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

4,137 篇 会议
38 册 图书
6 篇 期刊文献

馆藏范围

4,181 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,738 篇 工学
- 2,465 篇 计算机科学与技术...
- 2,042 篇 软件工程
- 616 篇 生物工程
- 587 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
- 216 篇 电气工程
- 211 篇 光学工程
- 148 篇 安全科学与工程
- 136 篇 机械工程
- 124 篇 电子科学与技术（可...
- 118 篇 化学工程与技术
- 107 篇 交通运输工程
- 91 篇 动力工程及工程热...
1,369 篇 理学
- 675 篇 数学
- 646 篇 生物学
- 332 篇 统计学（可授理学、...
- 307 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
157 篇 教育学
- 155 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

526 篇 machine learning
243 篇 deep learning
117 篇 support vector m...
99 篇 adversarial mach...
92 篇 accuracy
92 篇 machine learning...
83 篇 forecasting
75 篇 convolutional ne...
70 篇 predictive model...
69 篇 feature extracti...
58 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 neural networks

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

3,930 篇 英文
250 篇 其他
34 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 4181 条记录，以下是3501-3510 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：

Analysis Of Accounting Information Systems Based On Artificial Intelligence On Fraudulent Financial Reporting Trends In Indonesia 22

Analysis Of Accounting Information Systems Based On Artifici...

引用

proceedings of the 2022 4th international conference on E-Business and E-Commerce Engineering

作者： Meiryani Meiryani Vidhiya Andini Mochammad Fahlevi Winwin Yadiati Agung Purnomo Gredion Prajena Department School of Accounting Bina Nusantara University Indonesia Management Department BINUS Online Learning Bina Nusantara University Indonesia Accounting Department Faculty of Economics and Business Padjadjaran University Indonesia Entrepreneurship Department BINUS Business School Bina Nusantara University Indonesia Computer Science Department School of Computer Science Bina Nusantara University Indonesia

ISBN: (纸本)9798400700071

the accounting information system in a company functions to collect information from various entity subsystems and communicate it to the organization's information processing subsystem. Along with the development of technology and information resulting in significant changes resulting in the need for collaboration from technological developments such as artificial intelligence. By looking at the number of frauds in financial reporting, it requires organizations or companies to make changes for the good of the company related to technological advances that make Artificial Intelligence-based Accounting Information Systems become one of the important needs. this study aims to determine whether there is an effect given by the application of an Artificial Intelligence (AI)-based Accounting Information System (AIS) in detecting and preventing the tendency of fraudulent financial reporting. And to examine how big the role of the Accounting Information System (SIA) based on Artificial Intelligence (AI) in detecting and preventing the tendency of fraudulent financial reporting. this research method is a quantitative research that has a research sample of 31 respondents. the data used is primary data in the form of respondents' answers and processed using SPSS version 27. With the conclusion that the application of an artificial intelligence-based accounting information system has a positive effect on the tendency of fraudulent financial reporting based on the output of the Scatter Plot Graph. based on the coefficient of determination of 0.717 and the regression coefficient of 0.762. In conclusion, the application of accounting information systems has a significant positive effect on the prevention of fraudulent financial reporting with the effect given is 71.7%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ice Detection on Edge Device Based on Most Significant Digit First SVM 22

Ice Detection on Edge Device Based on Most Significant Digit...

