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

422 篇 会议
158 篇 期刊文献
2 册 图书

馆藏范围

582 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

328 篇 工学
- 234 篇 计算机科学与技术...
- 193 篇 软件工程
- 87 篇 信息与通信工程
- 61 篇 生物工程
- 59 篇 生物医学工程（可授...
- 39 篇 控制科学与工程
- 36 篇 电气工程
- 31 篇 化学工程与技术
- 26 篇 电子科学与技术（可...
- 25 篇 光学工程
- 22 篇 仪器科学与技术
- 21 篇 机械工程
- 19 篇 安全科学与工程
- 17 篇 材料科学与工程（可...
- 17 篇 网络空间安全
209 篇 理学
- 96 篇 数学
- 71 篇 生物学
- 58 篇 物理学
- 38 篇 统计学（可授理学、...
- 29 篇 化学
- 27 篇 系统科学
107 篇 管理学
- 59 篇 图书情报与档案管...
- 44 篇 管理科学与工程(可...
- 21 篇 工商管理
51 篇 医学
- 40 篇 临床医学
- 36 篇 基础医学(可授医学...
- 24 篇 公共卫生与预防医...
- 20 篇 药学(可授医学、理...
35 篇 法学
- 34 篇 社会学
14 篇 文学
- 14 篇 新闻传播学
11 篇 经济学
8 篇 农学
4 篇 教育学
2 篇 军事学

主题

23 篇 feature extracti...
19 篇 accuracy
18 篇 deep learning
17 篇 training
15 篇 support vector m...
15 篇 machine learning
12 篇 computer science
12 篇 optimization
11 篇 internet of thin...
11 篇 diseases
10 篇 image color anal...
9 篇 information tech...
9 篇 algorithm design...
9 篇 forecasting
8 篇 transfer learnin...
8 篇 image segmentati...
8 篇 medical services
8 篇 data mining
8 篇 computational mo...
8 篇 predictive model...

机构

129 篇 computer science...
35 篇 computer science...
26 篇 khulna universit...
21 篇 computer science...
19 篇 computer science...
17 篇 computer science...
17 篇 discipline of co...
15 篇 khulna universit...
12 篇 discipline of co...
10 篇 electronics and ...
9 篇 electronics and ...
9 篇 electronics & co...
7 篇 department of co...
6 篇 university colle...
6 篇 ai innovation la...
5 篇 discipline of co...
5 篇 north western un...
5 篇 computer science...
5 篇 discipline of bu...
4 篇 leeds institute ...

作者

18 篇 bairagi anupam k...
16 篇 islam md. rafiqu...
15 篇 md. rafiqul isla...
15 篇 anupam kumar bai...
14 篇 nahid abdullah-a...
13 篇 abu shamim moham...
13 篇 arif abu shamim ...
12 篇 sikder niloy
12 篇 rameswar debnath
11 篇 md. mahbubur rah...
10 篇 debnath rameswar
10 篇 talukder kamrul ...
10 篇 neminath hubball...
10 篇 kamrul hasan tal...
9 篇 raihan m.
9 篇 abdullah-al nahi...
8 篇 mrityunjoy gain
8 篇 s. a. ahsan rajo...
8 篇 nag anindya
8 篇 niloy sikder

语言

558 篇 英文
18 篇 其他
7 篇 中文
1 篇 德文
1 篇 法文

检索条件"机构=Computer Science and Engineering Discipline"

共 582 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：

Granularity-based Comparison of the Change-proneness of Micro-Clones 15

Granularity-based Comparison of the Change-proneness of Micr...

引用

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

作者： Shanto, Mehedi Hasan Rony, Mohammad Asaduzzaman Debnath, Rameswar Mondal, Manishankar Khulna University Computer Science and Engineering Discipline Bangladesh

ISBN: (纸本)9798350370249

Regular clones (i.e., identical or substantially equivalent code fragments greater than 4 LOC) inside a software system's code-base have been thoroughly examined by several studies. In our research, we investigate the change-proneness of micro-clones (i.e., code clones of at most 4 LOC). In particular, we compare the change-proneness of function and block level micro-clones. An empirical study shows that micro-clones are a growing concern since the number of micro-clones is three times as much as the number of regular clones in a software system. Analyzing the impacts of function and block level micro-clones is very useful for developers because they can realize which granularity (function or block) is more important for software maintenance and evolution. When it comes to managing clones, developers should pay more attention to code clones that are subject to frequent modifications, sometimes called unstable clones, from an evolutionary perspective. They can prioritize the more change-prone micro-clones for refactoring or tracking. We investigated the micro-clone category of function level and block level for 5 diverse subject systems from the SVN repository and analyzed their change-proneness by using UNIX diff. We found that micro-clones of function granularity are generally more change-prone than micro-clones of block granularity. Thus, function level micro-clones should be prioritized more for management, such as refactoring and tracking. © 2024 IEEE.

