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

2,116 篇 会议
47 篇 期刊文献
28 册 图书

馆藏范围

2,191 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,498 篇 工学
- 1,131 篇 计算机科学与技术...
- 654 篇 软件工程
- 274 篇 电气工程
- 251 篇 信息与通信工程
- 141 篇 生物医学工程（可授...
- 135 篇 控制科学与工程
- 133 篇 光学工程
- 104 篇 生物工程
- 93 篇 机械工程
- 66 篇 仪器科学与技术
- 61 篇 电子科学与技术（可...
- 59 篇 材料科学与工程（可...
- 55 篇 化学工程与技术
- 33 篇 建筑学
- 33 篇 土木工程
- 24 篇 力学（可授工学、理...
- 20 篇 安全科学与工程
663 篇 理学
- 348 篇 数学
- 206 篇 物理学
- 176 篇 生物学
- 95 篇 统计学（可授理学、...
- 59 篇 化学
- 33 篇 系统科学
206 篇 管理学
- 137 篇 图书情报与档案管...
- 79 篇 管理科学与工程(可...
- 25 篇 工商管理
140 篇 医学
- 132 篇 临床医学
- 49 篇 基础医学(可授医学...
- 31 篇 药学(可授医学、理...
21 篇 法学
- 21 篇 社会学
20 篇 艺术学
11 篇 教育学
9 篇 经济学
9 篇 农学
2 篇 文学
1 篇 军事学

主题

635 篇 pattern recognit...
92 篇 feature extracti...
60 篇 pattern matching
59 篇 local binary pat...
59 篇 neural networks
59 篇 face recognition
54 篇 data mining
41 篇 image segmentati...
40 篇 pattern recognit...
40 篇 machine learning
40 篇 character recogn...
37 篇 shape
36 篇 pattern analysis
35 篇 image processing
34 篇 support vector m...
34 篇 image recognitio...
33 篇 bioinformatics
33 篇 computer vision
32 篇 image analysis
31 篇 artificial intel...

机构

13 篇 national laborat...
6 篇 chinese acad sci...
5 篇 pattern recognit...
5 篇 chinese acad sci...
5 篇 univ windsor sch...
5 篇 university of to...
5 篇 chinese academy ...
4 篇 university colle...
4 篇 pattern recognit...
4 篇 institute of ima...
4 篇 the hebrew unive...
4 篇 the university o...
4 篇 sorbonne univers...
4 篇 eurecom biot
4 篇 national lab of ...
4 篇 key laboratory o...
4 篇 école centrale d...
4 篇 national institu...
4 篇 computer vision ...
3 篇 institute of ima...

作者

11 篇 ngom alioune
9 篇 ma songde
8 篇 li stan z.
8 篇 suen ching y.
6 篇 c.y. suen
6 篇 lei zhen
6 篇 suen c.y.
5 篇 lu hanqing
5 篇 wang wei
5 篇 duin robert p. w...
5 篇 anon
5 篇 liao shengcai
5 篇 kropatsch walter...
4 篇 leo joskowicz
4 篇 li yifeng
4 篇 liu cheng-lin
4 篇 hagras hani
4 篇 diana mateus
4 篇 song de ma
4 篇 maria a. zuluaga

语言

2,156 篇 英文
27 篇 其他
8 篇 中文

检索条件"任意字段=3rd IAPR International Conference on Pattern Recognition in Bioinformatics"

共 2191 条记录，以下是11-20 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：

Application Research of Computer Artificial Intelligence Technology in Image Search and recognition System 3

Application Research of Computer Artificial Intelligence Tec...

引用

3rd IEEE international conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Yu, Xin Li, Yuan Modern Finance Industry School Shandong Institute of Commerce and Technology Shandong Jinan China

ISBN: (纸本)9798350380989

In order to improve the data transfer rate and identification search efficiency of image recognition, a software driver interface design architecture based on FACADE is established in this paper. The PCI device is driven by MDL memory and the vector identification software is designed. Then, a background occlusion method based on microscopic search is proposed to find an efficient decision subset to replace the traditional decision set. This allows efficient retrieval of high-precision image matting. The comparison with the classical matting method proves that the proposed method can effectively overcome the occlusion problem when the foreground and background are highly similar. At the same time, it can effectively reduce the dimension of high-score image matting problem, so as to improve the accuracy of foreground occlusion extraction. © 2024 IEEE.

