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

2,119 篇 会议
47 篇 期刊文献
28 册 图书

馆藏范围

2,194 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,499 篇 工学
- 1,132 篇 计算机科学与技术...
- 655 篇 软件工程
- 274 篇 电气工程
- 252 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
664 篇 理学
- 348 篇 数学
- 207 篇 物理学
- 177 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

2,150 篇 英文
36 篇 其他
11 篇 中文

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

共 2194 条记录，以下是421-430 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：

Pattern similarities of vector matrices

引用

3rd international conference on Science, ICOS 2019

作者： Muhtar, N. Cahyono, E. Arman Ransi, N. Rofianto, D. Department of Mathematics Universitas Halu Oleo Indonesia Department of Computer Science Universitas Halu Oleo Indonesia Department of Computer Science Institut Pertanian Bogor Indonesia

A concept of vector matrix or matrix of vector is introduced. It is a well-known matrix where the elements are vectors. An example of vector matrix is a digital image represented in a matrix A m×n. The elements of A are vectors in R 3 represent color in red, green, blue, and m × n is the number of pixels. Similarity of two matrices is defined by the similarity of each corresponding elements. Such definition is very strict, two similar matrices must have the same vector for each corresponding elements. Applying for digital images, two similar matrices are actually the same image. Less similarity concept is introduced, namely pattern similarity. pattern similarity is a generalization of strict similarity by applying a pattern function. An application of pattern similarity is for object recognition. © Published under licence by IOP Publishing Ltd.

关键词： Vectors

来源：评论

学校读者我要写书评

暂无评论

A Real-Time Detection Drone Algorithm Based on Instance Semantic Segmentation 3

A Real-Time Detection Drone Algorithm Based on Instance Sema...

引用

3rd international conference on Video and Image Processing (ICVIP)

作者： Liu, Zihao Xu, Haiqin Zhang, Yihong Xu, Zhouyi Wu, Sen Zhu, Di DongHua Univ Shanghai Coll Informat Sci & Technol Engn Res Ctr Digitized Text & Fash Technol Minist Educ Shanghai Peoples R China Huawei Technol Co Ltd 2222 Xin Jin Qiao Rd Pudong Shanghai Peoples R China

ISBN: (纸本)9781450376822

With the rapid development of drones, drones are widely used in various fields and bring convenience to people's production and life. However, they also bring security problems to society and the country. Especially in airports or military areas, the flight of drones can cause some problems. In order to effectively supervise the drone, this paper proposes a real-time detection drone algorithm HR-YOLACT which is based on instance semantic segmentation, and designed a new drone data set. The proposed algorithm combines the real-time instance semantic segmentation algorithm YOLACT with the deep high-resolution representation classification network HRNet. Firstly, feature maps are extracted by HRNet's backbone network. Secondly, the feature pyramid network is used to further extract image features, so that the network has better classification ability. Finally, the improved prediction head is utilized to detect the boxes of drones. In addition, this paper uses cross entropy instead of focal loss as the loss function to obtain better network training speed and quality. The experimental results show that HR-YOLACT has faster detection speed and higher detection precision than existing popular real-time object detection and real-time instance semantic segmentation algorithms.

关键词： Drones detection instance semantic segmentation pattern recognition

来源：评论

学校读者我要写书评

暂无评论

pattern recognition in the differentiated image for the powder and granulated materials particle size classification 3

Pattern recognition in the differentiated image for the powd...