引用

proceedings of the 2022 6th international conference on Video and Image Processing

作者： Najafi Mohammadreza Saeid Gorgin Danial Javaheri Jeong-A Lee computer engineering Chosun University south korea computer engineering Chosun University south korea and Department of Electrical Engineering and Information Technology IROSt Iran

ISBN: (纸本)9781450397568

Abstract- the present notion of smart cities inspires urban planners and academics to provide citizens with modern, secure, and sustainable infrastructure and a decent standard of living. To meet this demand, video surveillance cameras have been installed to improve the safety and well-being of the populace. Despite technological advances in modern science, detecting anomalous events in surveillance video systems is difficult and takes extensive human effort. Due to the context-dependent nature of the anomalous concept, we identify several objects of interest and freely accessible datasets for anomaly detection. Iced surface in highways is one of the serious anomaly which causes a large number of accidents on the highway every year. CCTVs installed on highways can be a good tool to detect iced surface. Detection is a time-sensitive application of computer vision; hence, this paper has concentrated on investigating iced surface detection using edge devices and methods. We have leveraged Most-Significant Digit First arithmetic to improve the performance and resource utilization of the Support Vector machine. We have applied our proposed method to address the problem of ice detection on highways, where the experimental results indicated a significant improvement in terms of accuracy, speedup, and energy consumption. these metrics are essential for edge computing and real-time intelligent surveillance applications.

关键词： computer arithmetic FPGA computer vision machine learning

来源：评论

学校读者我要写书评

暂无评论

Boosting-Based Construction of BDDs for Linear threshold Functions and Its application to Verification of Neural Networks 26th

Boosting-Based Construction of BDDs for Linear Threshold Fun...

引用

26th international conference on Discovery Science, DS 2023

作者： Tang, Yiping Hatano, Kohei Takimoto, Eiji Kyushu University Fukuoka Japan RIKEN AIP Tokyo Japan

ISBN: (纸本)9783031452741

Understanding the characteristics of neural networks is important but difficult due to their complex structures and behaviors. Some previous work proposes to transform neural networks into equivalent Boolean expressions and apply verification techniques for characteristics of interest. this approach is promising since rich results of verification techniques for circuits and other Boolean expressions can be readily applied. the bottleneck is the time complexity of the transformation. More precisely, (i) each neuron of the network, i.e., a linear threshold function, is converted to a Binary Decision Diagram (BDD), and (ii) they are further combined into some final form, such as Boolean circuits. For a linear threshold function with n variables, an existing method takes O(n2n2) time to construct an ordered BDD of size O(2n2) consistent with some variable ordering. However, it is non-trivial to choose a variable ordering producing a small BDD among n! candidates. We propose a method to convert a linear threshold function to a specific form of a BDD based on the boosting approach in the machine learning literature. Our method takes O(2npoly (1 / ρ) ) time and outputs BDD of size O(n2ρ4ln1ρ), where ρ is the margin of some consistent linear threshold function. Our method does not need to search for good variable orderings and produces a smaller expression when the margin of the linear threshold function is large. More precisely, our method is based on our new boosting algorithm, which is of independent interest. We also propose a method to combine them into the final Boolean expression representing the neural network. In our experiments on verification tasks of neural networks, our methods produce smaller final Boolean expressions, on which the verification tasks are done more efficiently. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Complex networks

来源：评论

学校读者我要写书评

暂无评论

Fault Diagnosis Technology of Industrial Circuit Breaker Optimized by Genetic Algorithm in LVQ Network

Fault Diagnosis Technology of Industrial Circuit Breaker Opt...

引用

Frontiers Technology of Information and computer (ICFTIC), IEEE international conference on

作者： Weichong Li Guangde Peng Xian Jun Huang Chu Liu Tang Yi Huang Guangzhou Li-Gong Industrial co. Ltd. Guangzhou China

the current signal of industrial circuit breaker switching-off coil contains rich state information of circuit breaker operating mechanism, which is of great significance to fault diagnosis of operating mechanism. Firstly, the ensemble empirical mode decomposition (EMD) is used to detect the abrupt change point, and the effective current signal segment of the closing coil is determined, and the noise reduction process is carried out adaptively. Secondly, the time domain extremum method is used to process the effective signal segment, and the composite characteristic quantities of current and time are extracted. Finally, the composite feature data is preprocessed by tensor product, so that it can be input into the LVQ network optimized by genetic algorithm for supervised fault state identification and diagnosis. the experimental results show that the current and time composite feature extraction method proposed in this paper is effective, and the genetic algorithm optimized LVQ network algorithm has higher diagnostic accuracy than GA-BP and support vector machine algorithm, which has higher practical application value.

