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

6,793 篇 会议
630 册 图书
130 篇 期刊文献

馆藏范围

7,552 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

3,899 篇 工学
- 3,090 篇 计算机科学与技术...
- 1,403 篇 软件工程
- 794 篇 电气工程
- 679 篇 信息与通信工程
- 503 篇 控制科学与工程
- 299 篇 生物工程
- 281 篇 生物医学工程（可授...
- 265 篇 机械工程
- 191 篇 光学工程
- 163 篇 电子科学与技术（可...
- 145 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
1,222 篇 理学
- 673 篇 数学
- 356 篇 物理学
- 334 篇 生物学
- 198 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
274 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
18 篇 经济学
5 篇 军事学

主题

3,150 篇 pattern recognit...
535 篇 feature extracti...
429 篇 artificial intel...
385 篇 neural networks
295 篇 data mining
278 篇 machine learning
234 篇 face recognition
224 篇 pattern matching
215 篇 support vector m...
203 篇 image segmentati...
194 篇 pattern classifi...
193 篇 computer imaging...
183 篇 computer science
182 篇 local binary pat...
168 篇 computational mo...
159 篇 computer vision
147 篇 humans
146 篇 testing
142 篇 accuracy
141 篇 training

机构

40 篇 school of comput...
38 篇 national laborat...
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 department of co...
20 篇 indian statistic...
19 篇 national laborat...
19 篇 institute of com...
16 篇 tongji universit...
16 篇 chinese academy ...
15 篇 institute for pa...
14 篇 national center ...
14 篇 chinese acad sci...
14 篇 częstochowa univ...
13 篇 agh university o...
13 篇 school of electr...
12 篇 indian stat inst...

作者

35 篇 yang jie
31 篇 de-shuang huang
25 篇 tieniu tan
23 篇 umapada pal
19 篇 ryszard tadeusie...
19 篇 liang wang
18 篇 ajith abraham
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 ...
16 篇 pal umapada
15 篇 wang da-han
15 篇 chew lim tan
15 篇 rafał scherer
14 篇 xu changsheng
14 篇 lotfi a. zadeh

语言

7,403 篇 英文
84 篇 其他
77 篇 中文

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

共 7554 条记录，以下是601-610 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：

Facial Emotion recognition Using CNNs: Implications for Affective computing and Surveillance

Facial Emotion Recognition Using CNNs: Implications for Affe...

引用

international conference on Computational and Characterization Techniques in Engineering & Sciences (CCTES)

作者： Vishnu Kant Panchal Sandeep Govindrao Shubham Mahajan Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Dept of Computer Engineering G H Raisoni College of Engineering and Management Pune Department Of Computer Science Christ Deemed to Be University Delhi-NCR

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

Human-computer interaction depends on facial expression detection, which also finds utility in mental health monitoring to improve digital environment user experiences. Perfect spotting Computer vision has always baffled emotions including rage, disdain, disgust, fear, happiness, neutrality, grief, and surprise. Since they can automatically generate hierarchical feature representations from raw visual data, CNN have been rather helpful tools in tackling these problems. This article presents a CNN-based method for facial emotion prediction by using the power of the network to detect minute changes in face features linked with different emotional states. Having been trained on a large collection of annotated facial photos, the suggested model achieved final accuracy of 92%. The results reveal in emotional computing, surveillance, and automated customer service the effectiveness and most likely applications of the model. This study helps sustainable digital technologies—, which might be applied in health, education, and well-being—to be always developed.

关键词： Emotion recognition Visualization Accuracy Computational modeling Face recognition Surveillance soft sensors Education Mental health User experience

来源：评论

学校读者我要写书评

暂无评论

Meta Transductive Linear Probing for Few-Shot Node Classification

Meta Transductive Linear Probing for Few-Shot Node Classific...

引用

pattern recognition and Machine Learning (PRML), IEEE international conference on

作者： Mingjing Lan Ningbo Huang Gang Zhou Yi Xia State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9798350355925

ISBN: (纸本)9798350355932

Graph few-shot learning aims to predict well by training with very few labeled data. Meta learning has been the most popular solution for few-shot learning problem. However, transductive linear probing shows that fine-tuning a simple linear classification head after a pretrained graph neural networks can outperforms most of the sophisticated-designed graph meta learning algorithms. Therefore, in the paper, we propose a meta transductive linear probing methods named Meta-TLP to incorporate the advantages of graph self-supervised and graph meta learning model. Specifically, the graph neural network is firstly pretrained with graph contrastive learning methods. Then we design an unsupervised meta training task construction methods to require meta tasks without relying on labeled data. Finally, we meta training the linear classification head on the meta training tasks to learn to fast adopt to novel classes. Experiment results show that our model can perform better than TLP on three real world datasets.

