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

分类表

所选分类

>> <<

限定检索结果

标题

标题
作者
主题词
出版物名称
出版社
机构
学科分类号
摘要
ISBN
ISSN
基金资助
索书号

作者

作者
标题
主题词
出版物名称
出版社
机构
学科分类号
摘要
ISBN
ISSN
基金资助
索书号

文献类型

43,241 篇 会议
26,542 篇 期刊文献
695 册 图书

馆藏范围

70,478 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

43,497 篇 工学
- 32,308 篇 计算机科学与技术...
- 26,872 篇 软件工程
- 10,490 篇 信息与通信工程
- 6,383 篇 控制科学与工程
- 5,991 篇 生物工程
- 5,150 篇 生物医学工程（可授...
- 4,795 篇 电气工程
- 3,899 篇 电子科学与技术（可...
- 3,526 篇 光学工程
- 2,624 篇 机械工程
- 2,229 篇 仪器科学与技术
- 2,092 篇 化学工程与技术
- 2,005 篇 动力工程及工程热...
- 1,921 篇 网络空间安全
- 1,780 篇 安全科学与工程
- 1,590 篇 交通运输工程
25,099 篇 理学
- 12,548 篇 数学
- 7,155 篇 生物学
- 6,710 篇 物理学
- 4,893 篇 统计学（可授理学、...
- 2,457 篇 系统科学
- 2,446 篇 化学
13,393 篇 管理学
- 7,616 篇 管理科学与工程(可...
- 6,300 篇 图书情报与档案管...
- 3,868 篇 工商管理
5,675 篇 医学
- 4,644 篇 临床医学
- 4,130 篇 基础医学(可授医学...
- 2,550 篇 公共卫生与预防医...
- 2,319 篇 药学(可授医学、理...
2,524 篇 法学
- 2,128 篇 社会学
1,520 篇 经济学
1,200 篇 农学
1,022 篇 教育学
328 篇 文学
137 篇 军事学
108 篇 艺术学
13 篇 哲学
12 篇 历史学

主题

2,346 篇 accuracy
2,067 篇 deep learning
1,868 篇 machine learning
1,661 篇 computer science
1,629 篇 data models
1,619 篇 data mining
1,558 篇 training
1,523 篇 feature extracti...
1,343 篇 computational mo...
1,270 篇 predictive model...
1,155 篇 internet of thin...
1,079 篇 real-time system...
1,009 篇 support vector m...
959 篇 convolutional ne...
950 篇 artificial intel...
705 篇 optimization
660 篇 cloud computing
643 篇 security
610 篇 semantics
583 篇 wireless sensor ...

机构

973 篇 cavendish labora...
943 篇 department of ph...
878 篇 oliver lodge lab...
864 篇 physikalisches i...
603 篇 university of ch...
561 篇 fakultät physik ...
519 篇 department of ph...
509 篇 horia hulubei na...
503 篇 school of physic...
499 篇 imperial college...
493 篇 school of physic...
487 篇 stfc rutherford ...
487 篇 nikhef national ...
480 篇 iccub universita...
480 篇 h.h. wills physi...
476 篇 school of physic...
472 篇 physik-institut ...
471 篇 department of co...
468 篇 henryk niewodnic...
464 篇 school of physic...

作者

253 篇 barter w.
235 篇 a. gomes
232 篇 beiter a.
222 篇 bellee v.
218 篇 s. chen
216 篇 brundu d.
212 篇 bowcock t.j.v.
210 篇 c. alexa
210 篇 blake t.
209 篇 j. m. izen
207 篇 g. bella
207 篇 j. strandberg
207 篇 d. calvet
207 篇 c. amelung
205 篇 boettcher t.
204 篇 betancourt c.
204 篇 amato s.
203 篇 borsato m.
199 篇 bencivenni g.
197 篇 bay a.

语言

54,693 篇 英文
15,287 篇 其他
624 篇 中文
33 篇 日文
18 篇 德文
17 篇 斯洛文尼亚文
16 篇 法文
6 篇 朝鲜文
3 篇 西班牙文
2 篇 阿拉伯文
1 篇 捷克文
1 篇 俄文

检索条件"机构=Data Science Program Computer Science Department School of Computer Science"

共 70478 条记录，以下是341-350 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：

相关度排序

相关度排序
时效性降序
时效性升序

Implementation of YOLO v7 algorithm in estimating traffic flow in Malang 9th

Implementation of YOLO v7 algorithm in estimating traffic fl...