关键词： Fault diagnosis Training Measurement Circuit breakers Transfer learning High-voltage techniques Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Deep learning Approach to Indian Sign Language Recognition 4th

Deep Learning Approach to Indian Sign Language Recognition

引用

4th international Research conference on machine learning, Deep learning, and Blockchain, IRCICD 2023

作者： Vilashni, N. Anju Uthika, B. Sanjana, A. Yegu Prabha, B. Department of Computer Science and Engineering SRM Institute of Science and Technology Vadapalani Chennai India

ISBN: (纸本)9783031882364

Communication is one of civilization’s fundamental demands. About 20% of the global population has disabling hearing loss. the deaf and hard-of-hearing people mostly use sign language. It may also be used by individuals who can listen but cannot speak and by those who have deaf family members. Our proposed method aims to convert real-time data of Indian Sign Language (ISL) into text and audio data. the equivalent American Sign Language (ASL) field has seen many studies. However, some obstacles hinder further analysis of ISL. the main obstacle preventing further ISL research has been the lack of standard datasets, hidden characteristics, and local language variance. the majority of the work is based on handcrafted facets. Indian Sign Language (ISL) has static and dynamic signs and various gestures for the same expression depending on the area of India. It makes constructing a standardized dataset very challenging. Furthermore, there is no standard collection accessible. Hence, we were forced to make our dataset which consists of alphabets (A-Z) and numbers (0–9). the proposed method uses a custom-made Convolution Neural Network (CNN) model to classify 36 signs. Once the CNN model recognizes the sign, the output label is printed as text. this proposed model achieves a validation accuracy of 99.4%. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Classification and Localization of COVID-19 based on a Pneumonia Radiograph using a Deep learning Approach 22

Classification and Localization of COVID-19 based on a Pneum...

引用

proceedings of the 4th international conference on Information Management & machine Intelligence

作者： M. Anto Bennet S. S. Saranya Dinesh Goyal Pankaj Dadheech S. Balu Sudhakar Sengan Electronics & Communication Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology India and Electronics & Communication Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology India School of Computing SRM Institute of Science and Technology Kattankulathur Campus India and School of Computing SRM Institute of Science and Technology Kattankulathur Campus India Computer Science & Engineering Poornima Institute of Engineering and Technology India and Computer Science & Engineering Poornima Institute of Engineering and Technology India Computer Science & Engineering Swami Keshvanand Institute of Technology Management & Gramothan (SKIT) India and Computer Science & Engineering Swami Keshvanand Institute of Technology Management & Gramothan (SKIT) India Computer Science & Engineering Paavai Engineering College India and Computer Science & Engineering Paavai Engineering College India Computer Science & Engineering PSN College of Engineering and Technology India and Computer Science & Engineering PSN College of Engineering and Technology India

ISBN: (纸本)9781450399937

the world is battling the pandemic corona virus disease (COVID-19) now, and even after 2 years of the COVID-19 pandemic, this technology is still not reasonably advanced to tackle the battle against this virus most efficiently. the total number of COVID-19 cases worldwide surpassed 420 million, with 5.8 million deaths. COVID-19 infects a person with various symptoms, and one of the symptoms is pneumonia. A person suffering from pneumonia may or may not be carrying COVID-19. this research article aims to describe an X-radiation (X-ray) of patients with pneumonia and proposes other subjects who also have the corona virus. this system is based on Deep learning (DL), and the Convolutional Neural Networks (CNN) method is applied. the work is done with additional help from the frameworks Tensorflow and Keras. Firstly, the images are loaded into the compiler, cleaned, and preprocessed accordingly. the next thing to come up with is setting up the Neural Network (NN) layer. the CNN layer is formed, and a particular Activation Function (AF), Rectified Linear Unit (ReLu), is applied. Finally, the model is trained, and a classification is done to determine whether the patient's X-ray is only for pneumonia or pneumonia + COVID-19. the paper's outcome has an accuracy of 96% to 98%.