关键词： Training Metalearning Design methodology Data visualization Prediction algorithms Magnetic heads Data models Graph neural networks pattern recognition Few shot learning

来源：评论

学校读者我要写书评

暂无评论

6th international conference on Big Data Cloud and Internet of Things, BDIoT 2022

6th International Conference on Big Data Cloud and Internet ...

引用

6th international conference on Big Data Cloud and Internet of Things, BDIoT 2022

ISBN: (纸本)9783031283864

The proceedings contain 49 papers. The special focus in this conference is on Big Data Cloud and Internet of Things. The topics include: Knowledge Embeddings for Explainable Recommendation;Design of Blended Learning Course Based on SPOC for Primary School Teachers: Case of soft Skills;the Impact of the Online Flipped Classroom on the Learning Outcomes and Motivation of Nursing Students in Computer Science;digitizing Writing: An Empirical Exploratory Study Towards Students’ Writing Skill Fluency Improvement in ‘Padletosphere’;AraBERT with GANs for High Performance Fine-Grained Dialect Classification;genetic-Novelty Oversampling Technique for Imbalanced Data;neural Network for Arabic Text Diacritization on a New Dataset;processing Time Performance Analysis of Scheduling Algorithms for Virtual Machines Placement in Cloud computing Environment;Business - IT Alignment in Cloud Environment Comparative Study;machine Learning-Based Intrusion Detection System: Review and Taxonomy;reduce Cheating in e-Exams Using Machine Learning: State of the Art;comparative Study of Bayesian Optimization Process for the Best Machine Learning Hyperparameters;The Effect of Normalization and Batch Normalization Layers in CNNs Models: Application to Plant Disease Classifications;the Role of Ground Truth Annotation in Semantic Image Segmentation Performance for Autonomous Driving;fine-Tuning Pre-trained Vision Transformer Model for Anomaly Detection in Video Sequences;An Efficient Real-Time Moroccan Automatic License Plate recognition System Based on the YOLO Object Detector;evaluation of Selected Machine Learning Models and Features for Electrical Consumption Prediction in Educational Institutions;Credit Card Fraud Detection Using SVM, Decision Tree and Random Forest Supervised Machine Learning Algorithms;SNDAE: Self-Normalizing Deep AutoEncoder for Recommendation;Intelligent Evaluation System Using NLP;retrospective Study and Evaluation of School Failure (Junior High School) in Scientific Subj

关键词：

来源：评论

学校读者我要写书评

暂无评论

Shear Stress Estimation in Compound Channel Using M5 Tree and XGBoost soft computing Techniques 28th

Shear Stress Estimation in Compound Channel Using M5 Tree an...

引用

28th international conference on Hydraulics, Water Resources, River and Coastal Engineering, HYDRO 2023

作者： Tripathi, Neil Sandilya, Shashank Shekhar Das, Bhabani Shankar Devi, Kamalini Khuntia, Jnana Ranjan NIT Patna Patna800005 India CBIT Hyderabad Hyderabad India NIT Warangal Warangal India

ISBN: (纸本)9789819780341

Compound channels, commonly found in natural river systems, typically consist of a main channel alongside one or two floodplains. In prismatic compound channels, water levels remain uniform, whereas non-prismatic ones exhibit a more complex and non-uniform flow pattern. The interaction between the main channel and floodplain generates shear stresses due to momentum transfer, but predicting their distribution along the boundary is challenging as it depends on various factors like velocity distribution, cross-section shape, and boundary roughness. This study aims to develop a model to predict shear stress in non-prismatic compound channels using two machine learning (ML) techniques: M5 tree and extreme gradient boosting (XGBoost). It considers geometric, flow, and roughness parameters such as width ratio, relative flow depth, flow aspect ratio, and bed slope. M5 tree offers transparent formulas that enhance understanding, while XGBoost, known for handling structured data well, is a powerful gradient-boosting algorithm. Both models utilize correlated physical channel characteristic variables to predict shear stress. The predictions from both M5 tree and XGBoost models demonstrate satisfactory performance, with coefficients of determination (R2) exceeding 0.85 and mean absolute percentage errors (MAPE) below 12% for both training and testing datasets. However, the XGBoost model generally outperforms the M5 tree model in predicting shear stress across different sections of non-prismatic compound channels. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Shear stress

来源：评论

学校读者我要写书评

暂无评论

A Novel Duo-Stage driven Deep Neural Network Approach for Mitigating Electrode Shift Impact on Myoelectric pattern recognition Systems

A Novel Duo-Stage driven Deep Neural Network Approach for Mi...