引用

3rd international conference on Information Processing and Control Engineering (ICIPCE)

作者： Yunovidov, D. V. Nadezhin, M. N. Shabalov, V. A. JSC NIUIF Severnoe Shosse 75 Cherepovets 162622 Russia Cherepovets State Univ Off 203Lunacharsky Str 5 Cherepovets 162622 Russia

The paper shows and investigates the technique of classifying the particle size of powder and granulated materials. The objects of the study are industrially produced mineral fertilizers. Samples with different composition (about five types of mineral fertilizers) and various degrees of particle size (less than 100 mu m, less than 500 mu m and granules of 2-5 mm) were examined. The samples particles have an irregular shape, close to spherical (in the case of granules) or cubic (in the case of powders). To improve the accuracy and eliminate the particle shape influence on analysis, the preliminary pressing of samples on a boric acid substrate was used. The keynote of the proposed technique is to obtain an optoelectronic image of an object with a resolution of at least 640x480 pixels (a three-dimensional matrix of pixel intensity in the Red-Green-Blue (RGB) system). Next, the area of analysis is separated from the obtained image and transformed into grayscale (a two-dimensional matrix of pixel intensities with a resolution of at least 200x200 pixels). The influence of external illumination (gradient, temperature and brightness) is eliminated by the grayscale image differentiation. The result is the "surface map" of the sample, which reflects defects in the pressed structure (patterns, which are responsible for the size of the particles). According to the found patterns, the samples are classified according to their particle size. Four classification algorithms were investigated (linear, linear with L1 and L2 regularization, and a nonlinear "random forest"). All proposed approaches are automated and implemented in the Python 3.6 programming language. There is provided the selection of the operating parameters of all the described algorithms.

关键词： Particle size

来源：评论

学校读者我要写书评

暂无评论

Constrain latent space for schizophrenia classification via dual space mapping net 23rd

Constrain latent space for schizophrenia classification via ...

引用

23rd international conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Shi, Weiyang Xu, Kaibin Song, Ming Fan, Lingzhong Jiang, Tianzi Brainnetome Center and National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China Innovation Academy for Artificial Intelligence Chinese Academy of Sciences Beijing China Key Laboratory for Neuro Information of Ministry of Education School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China Queensland Brain Institute University of Queensland Brisbane Australia

ISBN: (纸本)9783030597092

Mining potential biomarkers of schizophrenia (SCZ) while performing classification is essential for the research of SCZ. However, most related studies only perform a simple binary classification with high-dimensional neuroimaging features that ignore individuals unique clinical symptoms. And the biomarkers mined in this way are more susceptible to confounding factors such as demographic factors. To address these questions, we propose a novel end-to-end framework, named Dual Spaces Mapping Net (DSM-Net), to map the neuroimaging features and clinical symptoms to a shared decoupled latent space, so that constrain the latent space into a solution space associated with detailed symptoms of SCZ. Briefly, taking functional connectivity patterns and the Positive and Negative Syndrome Scale (PANSS) scores as input views, DSM-Net maps the inputs to a shared decoupled latent space which is more discriminative. Besides, with an invertible space mapping sub-network, DSM-Net transforms multi-view learning into multi-task learning and provides regression of PANSS scores as an extra benefit. We evaluate the proposed DSM-Net with multi-site data of SCZ in the leave-one-site-out cross validation setting and experimental results illustrate the effectiveness of DSM-Net in classification, regression performance, and unearthing neuroimaging biomarkers with individual specificity, population commonality and less effect of confusions. © Springer Nature Switzerland AG 2020.

关键词： Neuroimaging

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of Deepfake Video Detection Method

A Comparative Study of Deepfake Video Detection Method

引用

international conference on Information and Communications Technology (ICOIACT)

作者： Kurniawan Nur Ramadhani Rinaldi Munir School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia School of Computing Telkom University Bandung Indonesia

ISBN: (数字)9781728173566

ISBN: (纸本)9781728173573

Deepfake technology allows humans to manipulate images and videos using deep learning technology. The results from deepfakes are very difficult to distinguish using ordinary vision. Many algorithms are built to detect deepfake content in images and videos. There are several approaches in deepfake detection, including a visual feature-based approach, a local feature-based approach, a deep feature-based approach and a temporal feature-based approach. The main challenge in developing deepfake detection algorithms is the variety of existing deepfake models in both images and videos. Another challenge is that deepfake technology is still evolving, making deepfake images and videos look more realistic and harder to detect.