关键词： X-Rays, Pneumonia, Accuracy, ReLu COVID-19, CNN, Deep learning

来源：评论

学校读者我要写书评

暂无评论

Deep-learning algorithm for rib fracture detection in low-dose chest CT images 22

Deep-learning algorithm for rib fracture detection in low-do...

引用

proceedings of the 2022 9th international conference on Biomedical and Bioinformatics Engineering

作者： Hui Yu Yongzheng Ding Jinglai Sun Xuyao Yu Fengling Zhu Huanming Li Xiaoyun Liang Dagong Jia Key Laboratory of Biomedical Detecting Techniques and Instruments Tianjin University China Tianjin Medical University Cancer Institute & Hospital China Tianjin Hospital China Tianjin Joint Laboratory of intelligent medicine Tianjin 4TH Centre Hospital China School of Precision Instruments and Optoelectronics Engineering Tianjin University China

ISBN: (纸本)9781450397223

the detection of rib fractures is of great significance for the diagnosis and treatment of patients with blunt chest trauma. the while application of low-dose CT has become a trend. But there are few studies focusing on automatic fracture detection under low-dose CT. In this paper, a deep-learning model was proposed based on Mask R-CNN and its performance was evaluated by public dataset RibFrac containing 480 chest CT images with 3D rib fracture annotations. In addition, another dataset including 100 cases were collected from Tianjin Hospital for extensibility *** curve was used to compare the effects of different doses of CT images while the precision, recall, F1 score, IoU index and Dice coefficient were calculated. On the rib detection task,the detection rates achieved 93.5%, 90.8%, and 90.5% at normal dose, 10% mAs, and 5% mAs, respectively. On the external dataset,the recall rates of detection achieved of 95.7%, 93.9% and 92.7%.Our proposed network can effectively realize the task of detecting rib fractures in low-dose CT, and provide help for the application of deep learning for rib fracture detection in low-dose CT .

关键词： Object detection Low-dose CT Rib fracture Deep learning

来源：评论

学校读者我要写书评

暂无评论

Optimizing Energy Management and Load Balancing through AI-Driven Quantum Approximate Optimization

Optimizing Energy Management and Load Balancing Through AI-D...

引用

Mobile Networks and Wireless Communications (ICMNWC), IEEE international conference on

作者： Manjunath Kamath K Manasa M Anitha B. S Mahadevi Falguni Tlajiya Sangramjit Chavan Department of Cyber Security NMAM Institute of Technology NITTE (Deemed to be University) Karkala India Department of Artificial Intelligence and Machine Learning Brindavan College of Engineering Bengaluru India Department of Computer Science Sarada Vilas College Mysuru India Department of Electrical Engineering Parul institute of Engineering and Technology Parul University Gujarat India Symbiosis Law School (SLS) Symbiosis International (Deemed University) (SIU) Pune India

ISBN: (数字)9798331528348

ISBN: (纸本)9798331528355

the integration of Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) offers a promising approach to addressing energy management and load balancing challenges in modern power systems. this study explores the application of these quantum computing techniques, coupled with Artificial Intelligence (AI), to optimize energy distribution across smart grids. the proposed hybrid model leverages the problem-solving capabilities of QAOA for discrete optimization and the real-time adaptability of QA for minimizing energy consumption and operational costs. AI techniques are employed to predict energy demand, balance loads, and ensure efficient resource allocation. Simulations were conducted on a smart grid scenario involving renewable energy sources, varying demand, and distributed energy generation. the results demonstrate that the hybrid model achieved a 25% improvement in load balancing efficiency and a 30% reduction in energy wastage compared to traditional optimization methods. Additionally, the model reduced peak energy demand by 20%, contributing to overall grid stability. the quantum-enhanced approach also decreased computational complexity by 40%, enabling faster decision-making in dynamic environments. these findings highlight the potential of combining quantum algorithms with AI for sustainable and efficient energy management.

