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

6,797 篇 会议
647 册 图书
127 篇 期刊文献

馆藏范围

7,570 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

3,892 篇 工学
- 3,084 篇 计算机科学与技术...
- 1,402 篇 软件工程
- 793 篇 电气工程
- 676 篇 信息与通信工程
- 502 篇 控制科学与工程
- 298 篇 生物工程
- 281 篇 生物医学工程（可授...
- 265 篇 机械工程
- 189 篇 光学工程
- 162 篇 电子科学与技术（可...
- 144 篇 仪器科学与技术
- 140 篇 化学工程与技术
- 59 篇 安全科学与工程
- 45 篇 材料科学与工程（可...
- 36 篇 交通运输工程
1,220 篇 理学
- 671 篇 数学
- 357 篇 物理学
- 333 篇 生物学
- 197 篇 统计学（可授理学、...
- 147 篇 化学
- 105 篇 系统科学
553 篇 管理学
- 314 篇 管理科学与工程(可...
- 255 篇 图书情报与档案管...
- 59 篇 工商管理
273 篇 医学
- 230 篇 临床医学
- 109 篇 基础医学(可授医学...
- 75 篇 药学(可授医学、理...
66 篇 法学
- 62 篇 社会学
51 篇 艺术学
- 49 篇 设计学（可授艺术学...
42 篇 农学
- 39 篇 作物学
21 篇 教育学
19 篇 文学
17 篇 经济学
5 篇 军事学

主题

3,167 篇 pattern recognit...
535 篇 feature extracti...
431 篇 artificial intel...
385 篇 neural networks
297 篇 machine learning
295 篇 data mining
233 篇 face recognition
224 篇 pattern matching
216 篇 support vector m...
203 篇 image segmentati...
194 篇 pattern classifi...
194 篇 computer imaging...
183 篇 computer science
182 篇 local binary pat...
168 篇 computational mo...
160 篇 computer vision
147 篇 computer applica...
147 篇 humans
147 篇 testing
143 篇 training

机构

40 篇 school of comput...
38 篇 national laborat...
25 篇 indian institute...
25 篇 institute of ima...
24 篇 center for resea...
24 篇 computer vision ...
22 篇 institute of ima...
22 篇 university of ch...
21 篇 auckland univers...
21 篇 department of co...
20 篇 city university ...
20 篇 indian statistic...
19 篇 murdoch universi...
19 篇 national laborat...
19 篇 institute of com...
18 篇 king fahd univer...
16 篇 tongji universit...
16 篇 chinese academy ...
15 篇 institute for pa...
14 篇 national center ...

作者

35 篇 yang jie
31 篇 de-shuang huang
25 篇 tieniu tan
23 篇 umapada pal
21 篇 mufti mahmud
19 篇 zohreh doborjeh
19 篇 ryszard tadeusie...
19 篇 m. tanveer
19 篇 andrew chi sing ...
19 篇 kevin wong
19 篇 liang wang
18 篇 ajith abraham
18 篇 maryam doborjeh
17 篇 marcin korytkows...
17 篇 lu hanqing
17 篇 jacek m. zurada
17 篇 leszek rutkowski
16 篇 jie yang
16 篇 zhenan sun
16 篇 shamsuddin siti ...

语言

7,289 篇 英文
216 篇 其他
81 篇 中文

检索条件"任意字段=International Conference of Soft Computing and Pattern Recognition"

共 7572 条记录，以下是1301-1310 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：

The Effect of Spectrogram Reconstruction on Automatic Music Transcription: An Alternative Approach to Improve Transcription Accuracy

The Effect of Spectrogram Reconstruction on Automatic Music ...

