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

5,634 篇 会议
90 篇 期刊文献
10 册 图书

馆藏范围

5,734 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,774 篇 工学
- 2,332 篇 计算机科学与技术...
- 1,329 篇 软件工程
- 567 篇 信息与通信工程
- 466 篇 电气工程
- 200 篇 生物工程
- 174 篇 控制科学与工程
- 174 篇 生物医学工程（可授...
- 109 篇 机械工程
- 84 篇 交通运输工程
- 83 篇 化学工程与技术
- 80 篇 电子科学与技术（可...
- 79 篇 光学工程
- 69 篇 仪器科学与技术
- 65 篇 动力工程及工程热...
- 55 篇 土木工程
- 55 篇 安全科学与工程
897 篇 理学
- 478 篇 数学
- 235 篇 生物学
- 231 篇 物理学
- 191 篇 统计学（可授理学、...
- 119 篇 系统科学
- 66 篇 化学
589 篇 管理学
- 327 篇 图书情报与档案管...
- 305 篇 管理科学与工程(可...
- 163 篇 工商管理
289 篇 医学
- 243 篇 临床医学
- 144 篇 基础医学(可授医学...
- 80 篇 药学(可授医学、理...
- 52 篇 公共卫生与预防医...
76 篇 法学
- 71 篇 社会学
54 篇 经济学
45 篇 教育学
39 篇 农学
26 篇 文学
2 篇 军事学
1 篇 历史学
1 篇 艺术学

主题

1,600 篇 data models
535 篇 predictive model...
530 篇 training
498 篇 machine learning
461 篇 data mining
416 篇 big data
405 篇 computational mo...
343 篇 feature extracti...
333 篇 task analysis
327 篇 prediction algor...
268 篇 deep learning
255 篇 machine learning...
245 篇 classification a...
238 篇 analytical model...
191 篇 clustering algor...
190 篇 support vector m...
183 篇 neural networks
158 篇 natural language...
142 篇 training data
141 篇 mathematical mod...

机构

19 篇 sun yat sen univ...
19 篇 daffodil interna...
12 篇 univ chinese aca...
11 篇 tsinghua univers...
11 篇 university of ch...
11 篇 school of data a...
10 篇 carnegie mellon ...
9 篇 renmin univ chin...
9 篇 lviv polytechnic...
8 篇 shenzhen researc...
7 篇 shanghai jiao to...
7 篇 college of compu...
7 篇 university of el...
7 篇 school of comput...
7 篇 national univers...
7 篇 harbin institute...
7 篇 beijing key lab ...
7 篇 natl univ def te...
7 篇 renmin univ chin...
6 篇 university of sc...

作者

7 篇 li li
7 篇 wang wei
7 篇 xiao yanghua
6 篇 wen ji-rong
6 篇 cui bin
6 篇 zhao wayne xin
6 篇 ying liu
6 篇 syed akhter hoss...
5 篇 yang tong
5 篇 liu yang
5 篇 li zhang
5 篇 jia weijia
5 篇 chen liu
5 篇 yang yang
5 篇 xiao hongbo
5 篇 nguyen trong-the
5 篇 yu jie
5 篇 albert bifet
5 篇 wang bin
5 篇 carlos ordonez

语言

5,596 篇 英文
130 篇 其他
14 篇 中文
2 篇 俄文
1 篇 乌克兰文

检索条件"任意字段=2020 International Conference on Data Processing Algorithms and Models, ICDPAM 2020"

共 5734 条记录，以下是721-730 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：

AWCD: An Efficient Point Cloud processing Approach via Wasserstein Curvature

AWCD: An Efficient Point Cloud Processing Approach via Wasse...

