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

2,264 篇 会议
18 篇 期刊文献
16 册 图书

馆藏范围

2,298 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,928 篇 工学
- 1,213 篇 计算机科学与技术...
- 961 篇 软件工程
- 390 篇 信息与通信工程
- 235 篇 控制科学与工程
- 218 篇 机械工程
- 167 篇 电子科学与技术（可...
- 164 篇 化学工程与技术
- 158 篇 材料科学与工程（可...
- 154 篇 电气工程
- 128 篇 仪器科学与技术
- 126 篇 环境科学与工程（可...
- 115 篇 生物医学工程（可授...
- 97 篇 生物工程
- 92 篇 动力工程及工程热...
- 90 篇 土木工程
- 78 篇 建筑学
- 70 篇 光学工程
- 69 篇 冶金工程
- 68 篇 安全科学与工程
822 篇 理学
- 448 篇 数学
- 157 篇 物理学
- 121 篇 统计学（可授理学、...
- 116 篇 生物学
- 114 篇 系统科学
- 112 篇 化学
- 102 篇 生态学
506 篇 管理学
- 326 篇 管理科学与工程(可...
- 198 篇 图书情报与档案管...
- 144 篇 工商管理
75 篇 医学
71 篇 经济学
- 71 篇 应用经济学
62 篇 教育学
58 篇 法学
51 篇 农学
15 篇 艺术学
11 篇 军事学
5 篇 文学
1 篇 哲学

主题

35 篇 data mining
30 篇 educational inst...
26 篇 mobile ad hoc ne...
25 篇 wireless sensor ...
24 篇 bioinformatics
24 篇 genetic algorith...
19 篇 image segmentati...
19 篇 authentication
19 篇 cloud computing
17 篇 feature extracti...
17 篇 web services
17 篇 genomics
16 篇 quality of servi...
16 篇 routing protocol...
15 篇 support vector m...
15 篇 computational mo...
15 篇 remote sensing
15 篇 cryptography
14 篇 students
12 篇 computers

机构

29 篇 college of compu...
12 篇 school of comput...
11 篇 chongqing normal...
11 篇 school of comput...
9 篇 college of physi...
9 篇 college of compu...
8 篇 school of comput...
8 篇 information and ...
7 篇 school of comput...
7 篇 department of co...
6 篇 department of co...
6 篇 school of comput...
6 篇 school of comput...
6 篇 department of co...
6 篇 school of mechan...
6 篇 college of compu...
6 篇 school of softwa...
5 篇 school of inform...
5 篇 college of elect...
5 篇 college of manag...

作者

12 篇 ma yan
8 篇 zhang kun
8 篇 dhavachelvan p.
7 篇 wang jing
6 篇 wang hai-feng
6 篇 song li
6 篇 maode ma
6 篇 yuhang yang
6 篇 li ming
6 篇 he guotian
6 篇 ramesh t.
6 篇 mannava vishnuva...
6 篇 wang jun
5 篇 jiapeng xiu
5 篇 xu jing
5 篇 sukumar nandi
5 篇 chen liu
5 篇 liu fuyan
5 篇 li ying
5 篇 xu lijun

语言

2,265 篇 英文
32 篇 中文
1 篇 其他

检索条件"任意字段=2012 2nd International Conference on Advances in Computer Science and Engineering, CES 2012"

共 2298 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：

Explaining YOLOv9 Object Detection with Attribution-Based Heatmap Methods 2

Explaining YOLOv9 Object Detection with Attribution-Based He...

引用

2nd IEEE international conference on Electrical, Automation and computer engineering, ICEACE 2024

作者： Fan, Siyuan Fudan University School of Information Science and Technology China

ISBN: (纸本)9798350368208

This study investigates the problem of explainability for visual object detectors, focusing on the YOLOv9 object detection model. The model is fine-tuned on the VOC2012 dataset using a pre-trained YOLOv9 model. The study demonstrates various attribution-based heatmap methods into the YOLOv9 architecture and analyzes their effectiveness in explaining individual detections. The attribution methods explored include Grad-CAM++, Grad-CAM, XGrad-CAM, Eigen-CAM, HiResCAM, LayerCAM, RandomCAM, and Eigen Grad-CAM. The analysis reveals that different methods provide unique perspectives about the model's functioning, suggesting that the choice of attribution-based method can significantly influence the interpretation of the model's predictions. In the study, Layer-CAM and HiRes-CAM consistently demonstrate superior performance in visualizing the features learned by the YOLOv9 model. This study provides valuable insights into the explainability of the YOLOv9 object detection model, highlighting the importance of selecting the right attribution method for model interpretation. The findings suggest that improving the transparency of such models can enhance their trustworthiness and applicability in real-world tasks, particularly in domains where interpretability is crucial. © 2024 IEEE.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

Crime Against Women in India: Statistical Analysis Using Linear Regression 2

Crime Against Women in India: Statistical Analysis Using Lin...