关键词： Visualization Feature extraction pattern recognition Information and communication technology Detection algorithms Videos Information integrity

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on Intelligent Information Technologies, ICIIT 2018

3rd International Conference on Intelligent Information Tech...

引用

3rd international conference on Intelligent Information Technologies, ICIIT 2018

ISBN: (纸本)9789811335815

The proceedings contain 15 papers. The special focus in this conference is on Intelligent Information Technologies. The topics include: Linear and nonlinear analysis of cardiac and diabetic subjects;a study on discontinuity pattern in online social networks data using regression discontinuity design;“senator, We Sell Ads”: Analysis of the 2016 russian facebook ads campaign;Semantic query-based patent summarization system (SQPSS);proposed strategy for allergy prediction based on weather forecasting and social media analysis;wind characteristics and weibull parameter analysis to predict wind power potential along the south-east Coastline of Tamil Nadu;cloud enabled intrusion detector and alerter using improved deep learning technique;temporal and stochastic modelling of attacker behaviour;automatic license plate recognition using deep learning;towards reliable storage for cloud systems with selective data encryption and splitting strategy;Smart solar energy based irrigation system with GSM;understanding the role of visual features in emoji similarity;Semantic network based cognitive, NLP powered question answering system for teaching electrical motor concepts;novel wrapper-based feature selection for efficient clinical decision support system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Low-Frequency Oscillation pattern recognition Based on Wavelet Packet and SVM 3

Low-Frequency Oscillation Pattern Recognition Based on Wavel...

引用

3rd IEEE conference on Energy Internet and Energy System Integration, EI2 2019

作者： Hu, Hongmang Xiao, Hui He, Xu Li, Anle Liu, Ping He, Hui State Grid Changsha County Power Supply Company Changsha Hunan China Changsha University of Science and Technolgy College of Electrical and Information Engineering Changsha Hunan China Industrial Control Services Pte Ltd. Singapore. Singapore China Technology Energy Group Co. Ltd. Changsha Hunan China Wuling Power Corporation LTD. Changsha Hunan China State Grid Hunan Electric Power Corporation Changsha Hunan China

ISBN: (纸本)9781728131375

Traditional low-frequency oscillation mode identification methods have complex calculation processes and poor real-time performance, which make it difficult to meet the computational requirements of pattern classification of low-frequency oscillation in complex power system. Based on wavelet packet and support vector machine (SVM), a more simple and convenient method of identification and classification is proposed in this paper. The low-frequency oscillation signal is selected as the research object, and the wavelet packet decomposition of the signal in different modes is used to extract the energy eigenvector samples in this method. To achieve low-frequency oscillation mode identification classification, the principal component analysis (PCA) is used to reduce the energy eigenvectors and construct the SVM pattern recognition classifier. The simulation results show that this method can realize the classification of low-frequency oscillation modes in power system more quickly and accurately. The method proposed in this paper has good application prospects. © 2019 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Sausage Colony Detection Based on Hyperspectral Image Analysis via Machine Learning 19

Sausage Colony Detection Based on Hyperspectral Image Analys...

引用

3rd international conference on Deep Learning Technologies (ICDLT)

作者： Xiao, Hongbing Guo, Peiyuan Chen, Xiaodong Beijing Technol & Business Univ Sch Informat Engn Beijing Peoples R China