引用

2023 IEEE international Symposium on Medical Measurements and Applications, MeMeA 2023

作者： Kulwa, Frank Samuel, Oluwarotimi Williams Asogbon, Mojisola Grace Oyemakinde, Tolulope Tofunmi Obe, Olumide Olayinka Li, Guanglin Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems SIAT-CAS China University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Guangdong Shenzhen518055 China University of Derby School of Computing and Engineering DerbyDE22 3AW United Kingdom Federal University of Technology Department of Computer Science Akure Nigeria

ISBN: (纸本)9781665493840

A major barrier to the commercialization of pattern recognition (PR)-based myoelectric prostheses is the lack of robustness to confounding factors such as electrode shift which has been lingering for years. To overcome this challenge, a novel Duo-Stage Convolutional Neural Network (DS-CNN) is proposed. The DS-CNN is comprised of two cascaded stages in which the first stage deciphers the occurrence of a particular kind of shift upon which a requisite CNN model is triggered in the second stage for accurate decoding of individual motion intent, which is necessary for initiating robust control of the prostheses. The proposed scheme works on raw EMG signals as input which reduces the preprocessing time that would be required in conventional machine learning-based PR schemes, to effectively mitigate both transverse and longitudinal shifts using the same network architecture. This approach was validated for four distinct electrode shift conditions (with shifts in the range of 7.50mm-10.05mm) in a dataset obtained from 18 able-bodied subjects that performed 8 classes of targeted hand gestures. The experimental results show that the proposed dual-stage driven deep neural network model can adequately resolve the effects of electrode shift with classification accuracy near the No-shift scenario ( © 2023 IEEE.

关键词： Electrodes

来源：评论

学校读者我要写书评

暂无评论

Predicting Time Series with Adjusting Feature Weight: An Integrated Method Based on Large Language Models and SHAP

Predicting Time Series with Adjusting Feature Weight: An Int...

引用

Machine Learning and Natural Language Processing (MLNLP), international conference on

作者： Fang Keyuan Corey Kewei Xu IPE Society Hub The Hong Kong University of Science and Technology(Guangzhou) Guangzhou China

ISBN: (数字)9798350354973

ISBN: (纸本)9798350354980

Social computing, an emerging interdisciplinary field, is centered on understanding and predicting human social behaviors and their patterns. Despite the important role of time series prediction in social computing, existing model-driven approaches often ignore the significant impact that data feature weights can have on time series prediction tasks. This limitation leads to many predictive models performing well on standard test data but failing to achieve the expected accuracy on real-world social computing data. Recent studies have shown that Large Language Models (LLMs) possess strong pattern recognition and reasoning capabilities for sequences. However, effectively applying their amazing text reasoning abilities to social computing and time series forecasting remains challenging. To solve these two significant research gaps, this study proposes an innovative time series forecasting model based on LLMs and SHAP. This model is an adaptive multimodal supervised learning framework that can both combine time series data with token embedding data and dynamically adjust feature weights after a few training iterations to recognize the feature patterns hidden behind real-world data. By the proposed model structure, this model can focus on features with the greatest influence on the prediction results, hence improving prediction performance with stability and promoting LLMs' application in time series prediction related to social computing. Besides conventional performance testing, this study also proposes an evaluation indicator for measuring the feature weight adjustment effect of time series models. This effectively enriches model evaluation dimensions and allows for diversified evaluation of time series models.

关键词： Adaptation models Social computing Computational modeling Large language models Time series analysis Supervised learning Predictive models Data models pattern recognition Forecasting

来源：评论

学校读者我要写书评

暂无评论

The RSDS: A Current State and Future Plans

The RSDS: A Current State and Future Plans

引用

international Joint conference on Rough Sets (IJCRS)

作者： Suraj, Zbigniew Grochowalski, Piotr Rzeszow Univ Inst Comp Sci Rzeszow Rzeszow Poland

ISBN: (纸本)9783030873349;9783030873332

This paper provides a brief overview of the Rough Set Database System (the RSDS for short) for creating bibliographies on rough sets and related fields, as well as sharing and analysis. The current version of the RSDS includes a number of modifications, extensions and functional improvements compared to the previous versions of this system. The system was made in the client-server technology. Currently, the RSDS contains over 38 540 entries from nearly 42 860 authors. This system works on any computer connected to the Internet and is available at http://***.

