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

1,721 篇 会议
45 册 图书
12 篇 期刊文献

馆藏范围

1,777 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

1,224 篇 工学
- 1,093 篇 计算机科学与技术...
- 629 篇 软件工程
- 253 篇 信息与通信工程
- 200 篇 电气工程
- 177 篇 生物工程
- 99 篇 控制科学与工程
- 98 篇 生物医学工程（可授...
- 60 篇 光学工程
- 46 篇 化学工程与技术
- 45 篇 电子科学与技术（可...
- 41 篇 机械工程
- 41 篇 仪器科学与技术
- 40 篇 安全科学与工程
- 30 篇 交通运输工程
- 28 篇 动力工程及工程热...
- 27 篇 材料科学与工程（可...
456 篇 理学
- 199 篇 数学
- 197 篇 生物学
- 144 篇 物理学
- 83 篇 统计学（可授理学、...
- 51 篇 系统科学
- 46 篇 化学
233 篇 管理学
- 167 篇 图书情报与档案管...
- 86 篇 管理科学与工程(可...
- 43 篇 工商管理
182 篇 医学
- 160 篇 临床医学
- 72 篇 基础医学(可授医学...
- 39 篇 药学(可授医学、理...
- 32 篇 公共卫生与预防医...
34 篇 法学
- 30 篇 社会学
17 篇 经济学
14 篇 教育学
11 篇 农学
2 篇 艺术学
1 篇 军事学

主题

237 篇 machine learning
182 篇 deep learning
137 篇 pattern recognit...
107 篇 feature extracti...
89 篇 support vector m...
88 篇 data mining
74 篇 accuracy
72 篇 training
57 篇 convolutional ne...
50 篇 machine learning...
46 篇 artificial intel...
45 篇 data models
40 篇 neural networks
39 篇 face recognition
38 篇 computational mo...
36 篇 learning systems
36 篇 adversarial mach...
33 篇 predictive model...
32 篇 classification
32 篇 image recognitio...

机构

6 篇 college of compu...
5 篇 xi'an university...
4 篇 badji mokhtar un...
4 篇 shanghai jiao to...
4 篇 institute of big...
4 篇 chitkara centre ...
4 篇 chitkara univers...
4 篇 library shanghai...
3 篇 school of comput...
3 篇 univ chittagong ...
3 篇 chongqing univer...
3 篇 centre of resear...
3 篇 school of comput...
3 篇 school of comput...
3 篇 school of design...
3 篇 korea univ dept ...
3 篇 school of automa...
3 篇 university of mi...
3 篇 shenyang jianzhu...
3 篇 xi'an university...

作者

5 篇 venkatesh svetha
4 篇 ashwini kodipall...
4 篇 zhang yan
4 篇 srinivasa gowri
4 篇 kamel mohamed s.
4 篇 lall brejesh
4 篇 trupthi rao
3 篇 andersson karl
3 篇 peng yang
3 篇 malerba donato
3 篇 karl andersson
3 篇 chaudhury santan...
3 篇 de-shuang huang
3 篇 sekhar c. chandr...
3 篇 wang shuo
3 篇 kamata sei-ichir...
3 篇 mohammad shahada...
3 篇 azizi nabiha
3 篇 phung dinh
3 篇 krasotkina olga

语言

1,695 篇 英文
74 篇 其他
22 篇 中文

检索条件"任意字段=4th International Conference on Machine Learning and Data Minining in Pattern Recognition"

共 1778 条记录，以下是121-130 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：

Review on the Development of Few-Shot Specific Emitter Identification Technology 4

Review on the Development of Few-Shot Specific Emitter Ident...

