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

4,129 篇 会议
38 册 图书
6 篇 期刊文献

馆藏范围

4,173 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,733 篇 工学
- 2,463 篇 计算机科学与技术...
- 2,042 篇 软件工程
- 616 篇 生物工程
- 586 篇 信息与通信工程
- 362 篇 生物医学工程（可授...
- 266 篇 控制科学与工程
- 214 篇 电气工程
- 211 篇 光学工程
- 147 篇 安全科学与工程
- 136 篇 机械工程
- 123 篇 电子科学与技术（可...
- 118 篇 化学工程与技术
- 105 篇 交通运输工程
- 91 篇 动力工程及工程热...
1,368 篇 理学
- 674 篇 数学
- 646 篇 生物学
- 332 篇 统计学（可授理学、...
- 306 篇 物理学
- 197 篇 系统科学
- 127 篇 化学
720 篇 管理学
- 393 篇 管理科学与工程(可...
- 388 篇 图书情报与档案管...
- 237 篇 工商管理
340 篇 医学
- 315 篇 临床医学
- 308 篇 基础医学(可授医学...
- 221 篇 药学(可授医学、理...
- 125 篇 公共卫生与预防医...
159 篇 法学
- 138 篇 社会学
156 篇 教育学
- 154 篇 教育学
141 篇 农学
- 140 篇 作物学
89 篇 经济学
9 篇 军事学
5 篇 文学

主题

522 篇 machine learning
240 篇 deep learning
117 篇 support vector m...
99 篇 adversarial mach...
92 篇 accuracy
92 篇 machine learning...
83 篇 forecasting
74 篇 convolutional ne...
70 篇 predictive model...
69 篇 feature extracti...
57 篇 artificial intel...
53 篇 students
51 篇 learning systems
48 篇 decision trees
48 篇 training
47 篇 reinforcement le...
47 篇 computational mo...
47 篇 computer vision
46 篇 internet of thin...
41 篇 sentiment analys...

机构

46 篇 chitkara univers...
15 篇 graphic era hill...
10 篇 college of manag...
9 篇 graphic era deem...
8 篇 computer science...
8 篇 beijing universi...
7 篇 school of comput...
7 篇 school of comput...
7 篇 school of comput...
7 篇 department of in...
6 篇 università di ca...
6 篇 infn sezione di ...
6 篇 north-west unive...
6 篇 computer science...
6 篇 lovely professio...
6 篇 in2p3 lpc campus...
6 篇 kkr and ksr inst...
6 篇 institut univers...
6 篇 national centre ...
6 篇 greater bay area...

作者

18 篇 kukreja vinay
15 篇 mehta shiva
10 篇 william p.
8 篇 sharma vikrant
7 篇 mahamudul hasan
7 篇 shiva mehta
6 篇 chen a.
6 篇 benoit d.m.
6 篇 ferrara g.
6 篇 ardid m.
6 篇 calvo d.
6 篇 gagliardini s.
6 篇 eddymaoui a.
6 篇 kulikovskiy v.
6 篇 labalme m.
6 篇 gal t.
6 篇 bozza c.
6 篇 khatun a.
6 篇 kalekin o.
6 篇 huang f.

语言

4,030 篇 英文
142 篇 其他
30 篇 中文

检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

共 4173 条记录，以下是4121-4130 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：

Skin Melanoma diagnosis using machine learning and ABCD rule

Skin Melanoma diagnosis using machine learning and ABCD rule

引用

Science and Information Technology in Smart Administration (ICSINTESA), international conference of

作者： Zahra B. Kadeem Qusay O. Mosa dept. Computer Science College of Computer Science and Information Technology Diwaniyah Iraq