引用

9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Saputri, Hanis Amalia Avrillio, Matthew Christofer, Louis Simanjaya, Victorius Alam, Islam Nur Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

The escalating prevalence of traffic congestion in Malang, which has worsened over time, has resulted in increased inconvenience and traffic-related issues. As a solution, we propose the development of an intelligent transportation system based on traffic flow estimation. While this endeavor presents challenges, advancements in traffic data accessibility and deep learning algorithms, including You Only Look Once (YOLO), R-CNN based ResNet101, Inception V2, and others, with YOLOv7 demonstrating superior performance, continue to enhance traffic flow estimation. Consequently, this study aims to describe and assess the YOLOv7 model's suitability for estimating traffic flow. To achieve this, we propose a traffic monitoring system utilizing the YOLOv7 model in conjunction with a SORT filter, capable of tracking vehicle count and average speed using a custom dataset comprising car images and CCTV footage of Malang's traffic. Subsequently, the number and average speed of cars passing on the road were computed by delineating two virtual boxes. According to the findings, our YOLOv7 system exhibited higher average precision, achieving 61.3%, 78.6%, and 62.1% for each test, and boasted a faster average inference time of 90.67 seconds, meeting the requirements of an intelligent transportation system. Nevertheless, with an average percent deviation in vehicle count exceeding 30% compared to the pre-trained model, vehicle detection is suboptimal, consequently impacting average vehicle speed detection adversely. Hence, our custom model necessitates further optimization and training before practical implementation in real-world traffic estimation. © 2024 The Authors.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Recognition of Facial Expressions and Emotions on the Face using the YOLOv5 Algorithm

Recognition of Facial Expressions and Emotions on the Face u...

引用

2023 International Workshop on Artificial Intelligence and Image Processing, IWAIIP 2023

作者： Gunawan, Alexander A. S. Kusnadi, Maximilianus Raymond Joseph, James Tristan Josan, William Edbert, Ivan Sebastian Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Cyber Security Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350382914

This study examines the significant influence of emotional states on individuals, recognizing that people are often confronted with numerous challenges and problems in their lives. Such challenges can give rise to feelings of despair and tension, especially in those who struggle to manage them effectively. Depression, which is not just limited to adults, can also have a significant impact on children who may not fully grasp their socio-economic conditions. One of the serious consequences of unresolved emotional distress, particularly depression, is an elevated risk of suicide. Within this framework, facial recognition technology presents itself as a powerful instrument for identifying human emotions. The purpose of this study is to assess the efficacy of facial recognition systems in detecting indicators of depression. Using the YOLOv5 algorithm and comparing it with its precursors, YOLOv4 and YOLOv7, the research conducts a simulation experiment to examine the ability of the system to precisely interpret a range of emotional states, including happiness, sadness, and anger. The research findings suggest that the YOLO algorithm, particularly in its most recent versions, displays exceptional precision in identifying and classifying intricate facial expressions, thus showcasing its potential as a beneficial device in mental health evaluations. © 2023 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Exploring the Spectrum of Biometric Technologies: A Systematic Literature Review of Conventional and Unconventional Modalities 9th

Exploring the Spectrum of Biometric Technologies: A Systemat...

引用

9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Aldo Arista, W.P. Bryan Fernando, K.S. Sidharta, Sidharta Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Biometric recognition is a process of validating and identifying people based on their distinct physiological or behavioral traits. Through this literature review, we strive to reduce the knowledge gap among the public about existing biometric modalities, how the biometrics technology is applied, what algorithms are often used in processing the biometrics data, and what common benchmarks are often used to test and measure the performance of each biometrics. This paper provides a systematic literature review with the Kitchenham and Cochrane method, aimed at exploring variant types of biometric modalities and how each of them collects data, how biometric modalities are applied in various industries, common algorithms or methods used in biometric technologies, and establishing metrics and benchmarks for evaluating the performance of biometric technology. As a result, each biometric modality has its way of collecting data, for example, fingerprint recognition uses techniques like contrast correction, noise filtering, and sharpening to extract the fingerprint pattern. Biometric modalities are already used in many sectors of industries, and fingerprint readers or facial feature detection cameras are used to reduce the authentication process in the banking sector. Minutiae-based algorithm commonly used for fingerprint biometric modality, Eigenface for facial detection, and Euclidean distance or Support Vector Machine (SVM) for gait detection. Accuracy, False Acceptance Rate (FAR), False Rejection Rate (FRR), Equal Error Rate (EER), and Receiver Operating Characteristic (ROC) metrics and benchmarks are used to evaluate the performance of biometric technology. © 2024 The Authors.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Content-Based Book Recommendation System Using DeepWalk 11

Unsupervised Content-Based Book Recommendation System Using ...