引用

international conference on pattern recognition

作者： Kin Wai Cheuk Yin-Jvun Luo Emmanouil Benetos Dorien Herremans Institute of High Performance Computing Agency for Science Technology and Research School of Electronic Engineering and Computer Science Queen Mary University of London

ISBN: (纸本)9781728188089;9781728188096

Most of the state-of-the-art automatic music transcription (AMT) models break down the main transcription task into sub-tasks such as onset prediction and offset prediction and train them with onset and offset labels. These predictions are then concatenated together and used as the input to train another model with the pitch labels to obtain the final transcription. We attempt to use only the pitch labels (together with spectrogram reconstruction loss) and explore how far this model can go without introducing supervised sub-tasks. In this paper, we do not aim at achieving state-of-the-art transcription accuracy, instead, we explore the effect that spectrogram reconstruction has on our AMT model. Our proposed model consists of two U-nets: the first U-net transcribes the spectrogram into a posteriorgram, and a second U-net transforms the posteriorgram back into a spectrogram. A reconstruction loss is applied between the original spectrogram and the reconstructed spectrogram to constrain the second U-net to focus only on reconstruction. We train our model on three different datasets: MAPS, MAESTRO, and MusicNet. Our experiments show that adding the reconstruction loss can generally improve the note-level transcription accuracy when compared to the same model without the reconstruction part. Moreover, it can also boost the frame-level precision to be higher than the state-of-the-art models. The feature maps learned by our U-net contain gridlike structures (not present in the baseline model) which implies that with the presence of the reconstruction loss, the model is probably trying to count along both the time and frequency axis, resulting in a higher note-level transcription accuracy.

关键词： Training Measurement Time-frequency analysis Transforms Predictive models Market research pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Smart Snickometer for assisting Cricketing Umpires

Smart Snickometer for assisting Cricketing Umpires

引用

5th international conference on computing, Communication and Security (ICCCS)

作者： Pavuluri, Kumar Raja Aishwarya, Nilay Kumar, Arvind Kishore, Kamlesh Vodafone Intelligent Solut Pune Maharashtra India Deloitte Bangalore Karnataka India Birla Inst Technol Dept Elect & Commun Ranchi Bihar India RTC Inst Technol Dept Elect & Commun Ranchi Bihar India

ISBN: (纸本)9781728191805

This paper proposes a novel technique for designing a smart Snickometer for assisting on field cricketing umpires and evaluates its performance for combination of different classifiers and features. Snickometer are used to analyze weak signals coming from bat/pad/gloves when incoming ball hits any part of them. The sound generated are captured from high sensitive microphone attached to the stumps and are synced with video for offline analysis. A decision is made by simultaneous analysis of both video and oscilloscope in slow motion. The traditional method involves manual interpretation and may lead to erroneous judgment. The entire verification process sometime takes too much time. To overcome the limitation of the current working model, a Smart Snickometer is proposed. Data are collected in real time environment. Feature extracted from these data are fed to different classifiers and their performance is reported. Best classification accuracy of 95.83% is achieved with both K-Nearest Neighbour (KNN) and Support Vector Machine (SVM). Maximum Amplitude and Peak Energy are best performing features.

关键词： Cricket Snickorneter Machine Learning pattern recognition Time-frequency Analysis

来源：评论

学校读者我要写书评

暂无评论

A Novel Clustering-Based Gene Expression pattern Analysis for Human Diabetes Patients Using Intuitionistic Fuzzy Set and Multigranulation Rough Set Model 4th

A Novel Clustering-Based Gene Expression Pattern Analysis fo...

引用

4th international conference on soft computing: Theories and Applications, SoCTA 2019

作者： Ghosh, Swarup Kr Ghosh, Anupam Department of Computer Science and Engineering Sister Nivedita University Kolkata700156 India Department of Computer Science and Engineering Netaji Subhash Engineering College Kolkata700152 India

ISBN: (纸本)9789811540318

In this article, we present an intuitionistic fuzzy set (IFS)-based gene expression pattern classification using multigranulation rough set theory for human diabetes patient. At the very beginning, the proposed scheme generates a soft-information structure from the microarray by IFS via multiple fuzzy membership functions with Yager generating function. The intuitionistic fuzzy set deals with the ambiguity between normal state and diabetic state from gene expression microarray via the hesitation degree while shaping the membership function. Thereafter, a multigranulation rough set is utilized for the measurement of accuracy and roughness from expression pattern that has been deferentially expressed from normal state to diabetic state. Lastly, Rough-fuzzy C-means clustering has been applied on the datasets into two clusters such as diabetes or non-diabetes. The associations among human genes have also been identified which are correlated with diabetes (type-2). In addition, we have validated a measurement by F-score using diabetes gene expression NCBI database and achieved better performance in comparison with baseline methods. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Rough set theory

来源：评论

学校读者我要写书评

暂无评论

Binary neural network based real time emotion detection on an edge computing device to detect passenger anomaly

Binary neural network based real time emotion detection on a...