ISBN: (数字)9798350376111

ISBN: (纸本)9798350376128

Skin cancer, being the most predominant type of malignant growth, represents more than half of all cancer instances. While melanoma is less common than other skin cancers, it poses the highest risk due to its tendency to metastasize and potentially result in mortality. Nonetheless, early detection significantly increases the chances of curing melanoma. the detection of melanoma poses a considerable challenge, primarily attributed to the minimal interclass variance observed between images of melanoma and non-melanoma, alongside the heightened interclass variance within melanoma images. Hence, it is imperative to formulate a computer-aided Diagnosis (CAD) to identify such lesions and facilitate early disease diagnosis to enhance the probability of patient survival. the proposed methodology consists of a sequence of four distinct phases. the initial stage involves preprocessing, which incorporates the application of filtering and contrast enhancement algorithms such as the Median filter, Dull razor, and Histogram Equalization. the segmentation process proceeds by utilizing Otsu methods in order to detect any anomalies. Subsequently, the following phase involves the extraction of features through GLCM for textural attributes and ABCD base parameters, encompassing asymmetry, border irregularity, color, and diameter. Following this, a model based on artificial neural networks (ANN) is developed by leveraging these extracted traits to discern instances of skin cancer within the provided dataset. this methodology achieves a commendable overall accuracy rate of 99%. Dermatologists may derive significant assistance in their clinical decision-making procedures from this promising breakthrough.

关键词： Training Solid modeling Accuracy Image color analysis Shape Decision making Melanoma Feature extraction Skin Surges

来源：评论

学校读者我要写书评

暂无评论

WellBe: An Intelligent Elderly Care and Well-Being Monitoring System Using Deep learning

WellBe: An Intelligent Elderly Care and Well-Being Monitorin...

引用

Intelligent Technologies (CONIT), international conference on

作者： Atharv Raotole Sailee Sanjay Shirodkar Rahul Shukla Jignesh Sisodia Kailas Devadkar Dept. of Information Technology Sardar Patel Institute of Technology Mumbai India Dept. of Computer Science and Engineering Sardar Patel Institute of Technology Mumbai India

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

Deep learning refers to a subset of machine learning that utilizes deep neural networks to simulate the complex decision-making process of the human brain. In recent years, DL has made remarkable progress in addressing multiple unique challenges faced by most elderly individuals. While there have been significant contributions to independent systems catered for the elderly, there is the existence of an overall integrated AI platform that unifies the use of individual modules for an optimized solution. this paper introduces “WellBe,” an innovative AI system that encompasses an alarm-based fall detection component, a facial emotion recognition (FER) system and a built-in personalized chatbot all under a user-friendly website. the novelty of the work extends beyond the aforementioned components, owing to the implementation of an optimized FER system able to handle wrinkles and changes in skin texture, thereby tailored exclusively for the elderly demographic. the system leverages a custom feature extraction module, fusing facial and wrinkle features, in addition to extending a convolutional neural network (CNN) architecture for accurate emotion classification, achieving promising performance with precision, recall, and F1-scores of 0.87, 0.91, and 0.89 for the “Happy” (one of the predicted emotions) class, respectively. the fall detection component, on the other hand, utilizes a pre-trained YOLOv7 Pose model for the real-time identification of falls, sitting at a performance accuracy of 95.3%. Finally, the personalized chatbot is implemented using a rule-based approach enhanced with the Jaccard similarity algorithm, to facilitate prompt assistance and a sense of companionship to the end user. Overall, the integration of these components into a cohesive website offers a comprehensive solution for enhancing the quality of life for elderly individuals living alone, addressing loneliness, safety, and overall well-being.

关键词： Deep learning Accuracy Feature extraction Chatbots Skin Real-time systems Safety

来源：评论

学校读者我要写书评

暂无评论

Breaking Boundaries: Harnessing the Power of Deep learning Model Design to Predict Diabetes with Artificial Intelligence Assisted Prediction Strategy

Breaking Boundaries: Harnessing the Power of Deep Learning M...

引用

Intelligent Technologies (CONIT), international conference on

作者： N.K. Senthil Kumar S Kalpana K. Karthika A. Anandh Badepalli Anusha P Santhoshini Department of CSE School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Computer science BITS Pilani Dubai campus (BPDC) Dubai UAE Department of Civil Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering Kamaraj College of Engineering and Technology Virudhunagar Tamil Nadu India Department of ECE MLR Institute of Technology Dundigal Hyderabad India Department of Electronics and Communications Engineering RMD Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

