeline that assesses LLMs’ long-text capabilities through question answering, explicitly accounting for the Semantic Masking effect. We conduct experiments to demonstrate that Semantic Masking significantly impacts LLM performance more than text length does. By accounting for Semantic Masking, we provide a more accurate assessment of LLMs’ true proficiency in utilizing extended contexts, paving the way for future research to develop models that are not only capable of handling longer inputs but are also adept.at navigating complex semantic landscapes. © WRAICOGS 2025 - Writing Aids at the Crossroads of AI, Cognitive science and NLP, Proceedings of the 1st Workshop.

关键词： Needles

来源：评论

学校读者我要写书评

暂无评论

A Motor Activity Analysis as a Depression Indicator: Predictive Approach Using A Hybrid CNN and LSTM Network 6

A Motor Activity Analysis as a Depression Indicator: Predict...

引用

6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Sutedja, Vinsensius Odilo Andreas, Frans Nabiilah, Ghinaa Zain Moniaga, Jurike V. Dept. Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798331539603

Depression is a prevalent mental disorder affecting behavior, cognition, and physical activity. Early detection and intervention are crucial to mitigating its severe impacts, including suicidal ideation or suicide attempts. This study proposes a novel predictive model using a hybrid Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network to analyze motor activity data as an indicator of depression. Utilizing the "Depresjon" dataset, which comprises activity levels from both depressed and non-depressed individuals, the model extracts features through CNN and processes these with LSTM to identify depression patterns. To address class imbalance in the dataset, Synthetic Minority Over-sampling Technique (SMOTE) was employed, enhancing the model's predictive accuracy. The final model achieved a high accuracy rate of 97.89%, significantly outperforming the other model created. This research demonstrates the potential of combining CNN and LSTM for effective depression prediction, providing a valuable tool for early diagnosis and intervention. © 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

Comparative analysis of Machine Learning Techniques for the Detection of Heart Disease

Comparative analysis of Machine Learning Techniques for the ...

引用

2024 International Conference on science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Adeniyi, Jide Kehinde Adeniyi, Tunde Taiwo Adeniyi, Emmanuel Abidemi Abiodun, Moses Kazeem Awotunde, Joseph Bamidele Landmark University SDG 9: Industry Innovation and Infrastructure Dept. of Computer Science Nigeria University of Ilorin Dept. of Computer Science Nigeria Bowen University Dept. of Computer Science Iwo Nigeria Landmark University SDG 10: Reduced Inequality Dept. of Computer Science Nigeria

ISBN: (纸本)9798350358155

The World Health Organization stated that an alarming 32 percent of worldwide fatalities was from heart related challenges. This percentage is even more escalated in poor and moderate countries. Most heart related issues can be ameliorated or managed if they are detected on time. Hence, with the advent of machine learning techniques, prediction of heart related issues can be made. Several machine learning methods have been proposed for heart related issues prediction, and each with varying performance level. A few comparisons have been made amongst these machine learning techniques with little details. In this study, a detailed comparison of four machine learning techniques was considered. The machine learning methods considered were selected based on their performance from literatures. The examined methods include the decision tree, random forest, support vector machines, and logistic regression. Prior to training and testing, the dataset was preprocessed by encoding the categorical data and scaling the dataset features. The outcome of the testing showed that the accuracy was obtained for logistic regression and support vector machine;with both having an accuracy of 0.882. © 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

Enhancing Human computer Interaction (HCI) Through Machine Learning Application 8

Enhancing Human Computer Interaction (HCI) Through Machine L...

引用

8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Yaseen, Fahad Abdulateef Ahmed, Mohammad Shihab Khudhur, Mokhalad Eesee College Tikrit University Dept. Computer Science Computer Science and Mathematics Tikrit Iraq

ISBN: (纸本)9798350354423

Integrating human-computer interaction with machine learning is an important development that contributes and opens the way for many experiences that serve the user. This research presents the scientific benefits and effects resulting from integrating human-computer interaction and machine learning, and on the other hand, discusses the common applications between them and what challenges will arise from data privacy and ethical considerations. Thus, this interaction will contribute to enhancing and encouraging user participation and to a greater increase in intelligence and responsiveness. This research aims to present and propose innovative solutions that address the challenges that will face this interaction, in addition to presenting a concept and a methodological model that increases the power of human-computer interaction in a more intelligent and smooth way. © 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

State of the art: Security Testing of Machine Learning Development Systems 14

State of the art: Security Testing of Machine Learning Devel...