引用

2021 IEEE international conference on Artificial Intelligence and Computer Applications, ICAICA 2021

作者： Luo, Yihao Yang, Ailing Sun, Fupeng Sun, Huafei School of Mathematics and Statistics Beijing Institute of Technology Beijing China School of Statistics University of International Business and Economics Beijing China

ISBN: (纸本)9781665418676

In this paper, we introduce the adaptive Wasserstein curvature denoising (AWCD), an original processing approach for point cloud data. By collecting curvatures information from Wasserstein distance, AWCD consider more precise structures of data and preserves stability and effectiveness even for data with noise in high density. This paper contains some theoretical analysis about the Wasserstein curvature and the complete algorithm of AWCD. In addition, we design digital experiments to show the denoising effect of AWCD. According to comparison results, we present the advantages of AWCD against traditional algorithms. © 2021 IEEE.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

AN ATTENTION-SEQ2SEQ MODEL BASED ON CRNN ENCODING FOR AUTOMATIC LABANOTATION GENERATION FROM MOTION CAPTURE data

AN ATTENTION-SEQ2SEQ MODEL BASED ON CRNN ENCODING FOR AUTOMA...

引用

IEEE international conference on Acoustics, Speech and Signal processing (ICASSP)

作者： Li, Min Miao, Zhenjiang Zhang, Xiao-Ping Xu, Wanru Beijing Jiaotong Univ Inst Informat Sci Beijing Peoples R China Ryerson Univ Dept Elect Comp & Biomed Engn Toronto ON Canada

ISBN: (纸本)9781728176055

Labanotation is an important notation system widely used for recording dances. Numerous methods have been proposed for automatic Labanotation generation from motion capture data. Recently, the sequence-to-sequence (seq2seq) model is proposed. However, the encoder of the model only encodes the temporal information of motion data, lacking the encoding for spatial information. And it is challenging for the decoder to align input and output sequences due to the imbalance of the sequence lengths. In this paper, we propose an attention-seq2seq model based on Convolutional Recurrent Neural Network (CRNN). The proposed model employs an encoder based on CRNN to learn the spatial-temporal information of motion data and applies an attention mechanism to align each target Laban symbol with relevant parts of the input motion data in decoding. Experiments show that the proposed method performs favorably against state-of-the-art algorithms in the automatic Labanotation generation task.

关键词： Labanotation generation motion capture data seq2seq model CRNN attention

来源：评论

学校读者我要写书评

暂无评论

Learning the Optimal Energy Supply Plan with Online Convex Optimization

Learning the Optimal Energy Supply Plan with Online Convex O...

引用

IEEE international conference on Communications (ICC)

作者： Chadoulos, Spiros Koutsopoulos, Iordanis Athens Univ Econ & Business Dept Informat Athens Greece

ISBN: (纸本)9781728171227

In this paper, we propose an online learning approach, utilizing the framework of Online Convex Optimization (OCO) to tackle the problem of learning the optimal energy supply plan, in terms of total incurred cost, from the perspective of an electricity retailer that also owns power generators and renewable energy sources. The retailer does not have prior knowledge about key dynamic processes that affect the problem, such as future demand, renewable energy supply, and wholesale market prices. The retailer sequentially learns how to adjust the power generation plan so as to minimize the power generation cost plus the cost of buying additional power from the wholesale market, in case the planned generated amount is not enough to cover the demand. We use Online Mirror Descent (OMD) and Online Gradient Descent (OGD), and we verify that they both achieve sublinear static and dynamic regret, which compare the cumulative cost of each algorithm against that of the optimal offline static and dynamic solution respectively. In particular, dynamic regret appears to be well aligned with the considered setting since it captures the fact that a power generator can dynamically change its power output between consecutive time slots based on only small adjustments and not in an arbitrary fashion, due to ramp constraints. Our model can capture different settings of electricity markets. Simulations with real data verify that OMD precisely learns the optimal dynamic supply policy for small power adjustments between consecutive time slots.

关键词： Renewable energy sources Adaptation models Heuristic algorithms Generators data models Convex functions Smart grids

来源：评论

学校读者我要写书评

暂无评论

Informatization Strategies of Education and Teaching Management in the Era of Cloud Computing and Big data 2

Informatization Strategies of Education and Teaching Managem...