Predicting the onset of diabetes at an early stage might greatly mitigate the disease’s devastating effects; the condition is currently incurable and results from chronically elevated blood sugar levels. Predicting the onset of diabetes has been the focus of current efforts within the deep learning community, building on decades of prior study. Nowadays, diabetes is a common and unfortunately incurable health problem. People can’t give their health the attention it needs because of their busy schedules. the food we eat is broken down into glucose, which is then released into our bloodstream. When blood sugar levels are too high, the pancreas secretes a hormone called insulin. A key function of insulin is to facilitate the uptake of glucose by cells for energy production. Identifying diabetes at an early stage can greatly improve the chances of leading a sustainable life. A fruitful way would be to use machine learning algorithms, which can improve themselves with future predictions after being taught and tested with massive amounts of data. this study presents AI-based Diabetes Prediction (AIDP), a model that explores diabetes data to make better predictions about the illness, with the severity of the condition in mind. the suggested rationale is tested against the traditional K-Nearest Neighbor (kNN) learning paradigm to see how well it works. Results from the planned study demonstrate that the model can accurately forecast the onset of diabetes, if not better. When compared to another deep learning method known as kNN, our results reveal that the suggested AIDP attained superior accuracy.

关键词： Deep learning Schedules Accuracy Production Predictive models Prediction algorithms Diabetes

来源：评论

学校读者我要写书评

暂无评论

Deep-Reinforcement-learning-Based Proportional Computation Offloading With User Equipment in Smart Home Edge Computing

Deep-Reinforcement-Learning-Based Proportional Computation O...

引用

computer, Big Data and Artificial Intelligence (ICCBD+AI), international conference on

作者： Haohang Xie Yunlong Tian Li Niu Miao Wang Yonghua Li School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Qingdao Haier Technology Co. Ltd National Engineering Research Center for Digital Home Network Qingdao China Qingdao Haier Intelligent Home Appliance Technology Co. Ltd Qingdao China Haier Youjia Intelligent Technology (Beijing) Co. Ltd Beijing China

ISBN: (数字)9798350373233

ISBN: (纸本)9798350373240

the growing adoption of Internet of things (IoT) applications has resulted in a surge in the offloading of time-sensitive and computationally intensive tasks from IoT devices to mobile edge computing (MEC) servers. In this article, we survey the task partition strategy in a smart home edge computing network with multiple user equipments (UEs) and edge servers (ESs), where each UE runs IoT application and generates computation task periodically. the generated task is allowed to be broken down into several proportions then offloaded to ESs following a task partition strategy designed to minimize both execution latency and energy consumption. We first formulate the task partition problem as a nonlinear programming problem. Subsequently, we introduce an algorithm based on multiagent deep deterministic policy gradient (MADDPG) for UEs to optimize their offloading strategies. In the proposed approach, each User Equipment leverages its local observations as input for an actor network, which generates a task partitioning strategy. Simultaneously, a critic network is trained to enhance the performance of task partitioning. through our simulations, the performance of the proposed algorithm has been confirmed to surpass that of alternative methods in terms of minimizing both delay and energy consumption.

关键词： Surveys Energy consumption Costs Multi-access edge computing Smart homes Partitioning algorithms Delays

来源：评论

学校读者我要写书评

暂无评论

Research on the application of Interactive Media Technology in General Education in the Post-epidemic Era 21

Research on the Application of Interactive Media Technology ...

引用

proceedings of the 2021 4th international conference on E-Business, Information Management and computer Science

作者： Liu Dan Wuhan Business University China

ISBN: (纸本)9781450395687

this article summarizes online teaching and its development process, combs the current status of online teaching, and paves the way for the popularization of online teaching during the epidemic. A horizontal analysis and a vertical analysis are carried out on the general education interaction as a whole. In the horizontal analysis, the mode of general education interaction is mainly analyzed. In the longitudinal analysis, all the teaching modes are integrated to analyze the interactive hierarchical tower of general education from a longitudinal perspective. this article proposes to establish an online learning community to promote the development of interaction, which creatively analyzes the relationship between social constructivism, online learning community and general education interaction. According to the implementation of network teaching policies in various countries, we start from the practice of network teaching for college students and rely on relevant theories to divide network teaching elements into subject, object, channel, content, and effect, so as to draw an online teaching model diagram, and carry out around the model diagram. this article is based on the theory of spreading modes, combined with the actual analysis of the online teaching process framework during the epidemic. through interviews, network ethnography and other methods, under the relevance theory of learning, we examine the various elements of teaching activities function. Starting from the three aspects of teaching content, methods, and evaluation, it comprehensively analyzes the specific practical effects of online teaching during the epidemic, hoping to pave the way for the development of the online teaching industry in the post-epidemic era.