引用

2024 IEEE 14th Annual Computing and Communication Workshop and Conference, CCWC 2024

作者： Das, Saikat Krishnamurthy, Bhargavi Das, Raktim Ranjan Shiva, Sajjan G Utah Valley University Dept. of Computer Science Orem United States Siddaganga Institute of Technology Dept. of Computer Science Karnataka Tumakuru India Stamford University Bangladesh Dept. of Computer Science Dhaka Bangladesh University of Memphis Dept. of Computer Science Memphis United States

ISBN: (纸本)9798350360134

In recent days, machine learning (ML) systems have become integral to nearly all mainstream applications. Understanding the underlying logic that contributes to the desired behavior in ML systems can be challenging. Humans play a crucial role in providing the necessary data samples for training ML models to ensure accurate predictions. The complexity of ML testing arises from various factors such as data dependency, dynamic model behavior, the absence of a test oracle, a vast input space, and the lack of a specific testing life cycle tailored for ML. Testing ML systems is not a straightforward process, as it not only involves verifying the code and their corresponding data but also is further complicated by the dynamic nature of these systems. A typical ML model undergoes seven stages, including eliciting business needs/requirements, gathering data, selecting a model, training the model, testing the model, deploying the model, and monitoring the model. Throughout the ML Development Life Cycle (MLDLC), each stage introduces various security risks. This paper explores the current state of the literature on security attacks and defense approaches concerning data, model, and prediction output of ML models. The paper also addresses potential security attacks at each stage of the MLDLC and the corresponding security measures to mitigate those attacks. © 2024 IEEE.

关键词： Life cycle

来源：评论

学校读者我要写书评

暂无评论

Classification Flower Images Based on Deep Learning and Machine Learning 8

Classification Flower Images Based on Deep Learning and Mach...

引用

8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Mustfa, Asia Kamal Abdulateef, Salwa Khalid Hameed, Qabas Amer Ahmed, Mohamed Aktham Al-Qaysi, Zaydoon Computer Science and Mathematics College Tikrit University Dept. Computer Science Tikrit Iraq

ISBN: (纸本)9798350354423

Image classification has grown increasingly popular due to the growing significance of machine learning and deep learning. Flower images may sometimes exhibit resemblances in terms of hue, form, and visual characteristics. The problem lies in the classification of flowers. This work employs a hybrid approach that integrates deep learning and machine learning techniques to classify 17 discrete flower species. In order to do this, we utilised the ResNet_50, PCA, and SVM architecture to classify several species from the 'Oxford-17' dataset. With this goal in mind, we have made efforts to improve our model in order to get more accuracy compared to similar methods. Prior to inputting our images into our pretrained model, we resized them, and subsequently fine-tuned the model. The dataset was partitioned into two distinct sets: a training set and a testing set. We attained a precision rate of 95.58% while utilising the 'Oxford-17' dataset. Our approach outperformed previous machine learning and deep learning-based methods on this dataset. © 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

AnVILMEDFORD: Documenting Cloud-Based Analysis Projects Using the MEDFORD Metadata Language

AnVILMEDFORD: Documenting Cloud-Based Analysis Projects Usin...