引用

11th International Conference on ICT for Smart Society, ICISS 2024

作者： Zebua, Hans Jonathan Hamdi, Emmanuel Brandon Kurniadi, Felix Indra School of Computer Science Bina Nusantara University Computer Science Department Jakarta11530 Indonesia

ISBN: (纸本)9798350389654

Reading is a beneficial activity that anyone can do to increase their skills such as critical thinking skills and knowledge, unfortunately, low literacy rates are still prevalent in developing country such as Indonesia, to address this problem a book recommendation system is needed to increase people's interest in reading, this paper introduces the utilization of DeepWalk for creating an unsupervised content-based book recommendation system. It's starts by first doing pre-processing to the the dataset by cleaning the dataset and turning the dataset into graph, implement the DeepWalk's algorithm to the graph, and then conduct a study case to use the model to recommend books similar to the book 'Anna Karenina' as the basis for the recommendation. It is found that based on the results, the model achieves its goal in recommending a sensible and robust collection of recommended books and thus makes DeepWalk a promising algorithm in making a book recommendation system. © 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

Re-Enhancing Multi-Target Classification Techniques for CODEBRIM dataset using Deep Learning Algorithm 13

Re-Enhancing Multi-Target Classification Techniques for CODE...

引用

13th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2024

作者： Alexsah, Rizky P. Gunawan, Alexander Agung Santoso Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368086

The existence of concrete defects such as corrosion stains, cracks, efflorescence, exposed bars, and spallation has greatly compromised the safety and convenience of bridge users. These calamities can lead to deaths and have an impact on both communities and the economy. Effective maintenance management relies on the receipt of timely and accurate information. Technological progress facilitates the instantaneous handling of up-to-the-minute data. The objective of this work is to enhance the performance of YOLO models for current applications. The CODEBRIM custom dataset is used, which consists of 7,261 photographs illustrating concrete flaws. The results demonstrated that the YOLOv9m version attained the highest levels of accuracy and precision, reaching 74.99% and 89.41% correspondingly. Both YOLOv9 and YOLOv10 are outperformed in terms of accuracy, but they excel in training time, with YOLOv9 producing a more convergent result. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Study of Cross-Site Request Forgery on Web-Based Application: Exploitations and Preventions 8

Study of Cross-Site Request Forgery on Web-Based Application...

引用

8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Siahaan, Crisdeo Nuel Rufisanto, Mario Nolasco, Raymond Achmad, Said Siahaan, Chrisando Ryan Pardomuan Cyber Security Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Cross-Site Request Forgery (CSRF) is a prominent web exploit that continues to pose significant security risks, even on highly ranked websites. This research focuses on identifying the underlying vulnerability, understanding the techniques employed, and proposing effective preventive measures. The hybrid method which is systematic report review method and lab-based scenarios method is conducted to identify CSRF exploitation and prevention mechanisms. Using a scenario-based testing approach, this study investigated the cause and effect of CSRF attacks, uncovering numerous techniques for exploiting this vulnerability. Based on the report review, 35 CSRF vulnerability reports from the Hacker one Bug Bounty Platform are analyzed. The result shows there is a lack of awareness and implementation of primary defenses, resulting in a high violation of end-user data integrity. The result also extensively describes some of the profound causes and effects of CSRF attacks and uncovers a broad range of techniques for exploiting this vulnerability. Furthermore, this study provides actionable recommendations to enhance system security and raise awareness among developers and users. The findings from this research serve as a valuable resource for improving security practices and mitigating CSRF attacks. © 2023 The Authors. Published by Elsevier B.V.

关键词： cross-site request forgery vulnerability web exploitation

来源：评论

学校读者我要写书评

暂无评论

Systematic Literature Review and Comparative Performance Analysis of SQL and NoSQL databases in Big data Applications 6

Systematic Literature Review and Comparative Performance Ana...

引用

6th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2024

作者： Samarta, Muhammad Tsaqif Santoso Gunawan, Alexander Agung Syahputra, Muhammad Edo School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331533243

Today, in the digital moment, when the presence of the Internet in daily life is all around, management of data has become an indispensable part in any kind of organization irrespective of sector. Large-scale data applications are remarkably influenced in prosperity by the choice between SQL and NoSQL databases. This research deals with issues regarding which among database types- SQL or NoSQL-is more effective in Big data environments. The paper consequently benchmarks the key performance indicators such as storage capacity, query execution time, and scalability through a systematic review of literature. SQL databases have been found to be robust with respect to structured data and complex queries, maintaining transactional integrity and consistency. They are, however, limited in scalability and flexibility when handling unstructured data, thus less suitable for specific big data applications. On the other hand, NoSQL databases support availability and flexibility quite well, handle unstructured data in very large volumes, and give support for a variety of data models. This study concludes that organizations have to align database choice with the type of data an organization deals with and scalability requirements for optimal performance in Big data applications. © 2024 IEEE.