ISBN: (纸本)9781450371605

Sausage is a kind of food that people often eat in our lives because it is cheap and delicious. However, in the process of sausage production and transportation, if the quality control is not strict, it will cause deterioration and decay. If people eat these sausages, they will be sick and even die. Existing detection methods, such as physical and chemical detection, need a strict testing environment, and the sensory detection is inaccurate and incomplete. Colonies number is a key quality measure of sausage. Therefore, we planed to study a method to achieve rapid, non-destructive and accurate detection of sausage colonies number. In this paper, a method for detecting sausage colonies number based on hyperspectral technique and image features was proposed. Firstly, the sausage hyperspectral image and spectral information were collected. Then, the N-Dimensional Visualizer was used to extract features from the hyperspectral image. Moreover, the characteristic samples of sausage surface colony information were obtained by studying the colony surface characteristic spectrum curve and the color statistics of sample graphics. At last, the colony spectrum library was established and the two feature data were fused via the machine learning algorithm Support Vector Machine (SVM) to classify sausage quality. According to the established surface colony characteristic model, the samples of validation set were detected, and the fast detection of sausage colony quality was realized. The experimental results showed that the pixel proportion of the colony information in the image was consistent with the actual colony information measured in the physical and chemical experiments, which proved that the method is feasible to study the colony on the sausage surface. The method in this study can also be further extended to the detection of other related meat products.

关键词： hyperspectral image pattern recognition machine learning SVM

来源：评论

学校读者我要写书评

暂无评论

3rd international Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2019

3rd International Symposium on Cyber Security Cryptography a...

引用

3rd international Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2019

ISBN: (纸本)9783030209506

The proceedings contain 28 papers. The special focus in this conference is on Cyber Security Cryptography and Machine Learning. The topics include: The advantage of truncated permutations;reconstructing C2 servers for remote access trojans with symbolic execution;generating a random string with a fixed weight;an access control model for data security in online social networks based on role and user credibility;enhancing image steganalysis with adversarially generated examples;controllable privacy preserving blockchain: Fiatchain: Distributed privacy preserving cryptocurrency with law enforcement capabilities;a relay attack on a tamper detection system;amended cross-entropy cost: An approach for encouraging diversity in classification ensemble;governance and regulations implications on machine learning;linear cryptanalysis reduced round of piccolo-80;simulating homomorphic evaluation of deep learning predictions;Everything is in the name – a URL based approach for phishing detection;network cloudification;new goal recognition algorithms using attack graphs;peerClear: Peer-to-peer bot-net detection;Rethinking identification protocols from the point of view of the GDPR;Temporal pattern-based malicious activity detection in SCADA systems;anonymous deniable identification in ephemeral setup and leakage scenarios;randomized and set-system based collusion resistant key predistribution schemes;continuous key agreement with reduced bandwidth;Covert channel cyber-attack over video stream DCT payload: (Copyright protection algorithm for video and audio streams);Effects of weather on drone to IoT QKD;malware classification using image representation;MLDStore: DNNs as similitude models for sharing big data;cyber attack localization in smart grids by graph modulation;Beyond replications in blockchain: on/off-blockchain IDA for storage efficiency and confidentiality.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Neural Network Control Interface of the Speaker Dependent Computer System "Deep Interactive Voice Assistant DIVA" to Help People with Speech Impairments 3rd

Neural Network Control Interface of the Speaker Dependent Co...

引用

3rd international Scientific conference on Intelligent Information Technologies for Industry (IITI)

作者： Khorosheva, Tatiana Novoseltseva, Marina Geidarov, Nazim Krivosheev, Nikolay Chernenko, Sergey Kemerovo State Univ Kemerovo Russia

ISBN: (纸本)9783030018184

With the development of modern informational communication systems, voice control interface and speech recognition systems find application in various fields of activity. One application of such systems is for people with special needs who have speech impairments, and thus find using speech-dependent voice interfaces challenging. Our research team is developing a speaker dependent computer system "Deep Interactive Voice Assistant" (DIVA), which allows recognizing an arbitrary set of commands to control the computing system. The article presents the results of testing various artificial neural networks to train the machine to recognize vocal inputs. We examine such architectures as associative memory, multilayer perceptron and convolutional network. The research justifies the use of multilayer perceptron for the speaker dependent computer system DIVA as a training solution that demonstrated high results on a small selection. DIVA will be implemented in voice-user interface of such systems as "Smart House", mobile applications and IT-based assistive systems.

关键词： Voice interface technology Speech recognition technology Assistive technologies Neural network Multilayer perceptron pattern recognition Associative memory

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 << < 39 40 41 42 43 44 45 46 47 48 > >>

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：