引用

2024 IEEE International Conference on Big Data, BigData 2024

作者： Stubbs, Benjamin Shpilker, Polina Sayers, Michael Wallace, Shaun Daniels, Noah M. Couch, Alva Tufts University Department of Computer Science MedfordMA United States University of Rhode Island Dept. of Computer Science and Statistics KingstonRI United States Dept. of Computer Science and Statistics Dept. of Computer Science KingstonRI United States

ISBN: (纸本)9798350362480

This paper introduces AnVILMEDFORD, an R package that aims to enable MEDFORD metadata annotation from within the cloud based AnVIL platform for computational analysis. AnVILMEDFORD helps solve the problem of documentation within the AnVIL environment by providing bidirectional tools that both allow a user to generate MEDFORD documentation from a workspace, and also allow a user to update an AnVIL workspace starting with a MEDFORD meta-data file. AnVILMEDFORD accomplishes this by leveraging the Bioconductor AnVIL package and the AnVIL API to download and process AnVIL metadata, Tree-sitter-medford module along with the AnVIL API to update the workspace in the cloud. An implementation is available at https://***/bjstubbs/AnVILMEDFORD © 2024 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Unravelling the Enigma of Polycystic Ovary Syndrome (PCOS): Using MLAlgorithms 2

Unravelling the Enigma of Polycystic Ovary Syndrome (PCOS): ...

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Juneja, Sonam Bhati, Bhoopesh Singh Atwal, Shikha Anand, Monika Maiti, Souvik Chandigarh University Dept. of Computer Science and Engineering Gharuan India Iiit Dept. of Computer Science and Engineering Sonepat India

ISBN: (纸本)9798350371055

The difficulties and ramifications of PCOS, which affects a sizable portion of women who are of reproductive age, are discussed in this review. The article covers the various clinical manifestations of PCOS, how it affects both reproductive and non-reproductive health, and how it's linked to psychological distress and metabolic disorders. It highlights how critical lifestyle modifications, early detection, and accurate diagnosis are. Additionally, the study presents machine learning techniques for PCOS detection, demonstrating the effectiveness of techniques like Random Forests, CNN, and SVM. An innovative CDSS that uses the Red Deer Algorithm shows encouraging accuracy. The necessity of continued research, diversified datasets, and cooperative efforts to enhance PCOS detection at the nexus of technology and healthcare is highlighted in the abstract's conclusion. © 2024 IEEE.

关键词： Deep Learning KNN Machine Learning PCOS Random Forest SVM

来源：评论

学校读者我要写书评

暂无评论

Architectural Model of Deep Convolution Neural Network Approach for Brain Tumor Prediction

Architectural Model of Deep Convolution Neural Network Appro...

引用

2024 International Conference on Intelligent Computing and Sustainable Innovations in Technology, IC-SIT 2024

作者： Panigrahi, Raghunath Sahu, Rekha Nayak, Suvendu Chandan Kabat, Manas Ranjan IMIT Dept. of Computer Science and Engineering Cuttack India Silicon University Dept. of Computer Science and Engineering Bhubaneswar India

ISBN: (纸本)9798350369175

Magnetic Resonance Imaging (MRI) is most commonly used technique to detect a tumor by physicians in medical science. The MRI images are three-dimensional images with the number of slices that are analyzed to identify the defective cells in the naked eye that leads to a time-consuming process. Machine Learning (ML) techniques are investigated as a solution to improve tumor identification in a better way. Early and accurate detection is crucial for effective treatment planning and improving patient outcomes. Traditionally, brain tumor diagnosis relies on manual analysis of MRI (Magnetic Resonance Imaging) scans by radiologists, which can be time-consuming and prone to human error. The advent of deep learning, particularly Convolutional Neural Networks (CNNs), has opened new avenues for automating and improving the accuracy of brain tumor prediction. In this paper, we study the Convolutional Neural Network(CNN) model which is popular in image analysis. Similar way, we develop a CNN model to process and classify the MRI images to detect the type of brain tumor. We examine the model's performance by using 5712 MRI images from a standard dataset available in the public domain. The aim of the work is to classify the tumor in four classes like: Glioma, Meningioma, Pituitary and No Tumour using the proposed CNN model. Our model follows data preprocessing, image encoding, filtering and classification. The proposed model scores 78% accuracy as its performance in the dataset which needs more investigations and comparison with other techniques in further study. © 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500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：