关键词： Structured Query Language

来源：评论

学校读者我要写书评

暂无评论

The Feasibility of Using Synthetic-Generated dataset for Training Sentiment Analysis Model 9

The Feasibility of Using Synthetic-Generated Dataset for Tra...

引用

9th International Conference on Information Technology and Digital Applications, ICITDA 2024

作者： Nugroho, Bianca Chelsea Putri Widjaja, Denovan Wijaya, Nicole Sutoyo, Rhio School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331510732

New features in machine learning applications are constantly being explored demanding the availability and quality of data. To address this, the exploration of synthetic data emerges as a promising solution. This paper intends to solve the problem of data availability by finding out the feasibility of using synthetic data as a solution. Many researchers tried to use algorithms such as SMOTE and ADASYN, but encountered challenges in producing semantically and grammatically acceptable material. One of the few front-runners in synthetic text data generation is GPT 3.5. A trained sentiment analysis model would benefit users greatly by providing valuable insights into given text data, helping to understand emotions, opinions, and trends. The criteria of a high-quality dataset is providing various examples for each class. High-quality training data is crucial for accurate sentiment analysis, ensuring correct patterns, bias minimization, and reliable predictions. This paper utilizes GPT 3.5 to generate the synthetic data, with BERT and CNN-LSTM as the model architectures. Each architecture employs three models, each with a unique train-test combination that serves its own purpose. The performance of the six trained models is compared based on accuracy, precision, recall, and F1 score to evaluate the quality and efficacy of synthetic data. The conducted evaluation shows that data augmentation using synthetic data is feasible. This finding is presented as the main contribution of the study. However, fully synthetic data-trained models require more refining. © 2024 IEEE.

关键词： data assimilation

来源：评论

学校读者我要写书评

暂无评论

Stunting Prediction in Children Using Random Forest Algorithm 6

Stunting Prediction in Children Using Random Forest Algorith...

引用

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

作者： Kanz, Ahmad Fauzan Johanes, Luvky Pratama Alam, Islam Nur Wulandhari, Lili Ayu Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798331539603

Stunted child growth and development caused by chronic malnutrition has remained a significant global public health problem worldwide, especially in low-and middle-income countries. Thus, it is essential to employ effective predictive models that can identify those at risk so as to implement appropriate interventions. In this research, a predictive model for childhood stunting based on artificial intelligence (AI) methods will be introduced. The machine learning algorithms and statistical techniques are employed in the model which integrates several socio-economic, demographic, dietary and health related factors to predict stunting among children under five years of age. This includes training the model using survey data that is nationally representative as well as longitudinal studies to ensure its reliability and applicability across populations with different characteristics. Some of the metrics used to assess the predictive performance include accuracy, sensitivity, specificity and area under receiver operating characteristic curve (AUC-ROC). Many interpretability techniques have been utilized to highlight the primary factors associated with an increased risk of stunting thereby becoming a valuable tool for policy makers and health care providers in planning focused interventions and resource allocation effectively. Utilizing AI, this predictive model presents a proactive strategy to address childhood stunting, ultimately enhancing child health and well-being globally. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

A Transfer Learning based Deep Learning Framework for Lung Disease Detection Utilizing CXR Images

A Transfer Learning based Deep Learning Framework for Lung D...

引用

2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Kansal, Kajal Kansal, Kanika School of Computer Science Engineering and Technology Bennett University Uttar Pradesh Greater Noida India Abes Engineering College Department of Computer Science and Engineering - Data Science Uttar Pradesh Ghaziabad India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527495

The classification of various lung diseases with the help of chest X-ray images is one of the significant and challenging issues in medical imaging applications. This work proposes a transfer learning-based deep neural network architecture to classify lung diseases using a publicly available dataset. The proposed DenseNet201 model uses the interconnected structure to optimize feature transmission, minimize computation redundancy, and improve the gradient flow. The proposed model achieved a better classification accuracy of 98.34% compared to the other existing methods. These results show that DenseNet201 effectively learns discriminative features from the input medical image data. The proposed framework is suitable for large-scale implementation of lung disease classification. It helps develop more efficient computer-aided diagnostic systems, assisting clinicians in decision-making. © 2025 IEEE.

关键词： Lung cancer

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 << < 31 32 33 34 35 36 37 38 39 40 > >>

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

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：