关键词： Effectiveness Analysis

来源：评论

学校读者我要写书评

暂无评论

Developing an Effective Model for Skin Disease Detection: Techniques and Approaches

Developing an Effective Model for Skin Disease Detection: Te...

引用

Advancement in Electronics & Communication Engineering (AECE), international conference on

作者： Nikhil Kumar Yadav Amit Tiwari Gaurav Harsh Kumar Verma Arpna Saxena Ajay Kumar Garg Engineering College Varanasi India Ajay Kumar Garg Engineering College Muzaffarpur India Ajay Kumar Garg Engineering College Meerut India Ajay Kumar Garg Engineering College Ghaziabad India Master of Computer Application Ajay Kumar Garg Engineering College Ghaziabad India

ISBN: (数字)9798350364729

ISBN: (纸本)9798350364736

this research highlights the critical role of the skin as the body's primary defense against damage and infection. Despite its importance, the skin can be vulnerable to serious infections caused by fungi, viruses, or even dust, leading to conditions ranging from acne to eczema. Some skin diseases are highly contagious and can be spread by simple contact, underscoring the need for proper diagnosis and treatment to alleviate suffering and prevent transmission. the study focuses on developing a prototype for identifying skin diseases using convolutional neural networks (CNNs), a choice based on their effectiveness in image processing tasks. this research uses CNNs to classify specific skin conditions, including hand dermatitis, hand eczema, subacute eczema, lichen simplex, stasis dermatitis, and ulcers are all different skin conditions.. the methodology integrates image processing techniques with machine learning and uses the processed images to train a CNN model. the training data consists of five classes of skin conditions from the Dermnet dataset, which includes 19600 images. the prototype achieved an accuracy of 92%, highlighting the system's potential. Research suggests that with further improvements and a larger data set, the system could significantly improve early detection and treatment of skin ailments representing a substantial advance in dermatology care.

关键词： Deep learning Adaptation models Accuracy Computational modeling Dermatology Eczema Transformers Skin Convolutional neural networks Diseases

来源：评论

学校读者我要写书评

暂无评论

Research on the application of Business Data Fusion in the Engineering Management of Oil and Gas Storage and Transportation Station 23

Research on the Application of Business Data Fusion in the E...

引用

proceedings of the 2023 4th international conference on computer Science and Management Technology

作者： Rui Xie Bo Fan Jianlin Ma Meng Pan Southwest Pipeline Ltd. China School of Computing and Artificial Intelligence Southwest Jiaotong University China Chengdu Aerospace Science & Industry Big Data Institute Ltd. China

ISBN: (纸本)9798400709517

Due to challenges such as complex contractor personnel, a large amount of scattered form data, a cumbersome business implementation process, low levels of digitalization and security, and difficult management in the engineering management business of oil and gas storage and transportation stations, this paper proposes a study on business data fusion application in the engineering management of oil and gas storage and transportation stations. Focused on the business processes and data of engineering management in oil and gas storage and transportation stations, this research establishes and analyzes an architecture for engineering management business in these stations. Using an Artifact-centric data fusion method, the research constructs an information model for the engineering management business, identifying the data topics for this area. Finally, the research applies and verifies the study of business data fusion through real-world business management scenarios. As researchers in the field of business data fusion, this study utilizes digital technologies and methods to enhance the overall safety management of engineering operations, thereby promoting the transformation and upgrading of engineering management business in oil and gas storage and transportation stations

关键词：

来源：评论

学校读者我要写书评

暂无评论

Understanding Tourists Relationship Quality Using a machine learning ApproachUnderstanding Tourists Relationship Quality 23

Understanding Tourists Relationship Quality Using a Machine ...

引用

proceedings of the 2023 4th international conference on Big Data Economy and Information Management

作者： Dawei Shang Yufang Chi Zhengzhou University China Beijing Vocational College of Social Management (Ministry of Civil Affairs Training Centre) China

ISBN: (纸本)9798400716669

From the perspective of segmented industry sectors, the significance of big data economy and information management in the tourism industry cannot be underestimated. However, research on non-linear analysis of the relationship between tourists relationship quality and its influencing factors is still limited. this study examines the impact of tourist perceived value on relationship quality using neural network methods in the field of information management. Exploring the non-linear relationship used cross validation and independent variable importance analysis. the Root Mean Square Error (RMSE) test results show that the model evaluation in this study is effective and acceptable. the results show that perceived value plays the important nonlinear role in the relationship quality. the analysis of the importance of independent variables shows that results shows that perceived functional value, perceived cost effectiveness value, and perceived emotional value have the greatest nonlinear impact on relationship quality. Meanwhile, the non-linear impact of perceived social value and perceived environmental value on relationship quality is relatively small. this study contributes to improving the quality of tourist destinations, various tourism management themes, and tourist relationships, flourishing the tourism market, and promoting the sustainable development of the tourism industry in information management intelligence era.