引用

2020 2nd international conference on Electronics and Communication, Network and Computer Technology, ECNCT 2020

作者： Xiaona, Ma Dalian Vocational and Technical College Dalian Radio and TV University 116035 China

In the era of cloud computing and big data, the integrated processing of information and data has become the trend of various industries. College education and teaching management should be actively innovated and optimized, change traditional models and methods, build education and teaching management system, and improve management level. Based on this, this article will analyze the importance of the informatization of education and teaching management in the era of cloud computing and big data, and propose ways to construct the informatization of education and teaching management to help the relevant. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Informatization

来源：评论

学校读者我要写书评

暂无评论

A Multi-Step Speed Prediction Method for Traffic Networks Based on MAF-GCN-Seq2Seq Model 2

A Multi-Step Speed Prediction Method for Traffic Networks Ba...

引用

2nd international conference on Electronic Information Technology and Smart Agriculture, ICEITSA 2022

作者： Long, Yi Xiao, Hongbo Xiao, Jianhua Peng, Xiaoning School of Computer Science and Engineering Huaihua University Hunan Huaihua418000 China Intelligent Processing and Application in Hunan Province Universities Key Laboratory of Wuling-Mountain Health Big Data Hunan Huaihua418000 China Key Lab. of Intelligent Contr. Technol. for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China

ISBN: (纸本)9781665464017

Accurately predicting the future trend of traffic flow is of great significance to the planning of urban traffic. The great challenge of predicting traffic flow stems from the complexity and uncertainty of traffic flow. To address the complexity of traffic flow, this paper proposes a MAF-GCN 2 Seq model. The model uses a moving average filter to filter the time series data, extracts the spatial features between each node through a graph convolutional neural network, and forms a time series matrix for input into the encoder (GRU), and introduces a self-attention mechanism to mine the spatial features. time-domain features for multi-step traffic speed prediction. In order to verify the advanced nature of the model, this paper uses the traffic flow data set in Shenzhen to predict the traffic flow. Through the comparison experiments, it can be seen that the prediction accuracy of the MAF-GCN 2 Seq model reaches 90%, which has obvious advantages compared with other models. © 2022 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Automatic Detection of Defective Tablets in Pharmaceutical Manufacturing 8th

Deep Learning-Based Automatic Detection of Defective Tablets...

引用

8th international conference on the Development of Biomedical Engineering, BME8 2020

作者： Quan, Huynh Thanh Huy, Dong Duc Hoan, Ngo Thanh Duc, Nguyen Thanh Department of Electrical Engineering and Information Technology Vietnamese German University Thu Dau Mot Viet Nam School of Biomedical Engineering International University Ho Chi Minh City Viet Nam Vietnam National University-Ho Chi Minh City Ho Chi Minh City Viet Nam Department of Biomedical Science and Engineering Integrated of Integrated Technology Gwangju Institute of Science and Technology Gwangju Korea Republic of Montreal Neurological Institute McGill University Montreal Canada

ISBN: (纸本)9783030755058

With many tablets produced everyday in manufacturing plants, the pharmaceutical industry needs automatic, highly accurate methods for inspection of tablet quality. Detecting defective tablets is of importance to reduce unqualified products to consumers. In this paper, we propose a deep learning method combining image processing and deep convolutional neural networks (DCNN) for detection of defective tablets using images captured by a multiple-camera inspection system. A dataset of 6000 images of tablets labelled either GOOD or NOT-GOOD were collected at a pharmaceutical factory using commercial camera inspection systems. After collecting and labelling, the images were preprocessed to normalize intensity values. The entire dataset was split into a training set (50%, 3000 images), a validation set (16.6%, 1000 images) and a testing set (33.3%, 2000 images). We trained DCNN ResNets (ResNet50, ResNet101) and DenseNets (DenseNet169, DenseNet201) models on the training set and validated them on the validation set. We applied transfer learning techniques by using pre-trained models that had been trained on the ImageNet dataset in combination with data augmentation and training strategies such as learning rate rescheduling overtime. We compared our deep learning methods with various machine-learning ones such as Support Vector Machine (SVM), K-Nearest-Neighbors (KNN), AdaBoost that used intensity histograms as features. Tuning hyperparameters were performed to seek the best hyper-parameters and algorithms. We achieved best performances using the deep learning models as the ResNet50, and DenseNet169 obtained 96.60% ± 4.9% and 94.13% ± 4.2% accuracies (ACC), respectively. In contrast, SVM achieved 87.75% ACC, KNN achieved 76.09% ± 7.7% ACC while AdaBoost achieved 81.25% ACC, respectively. © 2022, Springer Nature Switzerland AG.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Proof-of-Authority-and-Association Consensus Algorithm for IoT Blockchain Networks