关键词： Data centers Renewable energy sources Quantum algorithm Computational modeling Power system stability Load management Quantum annealing Artificial intelligence Optimization Load modeling

来源：评论

学校读者我要写书评

暂无评论

Adaptive traffic signal control based on Dueling Deep Q-learning Network 22

Adaptive traffic signal control based on Dueling Deep Q-Lear...

引用

proceedings of the 2022 4th international conference on Robotics, Intelligent Control and Artificial Intelligence

作者： Zhuohang Xu Ping Wang Libin Zhang Fan Qi Guiping Wang School of Electronic and Control Engineering Chang45an University China

ISBN: (纸本)9781450398343

the intersection is the place where traffic flow converges and traffic accidents are most likely to occur, and the traffic conditions at intersections is also complex, which is easy to cause congestion and reduce the traffic efficiency. With the development of intelligent transportation system, adaptive traffic signal control is proposed to improve the traffic efficiency of the intersection by adjusting the phase sequence of the signal in real time. Meanwhile, with the extensive application of reinforcement learning in the traffic field, dueling DQN (Deep Q-learning Network) is introduced to realize the adaptive traffic signal control in this paper. By comparing the traffic flow conditions of intersections under different signal control methods, we find that dueling DQN can effectively improve the traffic efficiency of intersections under the condition of random change of traffic flow. through experiment results, we can conclude that the expected reward of dueling DQN is 41.1% and 4.8% higher than that of fixed phase method and DQN method. Meanwhile, simulation result shows that dueling DQN can react to the traffic flow of the road network more timely, and has higher stability than DQN, which can effectively improve the traffic efficiency.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Constructive Interpretability with CoLabel: Corroborative Integration, Complementary Features, and Collaborative learning

Constructive Interpretability with CoLabel: Corroborative In...

引用

IEEE international conference on Cognitive machine Intelligence (CogMI)

作者： Abhijit Suprem Sanjyot Vaidya Suma Cherkadi Purva Singh Joao Eduardo Ferreira Calton Pu School of Computer Science Georgia Institute of Technology Atlanta USA Institute of Mathematics and Statistics University of Sao Paulo Sao Paulo Brazil

machine learning models with explainable predictions are increasingly sought after, especially for real-world, mission-critical applications that require bias detection and risk mitigation. Inherent interpretability, where a model is designed from the ground-up for interpretability, provides intuitive insights and transparent explanations on model prediction and performance. In this paper, we present CoLabel, an approach to build interpretable models with explanations rooted in the ground truth. We demonstrate CoLabel in a vehicle feature extraction application in the context of vehicle make-model recognition (VMMR). By construction, CoLabel performs VMMR with a composite of interpretable features such as vehicle color, type, and make, all based on interpretable annotations of the ground truth labels. First, CoLabel performs corroborative integration to join multiple datasets that each have a subset of desired annotations of color, type, and make. then, CoLabel uses decomposable branches to extract complementary features corresponding to desired annotations. Finally, CoLabel fuses them together for final predictions. During feature fusion, CoLabel harmonizes complementary branches so that VMMR features are compatible with each other and can be projected to the same semantic space for classification. With inherent interpretability, CoLabel achieves superior performance to the state-of-the-art black-box models, with accuracy of 0.98, 0.95, and 0.94 on CompCars, Cars196, and BoxCars116K, respectively. CoLabel provides intuitive explanations due to constructive interpretability, and subsequently achieves high accuracy and usability in mission-critical situations.

关键词： Annotations Fuses Mission critical systems Semantics Color Predictive models Feature extraction

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419页 << < 347 348 349 350 351 352 353 354 355 356 > >>

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：