关键词：

来源：评论

学校读者我要写书评

暂无评论

EfficientNet-B0-Based Classification of Pneumonic Lungs Using Chest X-Ray Dataset

EfficientNet-B0-Based Classification of Pneumonic Lungs Usin...

引用

Intelligent Technologies (CONIT), international conference on

作者： Retinderdeep Singh Neha Sharma Kapil Rajput Mukesh Kumar Chitkara University Institute of Engineering and technology Chitkara University Punjab India Computer Science & Engineering Graphic Era Hill University Dehradun Uttarakhand India

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

In this research paper, the authors take a new angle: classify pneumonic lungs by utilizing up-to-date architecture such as EfficientNet-BO. Given a huge X-Ray dataset of real cases, the model is excellent at identifying pneumonia. the study aims to address a crucial need in the area of respiratory medicine-through development and application for clinical diagnosis of diseases of the lungs which are efficient, accurate and can be used on everyone. Its strong ability to learn is shown as the model demonstrates an awesome 99.50% training accuracy, checks itself out by verifying results with a validation accuracy of 92.20%, and sits tight under pressure during testing with an accuracy at 99.28%. As a matter of fact, these results serve to remind us that this model is excellent in accurately identifying normal and pneumonic lung conditions. this research not only enriches the growing literature on deep learning techniques in medical image analysis but also offers an extremely valuable tool for health care providers which can rapidly and precisely diagnose pneumonia. the method uses the EfficientNet-B0 architecture, known for its high performance in image classification. the model is built from a rich and diverse Chest X-Ray dataset, ensuring that it can be generalized to different patient populations and conditions of imaging. the study’s findings hold promise for improving diagnostic accuracy, lowering human error as well as ultimately transforming patient outcomes in the realm of pneumonia detection by means automated image classification.

关键词： Training Accuracy Pneumonia Lung Data models Ensemble learning X-ray imaging

来源：评论

学校读者我要写书评

暂无评论

Research progress of visual analysis of artificial intelligence application in depression field based on CiteSpace 23

Research progress of visual analysis of artificial intellige...

引用

proceedings of the 2023 4th international Symposium on Artificial Intelligence for Medicine Science

作者： Xin Zhang Zhencai Chen Key Research Laboratory of Chinese Medicine Psychology and Brain Science Jiangxi University of Chinese Medicine China

ISBN: (纸本)9798400708138

Depression is one of the most prevalent mental disorders with significant disability and mortality rates, which severely impairs the health and social function of individuals. To explore more efficient and objective diagnosis and treatment methods, the application of artificial intelligence technology in depression has gained increasing attention in recent years, providing a new tool for clinical practice and achieving preliminary successes. the goal of this study was to explore the research hotspots and frontiers of AI in the field of depression, providing reference for future research. Methods: We used literature related to AI in the field of depression retrieved from Web of Science as the data source. In combination with manual screening and information integration methods, CiteSpace software was used to make a statistical analysis of literature distribution, authors, institutions, keywords. Results: A total of 500 English articles were included, and the number of English articles increased significantly from 2019 to 2022. the authors were mainly new research groups in recent years. the pattern of institutional collaboration was relatively simple, and there were few highly cited articles. the research methods mainly involved data mining, machine learning, deep learning, and neural networks, while the application areas mainly focusing on the use of AI technology for predicting depression onset, early recognition, auxiliary diagnosis, and treatment planning. Conclusion: the research hotspots of AI in the field of depression are centered on improving depression intelligent methods, intelligent diagnosis, and intelligent prediction. the focus is more inclined towards intelligent prediction and diagnosis research. Research teams and institutions should strengthen cooperation among experts in different research fields to achieve multi-disciplinary integration.

关键词： CiteSpace software Depression Visual analysis artificial intelligence

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418页 << < 409 410 411 412 413 414 415 416 417 418 > >>

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：