引用

4th international conference on Electronic Information Engineering and Computer Science, EIECS 2024

作者： Lv, Dian Yu, Zhiyong Xie, Jiawei Zhang, Hao Rocket Force University of Engineering Xi'an China

ISBN: (纸本)9798331531409

In the face of a complex and ever-changing electromagnetic environment, the rapid increase in the number and types of radiation sources has made traditional Specific Emitter Identification techniques, which rely on conventional machine learning and statistical features, difficult to apply. In recent years, deep learning models have demonstrated exceptional performance in areas such as image recognition, prompting many researchers to incorporate deep learning into radiation source identification tasks. However, deep learning requires vast amounts of high-quality data, and in practical electromagnetic environments, it is challenging to collect and annotate radiation source signals. As a result, few-shot specific emitter identificatio has become a new focal point of research. this paper first introduces the radiation source identification system and reviews the research on traditional radiation source identification techniques. Next, it provides a detailed overview of few-shot specific emitter identification techniques categorized based on the radiation source identification technology framework, including data augmentation, metric learning, and model-based methods. Finally, the paper analyzes the current challenges in Few-Shot Specific Emitter Identification technology and offers prospects for future research. © 2024 IEEE.

关键词： Zero-shot learning

来源：评论

学校读者我要写书评

暂无评论

Generation of Synthetic Image Anomalies for Analysis 4th

Generation of Synthetic Image Anomalies for Analysis

引用

4th international conference on Intelligent Systems and pattern recognition-ISPR

作者： Breuss, David Rusy, Karel Goetzinger, Maximilian Jantsch, Axel Vienna Univ Technol ICT Gusshausstr 27 A-1040 Vienna Austria Christian Doppler Lab Embedded Machine Learning Vienna Austria Schneider Elect Power Drives GmbH Ruthnergasse 1 A-1210 Vienna Austria

ISBN: (纸本)9783031821493;9783031821509

Many powerful anomaly detection algorithms are based on machine learning and rely on datasets for training and evaluation. However, anomalous samples are often rare in real-world datasets and might not be representative of anomalies encountered in the field. In this paper, we propose a synthetic anomaly generation methodology that focuses on generating large numbers of synthetic anomalies in images with defined variances in size, shape, and texture, achieving higher diversity scores than the state-of-the-art. To demonstrate the value of the proposed generation methodology for in-depth performance analysis, we generate anomalies in three MVTec AD datasets, which we then use to analyze and evaluate several anomaly detection algorithms. While all analyzed anomaly detection algorithms showed strong recall rates on these datasets, significant sensitivity differences regarding an anomaly's size, shape, and texture are observable through the analysis with our synthetic datasets. While we observed some algorithms' robustness towards different anomaly shapes and textures, others showed differences in recall rates of up to 80% points for some pixel manipulation methods. the results demonstrate the value of our synthetic anomalies, as they boost the capability to scrutinize anomaly detection algorithms.

关键词： Synthetic data Anomalies Image Generation Analysis

来源：评论

学校读者我要写书评

暂无评论

machine learning Applied to Speech Recordings for Parkinson's Disease recognition 1

引用

4th international conference on Deep learning theory and Applications (DeLTA)

作者： Aversano, Lerina Bernardi, Mario L. Cimitile, Marta Iammarino, Martina Madau, Antonella Verdone, Chiara Univ Sannio Dept Engn Benevento Italy Unitelma Sapienza Univ Rome Italy

ISBN: (数字)9783031390593

ISBN: (纸本)9783031390586;9783031390593

Parkinson's disease is a common neurological condition that occurs when dopamine production in the brain decreases significantly due to the degeneration of neurons in an area called the substantia nigra. One of its characteristics is the slow and gradual onset of symptoms, which are varied and include tremors at rest, rigidity, and slow speech. Voice changes are very common among patients, so analysis of voice recordings could be a valuable tool for early diagnosis of the disease. this study proposes an approach that compares different machine learning models for the diagnosis of the disease through the use of vocal recordings of the vowel a made by both healthy and sick patients and the identification of the subset of the most significant features the experiments were conducted on a data set available on the UCI repository, which collects 756 different recordings. the results obtained are very encouraging, reaching an F-score of 95%, which demonstrates the effectiveness of the proposed approach.

关键词： Parkinsons's disease Speech recordings machine learning Early diagnosis

来源：评论

学校读者我要写书评

暂无评论

Scripting the Skies : Beyond the Horizon with machine learning in Drone Shaped Bird recognition 4

Scripting the Skies : Beyond the Horizon with Machine Learni...