Proof-of-Authority-and-Association Consensus Algorithm for I...

引用

2025 IEEE international conference on Consumer Electronics, ICCE 2025

作者： Kim, Dong-Seong Igboanusi, Ikechi Saviour Chijioke Ahakonye, Love Allen Anyanwu, Goodness Oluchi Kumoh National Institute of Technology Gumi Korea Republic of ICT Convergence Research Center NSLab Co. Ltd. Gumi Korea Republic of Kumoh National Institute of Technology Gumi Korea Republic of University of Calgary Canada

ISBN: (纸本)9798331521165

Blockchain networks must ensure secure and efficient consensus algorithms in consumer electronics and Internet of Things (IoT) devices. This paper proposes a novel consensus algorithm, "Proof-of-Authority-and-Association (PoA2)", designed specifically for IoT blockchain networks in consumer applications. PoA2 leverages redundancy-based mechanisms to enhance consensus efficiency and reliability, which is critical for real-time data processing and validation in IoT environments. The algorithm integrates proof of authority and association verification, ensuring network participants are authorized and associated with the transactions they validate. Combining these elements, PoA2 mitigates common challenges such as latency, scalability, and energy consumption often encountered in traditional consensus algorithms. Through simulations and performance evaluations, we demonstrate PoA2's effectiveness in achieving consensus while maintaining high levels of security and reducing computational overhead, making it suitable for resource-constrained IoT devices in consumer electronics applications. © 2025 IEEE.

关键词： data reduction

来源：评论

学校读者我要写书评

暂无评论

Federated Traffic Synthesizing and Classification Using Generative Adversarial Networks

Federated Traffic Synthesizing and Classification Using Gene...

引用

IEEE international conference on Communications (ICC)

作者： Xu, Chenxin Xia, Rong Xiao, Yong Li, Yingyu Shi, Guangming Chen, Kwang-cheng Huazhong Univ Sci & Technol Sch Elect Inform & Commun Wuhan Peoples R China Xidian Univ Sch Artificial Intelligence Xian Peoples R China Pazhou Lab Guangzhou Peoples R China Univ S Florida Dept Elect Engn Tampa FL 33620 USA

ISBN: (纸本)9781728171227

With the fast growing demand on new services and applications as well as the increasing awareness of data protection, traditional centralized traffic classification approaches are facing unprecedented challenges. This paper introduces a novel framework, Federated Generative Adversarial Networks and Automatic Classification (FGAN-AC), which integrates decentralized data synthesizing with traffic classification. FGAN-AC is able to synthesize and classify multiple types of service data traffic from decentralized local datasets without requiring a large volume of manually labeled dataset or causing any data leakage. Two types of data synthesizing approaches have been proposed and compared: computation-efficient FGAN (FGANI) and communication-efficient FGAN (FGAN-II). The former only implements a single CNN model for processing each local dataset and the later only requires coordination of intermediate model training parameters. An automatic data classification and model updating framework has been proposed to automatically identify unknown traffic from the synthesized data samples and create new pseudo-labels for model training. Numerical results show that our proposed framework has the ability to synthesize highly mixed service data traffic and can significantly improve the traffic classification performance compared to existing solutions.

关键词： Training Computational modeling conferences data protection Generative adversarial networks data models Numerical models

来源：评论

学校读者我要写书评

暂无评论

Learning to Socially Navigate in Pedestrian-rich Environments with Interaction Capacity 39

Learning to Socially Navigate in Pedestrian-rich Environment...