引用

2nd international conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Mim, Zarin Tasnim Paul, Rittika Foysal, Mollah Md Tohfa, Fairuz Nowshin Mahi, Shah Abrar Bangalore India Bangalore India B-Tech of Computer Science and Engineering East Delta University Chattagram Bangladesh B-Tech of Computer Science and Engineering-Cyber Security Chandigarh University Delhi India

ISBN: (纸本)9798331519056

The crime reports of offenses occurring against women all over India are increasing day by day. It has become one of today's most concerning socio-economic and cultural issues. Crime against women hampers the overall prosperity and development of the nation. This crime violates human rights, impacts women's physical and mental health, and becomes an educational barrier to women's empowerment. This paper surveys the reasons for the influence of reported Crime Against Women (CAW) in 35 states and union territories in India from 2001-2012. The dataset describes different types of Crime Against Women (CAW): rape, kidnapping, abduction, assault on women, insult to the modesty of women, cruelty by husband or relative. This paper also contains a report on the arrested rate for crimes against women in India from 2001-2012. According to the comparison between these two datasets, the person arrest rate is more than the crime against women rate in every state in India. We used machine learning-based linear regression analysis to format the relationship between two datasets, where crime against women is the dependent variable and people arrested rate is the independent variable. This paper discusses two types of linear regression: Simple Linear Regression and Multiple Linear Regression. The relation between these two datasets helps to predict the hot location of crimes, and the activeness of law enforcement regarding the crimes and encourages victims to take action. For the datasets, P-values, R-squared, and adjusted R-squared values are used to evaluate the statistically significant prediction in explaining the variation in crime rates. This prediction is used to reduce the rate of crime against women all over India. © 2024 IEEE.

关键词： Multiple linear regression

来源：评论

学校读者我要写书评

暂无评论

A lightweight attention-guided semantic segmentation network using a group convolution pyramid 2

A lightweight attention-guided semantic segmentation network...

引用

2nd international conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2023

作者： Yu, Siyu Huang, Dandan Wang, Guixian Yao, Anni Changchun University of Science and Technology School of Electronic Information Engineering Changchun China Name of Changchun University of Science and Technology School of Electronic Information Engineering Changchun China

ISBN: (纸本)9798350342697

Semantic segmentation is a key part of computer vision tasks, but its application is greatly limited by memory capacity and computational cost. This paper proposes a lightweight attention-guided semantic segmentation network (LAGNet) that adopts a joint group convolution pyramid strategy. Specifically, we introduced a lightweight symmetric double attention module (LS-DAM) and an adaptive selection interaction module (ASIM). In the LS-DAM, the self-attention adopts adaptive maximum pooling and average pooling instead of its previous form, in which the pixel-by-pixel similarity is calculated. Moreover, The ASIM has the capability to seamlessly integrate both high-level semantic information and low-level geometric information, leading to a remarkable enhancement in the performance of semantic segmentation. We evaluate our proposed LAGNet model using mean intersection over union (mIoU) on PASCAL VOC 2012 and Cityscapes, two commonly used datasets in the field of semantic segmentation, and finally achieve state-of-the-art performance of 81.73% and 81.90%, respectively. © 2023 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Exploratory Data Analysis and Data Visualization on Accidental Drug Related Deaths 2

Exploratory Data Analysis and Data Visualization on Accident...

引用

2nd international conference on Computing and Data Analytics, ICCDA 2024

作者： Ogwo-Ude, Ezinne Hasan, Raza Ahmad, Shakeel Mahmood, Salman Solent University Department of Science and Engineering Southampton United Kingdom Nazeer Hussain University Department of Computer Science Karachi Pakistan