关键词： driver program FACADE design pattern Real-time image recognition system WDM model driven

来源：评论

学校读者我要写书评

暂无评论

Analysis of Generative Data Augmentation for Face Antispoofing 12th

Analysis of Generative Data Augmentation for Face Antispoofi...

引用

12th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Orfao, Jarred van der Haar, Dustin Univ Johannesburg Acad Comp Sci & Software Engn Kingsway AveKingsway Ave & Univ Rd Johannesburg South Africa

ISBN: (纸本)9783031547256;9783031547263

As technology advances, criminals continually find innovative ways to gain unauthorised access, increasing face spoofing challenges for face recognition systems. This demands the development of robust presentation attack detection methods. While traditional face antispoofing techniques relied on human-engineered features, they often lacked optimal representation capacity, creating a void that deep learning has begun to address in recent times. Nonetheless, these deep learning strategies still demand enhancement, particularly in uncontrolled environments. In this study, we employ generative models for data augmentation to boost the face antispoofing efficacy of a vision transformer. We also introduce an unsupervised keyframe selection process to yield superior candidate samples. Comprehensive benchmarks against recent models reveal that our augmentation methods significantly bolster the baseline performance on the CASIA-FASD dataset and deliver state-of-the-art results on the Spoof in the Wild database for protocols 2 and 3.

关键词： Face antispoofing Generative data augmentation Keyframe selection Analysis

来源：评论

学校读者我要写书评

暂无评论

Proceedings - 2024 3rd international conference on Computer Applications Technology, CCAT 2024

Proceedings - 2024 3rd International Conference on Computer ...

引用

3rd international conference on Computer Applications Technology, CCAT 2024

ISBN: (纸本)9798331539795

The proceedings contain 12 papers. The topics discussed include: research on lip recognition method based on 3D ResNet;player position binary classification model;towards in x-ray induced acoustic imaging for nasopharyngeal carcinoma radiotherapy with a multidimensional information fusion network;complex project production mode and man-machine interaction exploration;using ArcGIS to analyze spatiotemporal distribution pattern of intangible cultural heritages in Huaihai economic zone;research on predicting public opinion event heat levels based on large language models;enhancing cold chain logistics efficiency: improved ga for time-window-constrained routing;and industrial IoT big data platforms based on 5G and BeiDou technologies.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Adaptive pattern Prediction Framework for Solar PV Power Forecasting Using Cloud Image 3

An Adaptive Pattern Prediction Framework for Solar PV Power ...

引用

3rd international conference on Energy and Electrical Power Systems (ICEEPS)

作者： Zhang, Xinyang Wen, Ming Liu, Yuchong Yu, Zongchao Wen, Bo Li, Jiaxi State Grid Hunan Elect Power Co Ltd Econ & Tech Res Inst Hunan Key Lab Energy Internet Supply Demand & Ope Changsha Hunan Peoples R China

ISBN: (纸本)9798350375145;9798350375138

The global energy crisis has hastened the development and adoption of renewable energy sources. The rapid expansion of photovoltaic (PV) installed capacity exacerbates the challenge of unit forecasting errors, particularly amidst instantaneous irradiance fluctuations caused by cloud movement. To address the limitations of individual models in accurately characterizing power fluctuations, this paper proposes a pattern prediction framework based on cloud image for refined enhancement of PV power forecasting. The framework incorporates a classifier for adaptive pattern classification of cloud images, aligning them with corresponding PV power periods, and a predictor comprising two models: an ultra-short-term PV power forecasting model and a pattern recognition model. Simulation results demonstrate the framework's ability to accurately predict target period patterns, thereby enhancing forecasting precision, thus providing crucial technical support for constructing a secure and manageable new power system.

关键词： adaptive pattern classification pattern prediction PV power forecasting cloud image renewable energy sources

来源：评论

学校读者我要写书评

暂无评论

Implementation of Face Feature Algorithms for Authentication of a Person (IFFAP) 3

Implementation of Face Feature Algorithms for Authentication...