引用

international conference on VLSI Design

作者： B S Ajay Madhav Rao Pre-Si Valid/Verif Engineer Intel Technology India Pvt. Ltd. Bangalore India Surgical and Assistive Robotics Lab International Institute of Information Technology Bangalore India

ISBN: (纸本)9781665440875;9781665431279

Passenger safety in public transportation especially while riding in the form of shared cabs, and taxis are often ignored, and not much preventive protocols are devised. In the connected mobility world, emotion recognition from facial expressions is a possibility, however a faster processing and edge computing device to derive anomaly state inferences will be apt for further notifying about the safety of the passenger. FPGA implementation is a viable approach to not only implement in the embedded system automotive electronics, but also accelerate the inference results, hence making it as an ideal real time candidate for passenger anomaly state identification. For the same, a real time emotion detection system using facial features was implemented on FPGA. A Binary Neural Network (BNN) feeded by Local Binary pattern (LBP) output was designed towards the development of an improved and faster emotion recognition system. LBP is configured as a preprocessing step to extract facial features that is passed on to the BNN layer for successful inference. The preprocessing method utilizes Viola-Jones (VJ) algorithm to extract facial data while removing other background information from the image. The LBP-BNN network is modelled using Facial Expression 2013 (FER-2013) data set for training. The custom hardware accelerator or the overlay is synthesized and the designed IP is implemented on FPGA for the inference. Inference is done using the trained model on FPGA to enable faster classified results. Emotion detection using facial expressions is classified to six states namely: angry, disgust, fear, happy, sad, and surprise. The LBP-BNN network is implemented in FPGA, to realize a real time facial emotion recognition by capturing the image of a person from a web camera interfaced to the FPGA acting as edge computing inference device, with acceptable accuracy. The image processing based emotion detection design is highly suitable for other applications including tracking of emotion

关键词： Emotion recognition Embedded systems Neural networks Feature extraction Real-time systems Hardware Safety

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Based on the Principle of Minimizing Robust Mean Estimates 11th

Machine Learning Based on the Principle of Minimizing Robust...

引用

11th Annual international conference on Brain-Inspired Cognitive Architectures for Artificial Intelligence, BICA*AI 2020

作者： Shibzukhov, Z.M. Institute of Mathematics and Informatics of Moscow Pedagogical State University Moscow Russia Institute of Physics and Technology Moscow Russia

ISBN: (纸本)9783030655952

The classical approach in machine learning, based on the principle of minimizing the arithmetic mean of parameterized functions, is vulnerable if training is carried out on the basis of data containing outliers. The article considers the approach to the construction of robust methods and machine learning algorithms, which are based on the principle of minimizing estimates of average values that are insensitive to outliers. Proposed machine learning algorithms are based on the principle of iterative reweighting. Illustrative examples show the ability of the proposed approach and algorithms to overcome the effect of outliers. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

5th international Symposium on Intelligent Systems Technologies and Applications, ISTA 2019

5th International Symposium on Intelligent Systems Technolog...

引用

5th international Symposium on Intelligent Systems Technologies and Applications, ISTA 2019