引用

IEEE international conference on Robotics and Automation (ICRA)

作者： Qiu, Quecheng Yao, Shunyi Wang, Jing Ma, Jun Chen, Guangda Ji, Jianmin Univ Sci & Technol China Sch Data Sci Hefei 230026 Peoples R China USTC Sch Comp Sci & Technol Hefei 230026 Peoples R China

ISBN: (纸本)9781728196817

Existing navigation policies for autonomous robots tend to focus on collision avoidance while ignoring human-robot interactions in social life. For instance, robots can pass along the corridor safer and easier if pedestrians notice them. Sounds have been considered as an efficient way to attract the attention of pedestrians, which can alleviate the freezing robot problem. In this work, we present a new deep reinforcement learning (DRL) based social navigation approach for autonomous robots to move in pedestrian-rich environments with interaction capacity. Most existing DRL based methods intend to train a general policy that outputs both navigation actions, i.e., expected robot's linear and angular velocities, and interaction actions, i.e., the beep action, in the context of reinforcement learning. Different from these methods, we intend to train the policy via both supervised learning and reinforcement learning. In specific, we first train an interaction policy in the context of supervised learning, which provides a better understanding of the social situation, then we use this interaction policy to train the navigation policy via multiple reinforcement learning algorithms. We evaluate our approach in various simulation environments and compare it to other methods. The experimental results show that our approach outperforms others in terms of the success rate. We also deploy the trained policy on a real-world robot, which shows a nice performance in crowded environments.

关键词： Adaptation models Automation Navigation Supervised learning Human-robot interaction Reinforcement learning Angular velocity

来源：评论

学校读者我要写书评

暂无评论

CSR++: A Fast, Scalable, Update-Friendly Graph data Structure 24

CSR++: A Fast, Scalable, Update-Friendly Graph Data Structur...

引用

24th international conference on Principles of Distributed Systems, OPODIS 2020

作者： Firmli, Soukaina Lozi, Jean-Pierre Weld, Alexander Hong, Sungpack Trigonakis, Vasileios Psaroudakis, Iraklis Chiadmi, Dalila Chafi, Hassan Sip Research Team Mohammed v University in Rabat Ecole Mohammadia d'Ingnieurs Casablanca Morocco Oracle Labs Zürich Switzerland Oracle Labs Palo AltoCA United States

ISBN: (纸本)9783959771764

The graph model enables a broad range of analysis, thus graph processing is an invaluable tool in data analytics. At the heart of every graph-processing system lies a concurrent graph data structure storing the graph. Such a data structure needs to be highly efficient for both graph algorithms and queries. Due to the continuous evolution, the sparsity, and the scale-free nature of real-world graphs, graph-processing systems face the challenge of providing an appropriate graph data structure that enables both fast analytical workloads and low-memory graph mutations. Existing graph structures offer a hard trade-off between read-only performance, update friendliness, and memory consumption upon updates. In this paper, we introduce csr++, a new graph data structure that removes these trade-offs and enables both fast read-only analytics and quick and memory-friendly mutations. csr++ combines ideas from CSR, the fastest read-only data structure, and adjacency lists to achieve the best of both worlds. We compare csr++ to CSR, adjacency lists from the Boost Graph Library, and LLAMA, a state-of-the-art update-friendly graph structure. In our evaluation, which is based on popular graph-processing algorithms executed over real-world graphs, we show that csr++ remains close to CSR in read-only concurrent performance (within 10% on average), while significantly outperforming CSR (by an order of magnitude) and LLAMA (by almost 2×) with frequent updates. © Soukaina Firmli, Vasileios Trigonakis, Jean-Pierre Lozi, Iraklis Psaroudakis, Alexander Weld, Dalila Chiadmi, Sungpack Hong, and Hassan Chafi;licensed under Creative Commons License CC-BY 24th international conference on Principles of Distributed Systems (OPODIS 2020).

关键词： data structures

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 << < 69 70 71 72 73 74 75 76 77 78 > >>

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：