引用

3rd IEEE international conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Ramachandra, A.C. Monisha, B. Muralapur, Poorvika Vasupraneetha, H. Nitte Meenakshi Institute Of Technology Department Of Ece Bengaluru India

ISBN: (纸本)9798350318609

The present conventional digital financial transaction at Automated Teller Machines (ATM) is secured with PIN number, with this there are chances of forgetting or misusing to overcome this with the increase in technology and various advancements in financial infrastructure, most of the bank customers prefer to use Automated Teller Machines (ATM). To improve the security in such cases a new generation ATM machine which is based on face recognition technology is used. It also assists with changing passwords which increases privacy and security. The high-quality image has an important role in the recognition process. We propose Implementation of Face Feature Algorithms for Authentication of a Person (IFF AP) technique, an attempt to solve, The LBP algorithm and Haar Cascade techniques are employed for this process. This technology helps in increased security and avoids unauthorized transactions. This mutually benefits banking institutions and the customers. Leveraging existing algorithms, particularly those based on Local Binary pattern (LBP) and Haar Cascade, reveals a commendable qualitative analysis showcasing high accuracy up to 92.85% and improves computational efficiency compared to existing Techniques. © 2024 IEEE.

关键词： Local binary pattern

来源：评论

学校读者我要写书评

暂无评论

Islanding Detection Using pattern recognition with HOG Features by Random Forest 3

Islanding Detection Using Pattern Recognition with HOG Featu...

引用

3rd IEEE international conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2024

作者： Pal, Kumaresh Goswami, Subhadip Manna, Pranendu Kumbhakar, Shyamal Benia, Tapas Kumar Yadav, Pawan Kumar National Institute of Technology Department of Electrical Engineering Jamshedpur India National Institute of Technology Department of Electrical Engineering Arunachal Pradesh India Techno India University Department of Electrical Engineering Kolkata India National Institute of Technology Department of Electrical Engineering Silchar India

ISBN: (纸本)9798350387193

Islanding is a significant obstacle along with excessive penetration of DG sources. The islanding could cause harm to the customers and their equipments. The IEEE 1547 DG interconnection regulations stipulate that the DG must be disconnected and the islanding must be observed within two seconds. Basically, this paper presents a novel method for detecting islanding based upon image pattern recognition using Random Forest (RF) classification technique is proposed. Images are utilised to derive the histogram of oriented gradient (HOG) characteristics so as to identify non-islanding as well as islanding events. Hence, the time series signal is obtained and transformed into spectrogram images at the point of common connection. These images are utilised to extract the features using histogram of oriented gradient, which is then utilised as a feature vector input for the RF classifier for training as well as testing. It uses rate of change of negative sequence voltage parameter to derive spectrogram image. The RF classifier's effectiveness is assessed with 5, 10, 20 and 25-fold cross-validations. The results from classification demonstrates that detection of islanding using RF classifier and HOG feature being used for image pattern recognition achieved excellent results with 98.75% accuracy and detection time of 192 ms. © 2024 IEEE.

关键词： Spectrographs

来源：评论

学校读者我要写书评

暂无评论

10th iapr TC3 international Workshop on Artificial Neural Networks in pattern recognition, ANNPR 2022

10th IAPR TC3 International Workshop on Artificial Neural Ne...

引用

10th iapr TC3 international Workshop on Artificial Neural Networks in pattern recognition, ANNPR 2022

ISBN: (纸本)9783031206498

The proceedings contain 16 papers. The special focus in this conference is on Artificial Neural Networks in pattern recognition. The topics include: Sequence-to-Sequence CNN-BiLSTM Based Glottal Closure Instant Detection from Raw Speech;preface;graph Augmentation for Neural Networks Using Matching-Graphs;Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi;transformer-Encoder Generated Context-Aware Embeddings for Spell Correction;assessment of Pharmaceutical Patent Novelty with Siamese Neural Networks;white Blood Cell Classification of Porcine Blood Smear Images;medical Deepfake Detection using 3-Dimensional Neural Learning;a Study on the Autonomous Detection of Impact Craters;utilization of Vision Transformer for Classification and Ranking of Video Distortions;a Novel Representation of Graphical patterns for Graph Convolution Networks;minimizing Cross Intersections in Graph Drawing via Linear Splines;multi-stage Bias Mitigation for Individual Fairness in Algorithmic Decisions;do Minimal Complexity Least Squares Support Vector Machines Work?.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Traffic pattern recognition Algorithm Based on Multi-Scale Feature Extraction 3

Traffic Pattern Recognition Algorithm Based on Multi-Scale F...