ISBN: (纸本)9798331542573

The drug overdose epidemic in the United States is rapidly getting worse with substantial associated public health effects. Covering 10,654 cases over a decade (2012-2022), this study analyses an extensive dataset of accidental drug-related deaths in Connecticut. We process and analyze this data using Python and Tableau, we then use LSTM to predict how many people will show up in the designated intervals. The ages of individuals were stated as a mean value 43.52 (SD =12.60) years with a range between 13 and 87 years, bimodally distributed around the mid-30s to mid-50's. Overall, 74.14% were male and 85.48 % white in race/ethnicity. Significant increases were seen in accidental drug-related deaths. The most implicated substances were any opioids, fentanyl (alone or in combination), cocaine alone, heroin and ethanol. Crucially, some 89.05% of the cases had co-abuse with multiple drugs by one person who showed evidence that poly-substance use is commonplace in this community. Most deaths involved fentanyl (309, with a mode at 36 years (229 out of 309 deaths) and r (0.51) associated with 'any opioid', the primary cause of death). New Haven, Hartford and Fairfield counties stood out as hotspots for overdoses in geographic analysis. The LSTM model achieved a Root Mean Square Error (RMSE) of 7.25 and a Mean Absolute Error (MAE) of 5.62, predicting a sustained annual increase in deaths over the next three years. This federal and state partnership provides a model for using existing surveillance resources to inform targeted overdose intervention strategies, with an emphasis on the rise of fentanyl positivity among decedents. © 2024 IEEE.

关键词： Lanthanum alloys

来源：评论

学校读者我要写书评

暂无评论

Interpretable MOOC Dropout Prediction using Different Ensemble Methods and XAI 2

Interpretable MOOC Dropout Prediction using Different Ensemb...

引用

2nd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Khan, Labib Hasan Haque, Mohammed Ashfaqul Ibrahim, Esaba Ahnaf Mostakim, Moin Hossain, Muhammad Iqbal Brac University Dept. of Computer Science & Engineering Dhaka Bangladesh

ISBN: (纸本)9781665456302

Massive open online course (MOOC) has been around for several years, which started to gain traction in 2012 when Coursera was established. MOOCs use pre-recorded lectures and scheduled weekly tests to provide content and access to students over the internet. The dataset used in this study is taken from the KDDCUP 2015 dataset, a publicly available dataset. Here, 12 features are considered, they are browser access, navigate, average chapter delays, etc to comprehend the possibility of dropout. This research study intends to predict the dropout of a learner so that it can be prevented through manual interaction. Additionally, XAI is implemented to inter-pret the models to suggest MOOC platforms, which feature impact dropout the most. Further, different ensemble learning techniques, namely voting classifier and stacking are used. The proposed voting classifier uses five of the best-performing machine learning models. Then, the performance of the model is evaluated by using multiple metrics such as precision, recall, and F1-score. Finally, a recall of 97.636 % has been obtained with stacking and f1-score of 91.603 % has been obtained with the hard voting classifier. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Stock Prices Prediction Using Machine Learning 2

Stock Prices Prediction Using Machine Learning

引用

2nd international conference for Innovation in Technology, INOCON 2023

作者： Gupta, Aditi Akansha Joshi, Khushboo Patel, Madhu Pratap, Vibha Indira Gandhi Delhi Technical University for Women Department of Computer Science and Engineering New Delhi India

ISBN: (纸本)9798350320923

Precise prediction of the stock market is incredibly difficult due to how volatile and non-linear it is. The growth of artificial intelligence and improvements in processing power have increased the accuracy of programmed methods of prediction in predicting stock values. In this paper, we used Multilayer Linear-Regression, Convolutional Neural Network (CNN), and long short-term memory (LSTM) algorithms to analyze the price trends over different time periods to predict the closing price of five companies, operating in different sectors. The final features we used were open, high, low, and close prices (OHLC), which were chosen using data pre-processing techniques. The dataset we used was made up of daily prices from 3 November 2012 to 3 November 2022. The number of previous days that would be required to predict the current day's closing price is known as the sequence length. Then, using a different set of information, we adjusted this length and evaluated the accuracy. Our models performed the best for a sequence length of 5 and LSTM outperforms other models for each company's dataset with different sequence lengths. © 2023 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Forecasting of Statistical Crisp Weather in India by Exploration of Different Machine Learning Techniques 2

Forecasting of Statistical Crisp Weather in India by Explora...