关键词： change-proneness granularity micro-clone refactoring

来源：评论

学校读者我要写书评

暂无评论

Enhanced YOLOv9-Based Endangered Tiger Detection Framework for Wildlife Surveillance

Enhanced YOLOv9-Based Endangered Tiger Detection Framework f...

引用

2024 IEEE International Conference on Signal Processing, Information, Communication and Systems, SPICSCON 2024

作者： Nabil, Rahat Morshed Kundu, Tarunnyamoye Computer Science and Engineering Discipline Khulna University Khulna Bangladesh

ISBN: (纸本)9798331510213

Tiger conservation requires integrating diverse strategies, including preserving natural habitats, stringent anti-poaching efforts, and active community participation to ensure sustainable tiger population growth. The emergence of artificial intelligence presents an opportunity to enhance tiger surveillance through automated object detection. This paper introduces a robust, illumination-invariant framework that leverages EnlightenGAN and the advanced YOLOv9c model for detecting Amur tigers. The fine-tuned YOLOv9c model, coupled with illumination enhancement techniques, achieves an impressive mAP50-95 score of 71.2% and an mAP50 score of 98.7% on the ATRW dataset. This approach significantly advances the state-of-the-art in tiger detection and highlights the potential of AI-driven solutions in wildlife conservation. © 2024 IEEE.

关键词： Invertebrates

来源：评论

学校读者我要写书评

暂无评论

Diagnosis of Pulmonary Embolism from CT Pulmonary Angiogram by Using Deep Transfer Learning and Sobel Filter 15

Diagnosis of Pulmonary Embolism from CT Pulmonary Angiogram ...

引用

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

作者： Haque, Md. Azizul Shome, Atanu Bairagi, Anupam Kumar Khulna University Computer Science and Engineering Discipline Khulna Bangladesh

ISBN: (纸本)9798350370249

Pulmonary embolism (PE) indicates a blood thrombus that travels toward the lungs and can lead to significant morbidity and mortality. Thus, early diagnosis and treatments are crucial. An efficient PE detection mechanism can improve radiologists' productivity by helping to prioritize critical cases and speed up at-risk patient diagnoses. The standard mechanism for diagnosing PE is the chest computed tomography pulmonary angiogram (CTPA) images. A subset of 15000 samples, including normal and PE-positive lung CTPA images were taken from the largest multinational publicly available RSNA-PE-CT dataset for our purpose. Noise and spatial aliasing in CTPA images can make it challenging to discern boundaries between different anatomical structures or abnormalities;therefore, an edge detection filter (Sobel) was deployed to remove noise and highlight the edges in the original image. In this study, PE in lung CTPA image is detected using deep transfer learning models, which utilize Convolutional Neural Network (CNN), a widely used deep learning (DL) technique. All selected models were trained and validated by adjusting the hyperparameters, which included the layers, loss function, activation function, rate of learning, and epoch number. Nonetheless, compared to other CNN-based frameworks such as MobileNetV2, Xception, InceptionV3, and ResNet50, the customized Sobel Filter-based DenseNet169 (SF-DenseNet169) model performs better. The SF-DenseNet169 model obtained the maximum training accuracy (97.32%) and validation accuracy (96.67%) with minimal loss. As a result, we propose the improved SF-DenseNet169 model to be the effective and reliable means to diagnose PE-positive patients automatically. © 2024 IEEE.

关键词： computerized tomography

来源：评论

学校读者我要写书评

暂无评论

Prediction of Lung Cancer using Genetic Algorithm and Machine Learning Technique 15

Prediction of Lung Cancer using Genetic Algorithm and Machin...

引用

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

作者： Mou, Shahida Islam Arif, Abu Shamim Mohammad Khulna University Computer Science and Engineering Discipline Khulna Bangladesh

ISBN: (纸本)9798350370249

As Lung cancer is a life-threatening disease for human beings, for the sake of saving lives, early detection of lung cancer is obligatory. Many existing methods have been proposed to predict lung cancer, but there is a scope to enhance the effectiveness of the existing methods with an optimal number of features. We have proposed a method based on Machine Learning (ML) and Genetic Algorithm (GA) approaches to predict lung cancer. The dataset has been collected from ***. In our proposed method, we optimized the features using the feature selection technique and applied the ML method to classify lung cancer patients. The GA's fitness function and operators have been designed for feature selection. Three classifiers were employed for the classification of Decision Tree, XG Boost, and Support Vector Machine (SVM). In this study, our proposed method reached 100% accuracy, which left behind other existing methods with 13 out of 24 features. In light of the experiment's outcomes, the proposed method outperformed the other strategies currently using the fewest features. © 2024 IEEE.