引用

3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Zeng, Hao Sichuan Post and Telecommunication College Chengdu China

ISBN: (纸本)9798350317022

The characteristics of various traffic modes are analyzed, the fuzzy neural network is used to identify the traffic modes, the eigenvalues of the identified traffic modes are determined, and the correctness of the network is tested by traffic flow. The manual approaches significantly capture the spatial and temporal relationships as well as enhance the model complexity through examining both connected and unconnected roads. In feature extraction process, initially the input image is provided to the computation gradients process and processed output provided to the collect HOG over image and it provides the HOG feature. The test results show that the application of fuzzy neural network to traffic pattern recognition can accurately reflect the situation of traffic flow. Taking the results of traffic pattern recognition as the basis of road patency can guide the group control system to adopt corresponding strategies according to different traffic conditions. © 2023 IEEE.

关键词： feature extraction multiscale analysis traffic mode

来源：评论

学校读者我要写书评

暂无评论

Vehicle Theft Detection Using Neural pattern recognition 3

Vehicle Theft Detection Using Neural Pattern Recognition

引用

3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Jane Rubel Angelina, J. Subhashini, S.J. Kumar Rapuri, Anil Ravva, Vennela Rasala, Raghavendra Ray Adurgam, Sai Dcepak Kalasalingam Academy of Research and Education Dept of Computer Science and Engineering TamilNadu Krishnankoil India SRM Madurai College for Engineering and Technology Dept of Computer Science and Engineering TamilNadu Sivagangai India

ISBN: (纸本)9798350322842

Finding stolen cars is becoming increasingly important in many urban regions. An automated system for scanning license plates can recognize vehicle numbers without the need for human interaction. This work proposes a vehicle theft detection system based on neural pattern recognition, gaussian filter, and equilibrium optimization. The proposed architecture has significant speedup and higher accuracy rates. The proposed number plate recognition method has a maximum accuracy rate of 94% and an average reduction in the processing time of 32%. pattern recognition is the process of detecting regularities and patterns in data using machine learning. These analogies may now be uncovered via statistical analysis, historical data, or machine-generated knowledge. © 2023 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Time Series pattern Matching Technique for Low-Energy Arrhythmia Classification in Implantable Cardiac Devices 3

Time Series Pattern Matching Technique for Low-Energy Arrhyt...

引用

3rd international conference on Computing and Machine Intelligence (ICMI)

作者： Sengupta, Prianka John, Eugene B. Texas A&M Univ Dept Elect & Comp Engn Coll Satation TX 77843 USA Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX 78249 USA

ISBN: (纸本)9798350372977;9798350372984

Implantable cardiac devices (ICDs) are often used as an effective treatment for arrhythmia. Although these devices have access to a live Electrocardiogram (ECG) stream, currently they do not offer on-device classification of arrhythmia due to the limited computing capability and severe power constraints. In this paper we propose a low-energy computing method for extracting shape-based features from ECG in combination with machine learning techniques for classifying nine different cases of arrhythmia. This is achieved by using a Localized Longest Common Subsequence (LLCS) algorithm which has low computational requirements that allows on-device execution. The proposed method strongly focuses on maintaining minimal energy and computational footprint, in line with the operating constraints of implantable devices. To demonstrate the energy efficiency and low computation load of the proposed method we implement the classification pipeline on a low-power RISC microcontroller and compare its performance with existing classification techniques. The classification accuracy and energy of the proposed method is compared with state-of-the art research in arrhythmia classification.

关键词： Low-energy Computing Machine Learning Localized Longest Common Subsequence Low-energy Arrhythmia Classification Time Series pattern recognition

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220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：