引用

2nd international conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Sahu, Premananda Kumar Mohapatra, Srikanta Kumar Sarangi, Prakash Srmist Department of Computer Science and Engineering UP Ghaziabad India Chitkara University Institute of Engineering and Technology Chitkra University Punjab India Vardhaman College of Engineering and Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9781665437899

The winter season starts suddenly in the mid of the Dew and ends in Spring. If we will analyze in a better way, the cold starts in the mid of October and continue up to mid of February month. Generally, some the states like Jammu, Kashmir, Uttar Pradesh, Uttarakhand, Punjab etcetera the people are suffering from a heavy cold. At that time the temperature is as much as decreased so that the old generation people cannot tolerate it. Sometimes also the meteorological department is very busy predicting temperature because in India other natural disasters like floods, droughts, cyclones etcetera are also coming suddenly. So in this investigation work, we have designed an automatic model for crisp weather forecasting which may be considerate to the people, so that they can take precautions earlier. For this work, we have worked for Odisha state for the investigation purpose which uses barometric parameters as well as the machine learning techniques like Support Vector Machine along with Random Forest for our investigation work. The dataset that we have used is IMD which is used for both training and testing. In this model, we have used two prognoses which are based on five and seven days respectively. The contrast result babbles 5 days produce better classification accuracy than 7 days' prediction. © 2022 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Multi-scale small object detection based on improved Faster R-CNN 2

Multi-scale small object detection based on improved Faster ...

引用

2nd international conference on Green Communication, Network, and Internet of Things, CNIoT 2022

作者： Ye, Chengzhuo Qin, Renchao Li, Ya He, Yaying Jiang, Ruilin Shu, Yue Yin, Zhanhong School of Computer Science and Technology Southwest University of Science and Technology Sichuan Mianyang621000 China

ISBN: (纸本)9781510662940

Aiming at the problem that the traditional Faster R-CNN is not sensitive to small targets and occluded targets, this paper submits an improved Faster R-CNN target detection algorithm. In this paper, using PASCAL VOC07+2012 to be the experimental data sample set. For the large differences in the targets to be detected in this set, the general anchor size and dimensions is not often used for detecting multi-category problems. For the purpose of increasing small objects detection accuracy, using K-means to improve this situation. The annotation information is centralized for clustering, and the clustering result is replaced by the anchor scale and size in the original RPN. Finally, missed detection and false detection caused by partial overlap of objects in the image, this paper uses the improved soft-NMS algorithm. The experimental results show that, compared with the traditional Faster R-CNN algorithm, the average mean precision (mAP) of the algorithm under the PASCAL VOC07+2012 dataset can reach 80.7% and it is enhanced by 6.5 percentage points. © 2023 SPIE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Optimized FOREX Rate Prediction Using Hybrid Machine Learning Algorithm 1

引用

2nd international conference on Intelligent Computing Systems and Applications, ICICSA 2023

作者： Latha, Challa Madhavi Bhuvaneswari, S. Soujanya, K.L.S. Department of Computer Science School of Engineering and Technology Pondicherry University Pondicherry Karaikal India Department of Information Technology CMR College of Engineering and Technology Medchal Hyderabad Kandlakoya India

ISBN: (数字)9789819754120

ISBN: (纸本)9789819754113

This research examines the application of fuzzy time series (FTS) models and different machine learning techniques to anticipate changes in foreign exchange (FOREX) data. The statistics used in this investigation include the actual FOREX prices and the high and low values of four different currencies. These statistics begin from January 2012 to November 2022;the data is available on the Reserve Bank of India website. This article investigates the significant flaws present in the literature information on FTS. This article identifies fundamental flaws in all FTS-based algorithms presently available in the literature and shows how to fix them. The study then describes the unique structure of improvised FTS. The Hybrid Machine Learning Algorithm is the name given to this structure. The purpose is to solve the identified issues present in FTS-based models previously published in the literature. The result was compared with the before and after optimization processes. After implementing the proposed hybrid machine learning algorithm, the result shows the better accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Research on semantic segmentation technology based on attention mechanism and residual learning 2

Research on semantic segmentation technology based on attent...

引用

2nd international conference on Digital Signal and computer Communications, DSCC 2022

作者： Liu, Tao Yan, Piao Qin, Denghui School of Electronic and Information Engineering Changchun University of Science and Technology Changchun China

ISBN: (纸本)9781510656734

Aiming at the problem that the image edge is blurred and the middle hidden layer features are lost in image semantic segmentation, the attention mechanism of joint training in channel domain and spatial domain is proposed, and the multi-objective joint training loss function and residual connection module are used to learn the semantic features in semantic segmentation, and the hidden layer features in the process of network training are added to the calculation of loss value. The experimental results show that the introduction of multi-channel attention mechanism and residual connection in semantic segmentation network is helpful to improve the effect of semantic segmentation. Pascal voc2012 data set was used in the experiment. © 2022 SPIE.

关键词： Semantic Segmentation

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230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：