ISBN: (纸本)9789811539138

The proceedings contain 21 papers. The special focus in this conference is on Intelligent Systems Technologies and Applications. The topics include: An Efficient Text Labeling Framework Using Active Learning Model;Exploring the Potential of Virtual Reality in Fire Training Research Using A’WOT Hybrid Method;a Task Parallel Programming Framework Based on Heterogeneous computing Platforms;using computing software to Evaluate How Physical Conditions Affect the Chess Players Results in the World Chess Championship;Extractive Single Document Summarization Using NSGA-II;application of Coverage Path Planning Algorithm for Milling Operations;a Novel Lightweight Authentication for Intelligent Energy Monitoring in Smart Home;a Real-Time IoT-Based Nitrate Sensing System Using Interdigital Transducer;Interpreting Microgrid Reliability Using RBD-Quantitative Approaches;residual and Ensemble Learning on Locally Derived Features for Face recognition;survey on LoRa Technology: Solution for Internet of Things;blockchain-Based Decentralized and Secure Lightweight E-Health System for Electronic Health Records;RIGGU: A Semi-humanoid Robot Platform for Speech and Image recognition;emotion recognition from Facial Expressions in Children and Adults Using Deep Neural Network;deep Learning-Based Automatic Classification of Slide Frames and Presenter Frames;a Meta-Heuristic Model Based Computational Intelligence in Exploration and Classification of Autism in Children;steganalysis of Reversible Data Hiding in Color Image Using Grayscale Invariance;handwritten English Character recognition Using Swarm Intelligence and Neural Network;soft computing Approach to Determine Students’ Level of Comprehension Using a Mamdani Fuzzy System.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Analysis on Student' Psychologic Status of Online Learning under Extraction Model from Computer Face Features 5

The Analysis on Student' Psychologic Status of Online Learni...

引用

2020 5th international conference on Intelligent computing and Signal Processing, ICSP 2020

作者： Wen, Lan Yang, Shaogang Zeng, Jiao Liang, Xiaowen Xu, Yanping Institute of Psychological and Education South China Business College Guangdong University of Foreign Studies China South China Business College Guangdong University of Foreign Studies China

The research aims to analyze students' psychological mood during online study and enhance the efficiency of learning. In this research, face features are extracted by LBP (local binary pattern) algorithm based on face feature recognition. The facial feature points are tracked by CLM (constrained local model) algorithm, and the face images are normalized by AdaBoost algorithm. In the end, the fatigue level of learners is calculated by P80 method in PERCLOS criterion to verify the accuracy, recognition rate and error rate of the model. The results indicate that through the recognition of the faces in a complex background, the accuracy of the mode is 95%, the recognition rate is 95.53% and the error rate is only 0.53%, the range of aspect ratio in the human eye image is 0.22 ≤ λopen ≤ 0.27, 0.05 ≤ λclose ≤0.1, and learner's level of excitement can be estimated according to the range of f. Therefore, this algorithm model can extract learner's facial features very well and show a good result. Detecting the degree of learner's excitement accurately can provide an important fundamental for the realization of online learning emotion detection system which also has guiding significance for the development and popularization of the networked education. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Local binary pattern

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on Advanced computing and Intelligent Engineering, ICACIE 2018

3rd International Conference on Advanced Computing and Intel...

引用

3rd international conference on Advanced computing and Intelligent Engineering, ICACIE 2018

ISBN: (纸本)9789811510809

The proceedings contain 54 papers. The special focus in this conference is on Advanced computing and Intelligent Engineering. The topics include: Wavelet Transform Domain Methods for Resolution Enhancement of Satellite Images;improving Query Results in Ontology-Based Case-Based Reasoning by Dynamic Assignment of Feature Weights;a Survey on Representation for Itemsets in Association Rule Mining;efficient Clustering Using Nonnegative Matrix Factorization for Gene Expression Dataset;design of Random Forest Algorithm Based Model for Tachycardia Detection;detection of Spam in YouTube Comments Using Different Classifiers;deep Learning Architectures for Named Entity recognition: A Survey;effect of Familiarity on recognition of Pleasant and Unpleasant Emotional States Induced by Hindi Music Videos;early Detection of Breast Cancer Using Support Vector Machine With Sequential Minimal Optimization;the Case Study of Brain Tumor Data Analysis Using Stata and R;predictive Data Analytics for Breast Cancer Prognosis;a Semantic Approach of Building Dynamic Learner Profile Model Using WordNet;prioritizing Public Grievance Redressal Using Text Mining and Sentimental Analysis;an Automatic Summarizer for a Low-Resourced Language;printed Odia Symbols for Character recognition: A Database Study;importance of Data Standardization Methods on Stock Indices Prediction Accuracy;Feature Relevance Analysis and Feature Reduction of UNSW NB-15 Using Neural Networks on MAMLS;video Summarization Based on Optical Flow;Decision Support System for Black Classification of Dental Images Using GIST Descriptors;clustering Performance Analysis;pattern Analysis of Brain Functional Connectivity Parameters After Removal of Artifactual Motifs from EEG During Meditation;Hyper-heuristic Image Enhancement (HHIE): A Reinforcement Learning Method for Image Contrast Enhancement.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Innovative Computational Moulding Approach for Genomics