关键词： accuracy feature genetic algorithm prediction support vector machine

来源：评论

学校读者我要写书评

暂无评论

Cardiovascular Disease Detection Using Machine Learning Algorithms

Cardiovascular Disease Detection Using Machine Learning Algo...

引用

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

作者： Mondal, Henreata Talukder, Kamrul Hasan Khulna University Computer Science & Engineering Discipline Khulna Bangladesh

ISBN: (纸本)9798350350289

Cardiovascular diseases (CVDs) are considered as the prime cause of death across the globe. Early and highly accurate detection of heart diseases can really be helpful for the world population. Addressing this problem on a large scale is essential for keeping the world healthy. Machine learning (ML) algorithms play a vital role in detecting cardiovascular diseases, offering the potential for higher accuracy in identification. Achieving precise detection with ML algorithms holds significant benefits for people worldwide. Our research utilizes various ML algorithms including Gaussian Naive Bayes (GNB), Random Forest (RF) and Logistic Regression (LR) to identify cardiovascular diseases. After assessing individual model accuracies, we combine GNB, RF and LR using hard voting, creating the 'voting-model'. Additionally, a stacking classifier is applied using GNB, RF, LR as base estimators and LR as the final estimator. The ensemble approach demonstrates maximum accuracy compared to individual models highlighting the potential of combining diverse algorithms through ensemble learning for enhanced predictive models in cardiovascular health. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Under Water Objects Detection and Classification using Deep Learning Technique

Under Water Objects Detection and Classification using Deep ...

引用

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

作者： Roy, Jyoti Talukder, Kamrul Hasan Khulna University Computer Science & Engineering Discipline Khulna Bangladesh

ISBN: (纸本)9798350350289

Seas and oceans, vital sources of food and critical reservoirs of sustenance and ecological balance, present formidable challenges to exploration due to their profound depths. Addressing this, the integration of deep learning with autonomous robots emerges as a pivotal solution for the real-time detection and classification of underwater objects through the analysis of images captured in challenging conditions. Our key objective of this research is to find an impressive deep learning method that can be useful for underwater objects detection and classification in challenging conditions. This paper talks about making deep learning models better for underwater places. It deals with problems like low light, blurry images, and noisy environment in the water. Focusing on 'The Brackish Dataset' our research leverages the YOLOv8 models, augmented with the MaxRGB filter, to robustly detect and classify underwater entities. We use MaxRGB filter in our experiment to increase the content separability in images. A thorough performance evaluation, including precision, recall and comparison with state-of-the-art models from prior work, proves the effectiveness of our approach. Our detector archives 98.6% mean average precision and classifier gains 99.6% classification accuracy. The findings not only affirm the suitability of YOLOv8 for underwater exploration but also highlight its potential strength in diverse fields, such as marine resource identification, rescue operations and ecosystem preservation. The intersection of deep learning and underwater environments opens new avenues for technological advancements with far-reaching implications for both scientific research and practical applications. © 2024 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

KULemma: Towards a Comprehensive Bangla Lemmatizer 6

KULemma: Towards a Comprehensive Bangla Lemmatizer

引用

6th International Conference on Electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Islam, Saimum Alam, Kazi Masudul Khulna University Computer Science and Engineering Discipline Khulna Bangladesh

ISBN: (纸本)9798350385779

Lemmatization is a natural language processing (NLP) based text normalization technique that effectively improves data consistency and assists in context interpretation. Nevertheless, due to the highly inflected nature and morphological richness of linguistics, lemmatization in Bangla NLP holds a thorny challenge. In this research work, we take the challenge to build a comprehensive Bangla lemmatizer. We concreted homogeneous resources by compiling heterogeneous resources, assembled root words, collected linguistic rules, and applied the Trie along with 'Longest Substring Search by Removing Affix (LSSRA)' to develop the lemmatizer. Our system aimed to lemmatize words based on their parts of speech within a given sentence and utilized the sequences of suffix marker occurrence according to the morpho-syntactic values by operating the longest suffix stripping methodology. The lemmatizer achieved an accuracy of 96.90% and experimented against a manually annotated test dataset. © 2024 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Ensem-EnsemHAR: Human Activity Recognition using Ensemble of Ensemble Methods and Smartphone Sensor Data 15

Ensem-EnsemHAR: Human Activity Recognition using Ensemble of...