关键词： Rough set soft computing Ontology Data mining Knowledge discovery pattern recognition Machine learning Database system

来源：评论

学校读者我要写书评

暂无评论

Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks

Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Netw...

引用

Quantum computing and Engineering (QCE), IEEE international conference on

作者： Nico Meyer Christian Ufrecht Maniraman Periyasamy Axel Plinge Christopher Mutschler Daniel D. Scherer Andreas Maier Fraunhofer IIS Fraunhofer Institute for Integrated Circuits IIS Nürnberg Germany Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Quantum computer simulation software is an integral tool for the research efforts in the quantum computing community. An important aspect is the efficiency of respective frameworks, especially for training variational quantum algorithms. Focusing on the widely used Qiskit software environment, we develop the qiskit-torch-module. It improves runtime performance by two orders of magnitude over comparable libraries, while facilitating low-overhead integration with existing code-bases. Moreover, the framework provides advanced tools for integrating quantum neural networks with PyTorch. The pipeline is tailored for single-machine compute systems, which constitute a widely employed setup in day-to-day research efforts.

关键词： Training Quantum computing Runtime Quantum algorithm Computer simulation Neural networks Pipelines Focusing software Libraries

来源：评论

学校读者我要写书评

暂无评论

Robotics Process Automation Technologies for Data Collection and Analysis

Robotics Process Automation Technologies for Data Collection...

引用

international conference on computing and Networking Technology (ICCNT)

作者： K Usman Tm Hayath Mohammed Shafiulla Dadapeer Dept. of Computer Science and Engineering Ballari Institute of Technology and Management Ballari Karnataka India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Data collection and analysis are critical aspects of various business processes. However, these tasks can be time-consuming, prone to errors, and delays employee productivity when done manually, especially when we have to deal with huge data. Robotic Process Automation (RPA) technologies offer a promising solution in form of a BOT, by automating tedious tasks related with data handling. A survey by The Economist corporation believe that automation kick launches digital transformation, robotic process automation (RPA) has evolved from an emerging technology to a must-have digital transformation tool for enterprises to compete globally. An increasing number of companies are now using RPA to automate normal business processes in a non-intrusive and cost-effective way. On the other hand, decision-making, pattern recognition, and many other business-related tasks benefit greatly from the use of big data and analytics. This paper explores the application of RPA in data collection and analysis, examining its functionalities, benefits, and limitations. In practical, Bot produces error-free work and takes 94.44% less time for data collection compared to a manual process, which encourages all firms to adopt to RPA technologies.

关键词： Intelligent automation Surveys Productivity Digital transformation Decision making Manuals Chatbots pattern recognition Delays Business

来源：评论

学校读者我要写书评

暂无评论

Gait pattern recognition via Fusing Static and Dynamic Features in Single Stream Network

Gait Pattern Recognition via Fusing Static and Dynamic Featu...

引用

international conference on computing and Networking Technology (ICCNT)

作者： Isha Jain Navya Dharini Reddy Vijay Kumar Pandey Tushar Sandhan EE PIL IIT-K Kanpur INDIA

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Gait refers to the walking and motion characteristics of an individual. In this paper, we suggest a unique method for analyzing human gait patterns using static as well as dynamic features passing through the same convolutional neural network. Generally, the gaits are processed using contour detection and segmentation to perform time series analysis with extracted features. Furthermore, machine learning models such as decision trees, support vector machine are also utilized for the gait classification. We initially trained our model on both cropped average images and optical flow of each gait independently. Subsequently, we fused the average image of each gait (building static information) with its corresponding optical flow (dynamic information). This novel fusion approach facilitated the training of a single stream convolutional neural network model. Our findings reveal a notable accuracy of ${9 8. 7 5 \%}$ in successfully recognizing individuals based on their gait patterns. Simplicity of the model and succinct fusion of static and dynamic features produce improved results with very less computational time.

关键词： Training Support vector machines Computational modeling Motion segmentation Time series analysis Streaming media Feature extraction pattern recognition Convolutional neural networks Optical flow

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 << < 57 58 59 60 61 62 63 64 65 66 > >>

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：