Innovative Computational Moulding Approach for Genomics

引用

international conference on Innovative computing (ICIC)

作者： Mehnaz Sarwar Hassaan Malik Insia Zahra National College of Business Administration and Economics Lahore Multan Campus Pakistan School of systems and technology University of Management and Technology Lahore Pakistan Institute of Computer Science and Information Technology The Women University Multan Pakistan

ISBN: (纸本)9781665400923

In the modern era, deep learning studies have been undertaken in different fields of research such as speech recognition, image type, autonomous use, and language processing. The objective of the project is to examine the use of genomics in deep learning. The study focuses on literature using DL models. The in-depth study showed a significant improvement in overall performance in compound classification and regression problems, wherever the complicated form of large-dimensional statistics is difficult to exploit to take advantage of convolutional ML algorithms. In the field of biology, deep learning applications are gaining popularity in predicting the shape and feature of genomic elements, together with enhancers, promoters, or gene expression levels.. In this review article, we generally tend to expose the most used deep learning architectures for the genomic domain. Then we supplied a concise overview of deep learning applications in genomics and artificial biology on the ranges of DNA, RNA, and protein. Finally, we affirmed the prevailing difficult situations and emerging perspective of deep learning in genomics.

关键词： Deep learning Shape Computational modeling Biological system modeling RNA soft sensors Genomics

来源：评论

学校读者我要写书评

暂无评论

9th international conference on soft computing for Problem Solving, SocProS 2019

9th International Conference on Soft Computing for Problem S...

引用

9th international conference on soft computing for Problem Solving, SocProS 2019

ISBN: (纸本)9789811532894

The proceedings contain 43 papers. The special focus in this conference is on soft computing for Problem Solving. The topics include: Electrophysiological Studies on Acetylcholine–Dopamine Interaction and Effect of Dopamine on Learning;Reinforcement Learning for Multiple HAPS/UAV Coordination: Impact of Exploration–Exploitation Dilemma on Convergence;Artificial Electric Field Algorithm for Solving Real Parameter CEC 2017 Benchmark Problems;flow Shop Scheduling Problem of Minimizing Makespan with Bounded Processing Parameters;finger-Induced Motor Imagery Classification from Hemodynamic Response Using Type-2 Fuzzy Sets;bit-Plane Specific Randomness Testing for Statistical Analysis of Ciphers;analysis of Rotation-Based Diffusion Functions;Detection of Abnormalities in Blood Sample Using WBC Differential Count;a Novel U-Shaped Transfer Function for Binary Particle Swarm Optimisation;performance Analysis of Whale Optimization Algorithm Based on Strategy Parameter;flat Splicing-Based Generative Model for Hexagonal Picture Array Languages;EEG-Induced Error Correction in Path Planning by a Mobile Robot Using Learning Automata;brain Connectivity Analysis in Color Perception Problem Using Convergent Cross Mapping Technique;distinct Prime Distance Labeling of Certain Graphs;interval Variational Inequalities;EEG-Based Epileptic Seizure Detection Using Least Square SVM with Spectral and Multiscale Key Point Energy Features;Maiden Application of Hybrid Crow Search Algorithm with pattern Search Algorithm in LFC Studies of a Multi-area System Using Cascade FOPI-PDN Controller;an Immuno-inspired Distributed Artificial Classification System;Comparison of PSO and Sequential Search Algorithms for Improvisation of Entropy-Based Ear Localization;an Upgraded Differential Evolution via Memory-Based Mechanism for Economic Dispatch;some Applications of Generalized Fuzzy γ*-Closed Sets;multi-Headed Self-Attention-based Hierarchical Model for Extractive Summarization.

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500页 << < 127 128 129 130 131 132 133 134 135 136 > >>

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：