引用

4th international conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： thamizhkani, B. Shalini, S. Jeyanthi, S. Aishwarya, R. Kumar, S. Senthil Anitha, R. New Prince Shri Bhavani College of Engineering and Technology Department of Eee Chennai India New Prince Shri Bhavani College of Engineering and Technology Department of Computer Applications Chennai India New Prince Shri Bhavani College of Engineering and Technology Department of It Chennai India

ISBN: (纸本)9798331508845

Support Vector machine (SVM) is a machine learning approaches has been used for bird species identification. Feature extraction from bird photos is used to train the SVM classifier. these features include morphological traits, color histograms, and texture descriptors. the experimental findings show that the SVM model works well for identifying bird species from photos. To begin, SVM's classification performance is very sensitive to the hyperparameters - the kind of kernel and regularization parameter - selected with great care. Also, support vector machines (SVMs) often have trouble handling noisy data or feature spaces with a lot of dimensions since they are so sensitive to the features that are *** contrasted with probabilistic classification model like logistic regression or Gaussian Naive Bayes, SVM's lack of intrinsic probabilistic outputs makes it less interpretable. Finally, SVM could have scalability problems with big datasets since training duration and storage needs go up with features and samples. Notwithstanding these caveats, support vector machines (SVMs) continue to be a hot commodity when it comes to machine learning classification algorithms, and bird species detection is no exception. To overcome SVM's limitations in bird recognition applications, future studies can investigate hybrid techniques or other algorithms. © 2024 IEEE.

关键词： Birds

来源：评论

学校读者我要写书评

暂无评论

Research on Vibration Signal Diagnosis Platform System Based on Computer Fuzzy Logic 4

Research on Vibration Signal Diagnosis Platform System Based...

引用

4th IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Bo, Liu Yang, Song Zhenwang, Lv Zhaoran, Meng Dalian Scientific Test and Control Technology Institute Dalian China

ISBN: (纸本)9798350361643

An on-line vibration detection method for power transformers is introduced. this design includes sensor module, real-time processing module, PC module. the sensor module collects the vibration, voltage, load voltage and other signals of the motor and transmits them to the processing unit on site. the real-time processing module transmits the processed information to the PC for display, storage, analysis and other functions. A real-time monitoring system for power transformer vibration based on virtual instrument /Compact RIO is developed. A new signal detection algorithm is established by combining wavelet energy information entropy theory with SVM. A frequency domain analysis algorithm based on wavelet analysis is proposed. the normalized feature vector is the input signal of support vector machine. then a support vector machine (SVM) multi-classifier model based on multi-class learning is proposed. Experimental results show that the SVM classifier proposed in this paper has high classification accuracy under multiple working conditions of power transformer. © 2024 IEEE.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

A Novel Post-Hoc Explanation Comparison Metric and Applications 4th

A Novel Post-Hoc Explanation Comparison Metric and Applicat...

引用

4th international conference on pattern recognition and Artificial Intelligence, ICPRAI 2024

作者： Mitra, Shreyan Gilpin, Leilani Paul G. Allen School of Computer Science and Engineering University of Washington at Seattle Seattle United States Baskin School of Engineering University of California at Santa Cruz Santa Cruz United States

ISBN: (纸本)9789819787012

Explanatory systems ("explainers") make the behavior of blackbox machine learning models more transparent. However, the results of different explainers ("explanations") are often inconsistent with each other. To measure such differences, we propose a novel metric, the Shreyan Distance dS. this paper uses dS to compare two explanatory systems, SHAP and LIME, for both regression and classification learning tasks on tabular data. We find that the linearly weighted mean dS value varies significantly between these two tasks. this leads us to conclude that consistency between explainers depends not only on inherent properties of the explainers themselves, but also on the type of learning task. In the hopes that more accurately quantifying differences between existing explainers will lead to better explanations in the future, we demonstrate a way to integrate our novel metric into existing machine learning pipelines via the XAISuite library. © the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive learning

来源：评论

学校读者我要写书评

暂无评论

Deep learning for Diagnosis of Endometrial Cancer and Atypical Endometrial Hyperplasia 4

Deep Learning for Diagnosis of Endometrial Cancer and Atypic...