引用

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

作者： Mohidul Islam, S.M. Talukder, Kamrul Hasan Computer Science and Engineering Discipline Khulna University Khulna Bangladesh

ISBN: (纸本)9798350370249

Recognizing human activity has many applications in real life such as in biometrics, military, security, medical care applications, etc. In this paper, we proposed a new activity recognition method using the voting fusion of various ensemble methods. The data are subject-wise split into training and test sets to accomplish a person-independent recognition model. As base ensemble methods we have used random forest, extra-trees, AdaBoost, Histogram-based Gradient Boost, and XGBoost classifier. The hyper-parameters of base ensemble methods are fine-tuned using four different methods: RandomizedSearchCV, HalvingRandomSearchCV, GridSearchCV, and HalvingGridSearchCV. The recognition accuracies of each base ensemble for various parameter tuning techniques as well as for scikit-learn default values of the parameters are compared and we selected those values of hyper-parameters for which we obtained the highest recognition accuracy. Then the base ensembles are used in a voting ensemble which provides the final recognition result. The prediction results show the robustness of the proposed method to many similar existing methods, especially for unbalanced datasets. ©2024 IEEE.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

Enhancing Healthcare with Desktop Companion Bot: A Novel computer Vision Approach

Enhancing Healthcare with Desktop Companion Bot: A Novel Com...

引用

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

作者： Kundu, Tarunnyamoye Nabil, Rahat Morshed Khulna University Computer Science and Engineering Discipline Khulna Bangladesh

ISBN: (纸本)9798350350289

In recent times, the escalating use of screens, particularly in work environments, has resulted in extended periods of sitting for coders, designers, and engineers. This prolonged screen time has led to the emergence of physical and mental health issues among individuals who are both busy and less health-conscious. Recognizing the prevalence and expanding market for Desktop Companion Bots (DCBs), it is evident that there is a pressing need for research and development in the realm of low-cost *** existing bots cater to entertainment purposes, there is a noticeable gap in the healthcare sector, addressing both physical and psychological well-being. This study aims to fill this gap by developing a DCB named Baymin 1.0, focusing on core features and utilizing fundamental hardware such as Raspberry Pi-4 and a webcam. Baymin 1.0 incorporates computer Vision technologies, including OpenCV, TensorFlow Lite, and MediaPipe, to detect user activity and presence. Through continuous data monitoring, Baymin 1.0 provides reminders for prolonged sitting, alerts for adequate water consumption, prompts for correct body posture, and integrates amusement activities. This research significantly contributes to the field of robotics, emphasizing the utility of DCBs in healthcare. Unlike previous studies that primarily focused on desktop companion bots for entertainment and conversation, this paper delves deeper into the integration of health-related functionalities. Baymin 1.0 exhibits swift performance in various scenarios;however, it is essential to note that low-light environments and variations in age may impact the accuracy of the DCB. This study sets the stage for further advancements in the development of DCBs with enhanced health-related features. © 2024 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

BSER: A Learning Framework for Bangla Speech Emotion Recognition 6

BSER: A Learning Framework for Bangla Speech Emotion Recogni...

引用

6th International Conference on Electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Hassan, Md. Mahadi Raihan, M. Hassan, Md. Mehedi Bairagi, Anupam Kumar Khulna University Computer Science and Engineering Discipline Khulna9208 Bangladesh

ISBN: (纸本)9798350385779

Human computer Interaction (HCI) relies on accurate speech emotion identification. Speech Emotion Recognition (SER) analyzes voice signals to classify emotions. English based Speech Emotion Recognition (SER) has been extensively studied, while Bangla SER has not. The study integrates a one-dimensional convolution neural network with a long short-term memory (LSTM) architecture into a fully linked network for SER. Speech categorization requires feature inclusion, which this method achieves. We included Additive White Gaussian Noise (AWGN), signal elongation, and pitch alteration to improve dataset dependability. Mel-frequency cepstral coefficients (MFCC), Mel-Spectrogram, Zero Crossing Rate (ZCR), chromagram, and Root Mean Square Error are analyzed in this study. One-dimensional convolutional neural network blocks extract local information, while LSTM layers catch global trends in our model. Training and testing loss curves, confusion matrix, recall, precision, F1-score, and accuracy are used to evaluate the model. We assessed using two cutting-edge datasets, the SUST Bangla Emotional Speech Corpus (SUBESCO) and the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS). Experimental results show that the suggested BSER model is more resilient than baseline models on both datasets. BSER improves research in this sector and shows that our hybrid model can detect and classify emotions in voice inputs. © 2024 IEEE.

关键词： Convolution

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59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：