引用

4th IEEE international conference on pattern recognition and machine learning, PRML 2023

作者： Zhao, Aihua Zhu, Xin Du, Xin Wang, Wenwen Ma, Wenqing Wang, Shixuan The University of Aizu School of Computer Science and Engineering Fukushima Japan Huazhong University of Science and Technology Maternal and Child Hospital of Hubei Province Tongji Medical College Department of Gynecology Wuhan China Huazhong University of Science and Technology Tongji Hospital Tongji Medical College Department of Obstetrics and Gynecology Wuhan China

ISBN: (纸本)9798350324303

Endometrial cancer(EC) is the most common and rapidly increasing female cancer globally. Atypical endometrial hyperplasia (AEH) is a precancerous condition of EC. Although hysteroscopy serves as the primary modality for diagnosing lesions, it relies on the subjective judgment of hysteroscopists. therefore, this study proposed a computer-aided diagnostic system utilizing the EfficientNet network as a baseline, incorporating ParNet attention mechanism and class weighting to accurately classify EC/AEH from benign lesions. this study included 49,556 hysteroscopy images from 1,237 cases as a training set and 3,412 hysteroscopy images from 85 cases as a testing set. AUC, accuracy, sensitivity, specificity, PPV, Kappa, and F1-Score of the proposed method are 0.941, 89.4%, 93.7%, 87.1%, 73.3%, 0.755, and 0.8225, respectively. the proposed model may be used as a computer-aided tool for the diagnosis of EC/AEH. © 2023 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Application of Virtualization Digital Technology in Intelligent Platform Construction pattern Analysis System 4

Application of Virtualization Digital Technology in Intellig...

引用

4th international conference on machine learning and Big data Analytics for IoT Security and Privacy, SPIoT 2023

作者： Yuan, Hongyan Shandong Institute of Commerce and Technology Shandong Jinan250103 China

Intelligent platforms are mainly service platforms composed of machine learning integrations that rely on continuous reasoning and learning. this technology has been widely used in today's the Internet Age, and its analysis system, as an important customer oriented feedback link, is also very important. therefore, this article would optimize the intelligent platform analysis system by applying virtual digital technology, and use intelligent platforms for ship shipping and smart home platforms as examples. © 2024 the Authors.

关键词： Smart homes

来源：评论

学校读者我要写书评

暂无评论

Examining Policy Entropy of Reinforcement learning Agents for Personalization Tasks 4th

Examining Policy Entropy of Reinforcement Learning Agents f...

引用

4th international conference on pattern recognition and Artificial Intelligence, ICPRAI 2024

作者： Dereventsov, Anton Starnes, Andrew Webster, Clayton Lirio AI Research Lirio LLC KnoxvilleTN37830 United States

ISBN: (纸本)9789819787012

this paper examines the behavior of reinforcement learning systems in personalization environments and details the differences in policy entropy associated with the type of learning algorithm utilized. We observe that as agents evolve towards the optimal policy, the trajectory of the learned policy is intricately linked to the chosen learning paradigm. through a series of numerical experiments, we consistently observe differences in policy entropy values between Policy Optimization and Q-learning agents during the training process. Our empirical findings are complimented by a theoretical analysis that sheds light on this phenomenon, which has not yet been explored in existing literature. © the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

IProceedings of the 4th international conference on Artificial Intelligence and Computer Engineering, ICAICE 2023

IProceedings of the 4th International Conference on Artifici...

引用

4th international conference on Artificial Intelligence and Computer Engineering, ICAICE 2023

ISBN: (纸本)9798400708831

the proceedings contain 200 papers. the topics discussed include: heat-aware graph data placement strategy for NVM;parameters estimation of photovoltaic models via an improved differential evolution algorithm;study on the extraction of law enforcement relationships in administrative law enforcement instrument data;online algorithm for exploring a grid polygon with two robots;research on gesture recognition method by improving dung beetle algorithm to optimize BP neural network;an improved algorithm for frequent sequence pattern mining based on PrefixSpan-ComplexPrefixSpan;machine learning-based research on reserve prediction of natural-gas-hydrates;enhancing coal mine safety monitoring algorithm using graph computing techniques;reverse distillation support vector data description for unsupervised anomaly detection;and few-shot object counting model based on self-support matching and attention mechanism.

关键词：

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178页 << < 9 10 11 12 13 14 15 16 17 18 > >>

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：