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

620 篇 期刊文献
569 篇 会议

馆藏范围

1,189 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

798 篇 工学
- 590 篇 计算机科学与技术...
- 485 篇 软件工程
- 163 篇 信息与通信工程
- 139 篇 生物工程
- 84 篇 电气工程
- 81 篇 控制科学与工程
- 80 篇 生物医学工程（可授...
- 67 篇 电子科学与技术（可...
- 66 篇 光学工程
- 54 篇 化学工程与技术
- 44 篇 机械工程
- 31 篇 动力工程及工程热...
- 26 篇 交通运输工程
- 23 篇 建筑学
- 23 篇 土木工程
- 21 篇 材料科学与工程（可...
- 16 篇 仪器科学与技术
428 篇 理学
- 206 篇 数学
- 151 篇 生物学
- 102 篇 物理学
- 59 篇 化学
- 59 篇 统计学（可授理学、...
- 32 篇 系统科学
202 篇 管理学
- 108 篇 图书情报与档案管...
- 107 篇 管理科学与工程(可...
- 31 篇 工商管理
62 篇 医学
- 57 篇 临床医学
- 44 篇 基础医学(可授医学...
- 33 篇 药学(可授医学、理...
35 篇 法学
- 28 篇 社会学
18 篇 农学
14 篇 经济学
5 篇 教育学
4 篇 文学
1 篇 军事学
1 篇 艺术学

主题

37 篇 semantics
30 篇 deep learning
28 篇 training
26 篇 feature extracti...
23 篇 machine learning
22 篇 computational mo...
20 篇 task analysis
18 篇 data mining
17 篇 conferences
17 篇 graph neural net...
16 篇 memory managemen...
15 篇 deep neural netw...
15 篇 forecasting
14 篇 object detection
14 篇 neural networks
14 篇 data models
13 篇 convolution
13 篇 accuracy
11 篇 recommender syst...
11 篇 contrastive lear...

机构

100 篇 national enginee...
53 篇 school of comput...
50 篇 school of cyber ...
38 篇 school of comput...
34 篇 national enginee...
31 篇 hubei engineerin...
29 篇 services computi...
27 篇 cluster and grid...
26 篇 huazhong univers...
26 篇 hubei key labora...
26 篇 zhejiang lab
21 篇 school of comput...
20 篇 school of mathem...
19 篇 school of softwa...
18 篇 national enginee...
17 篇 national univers...
17 篇 smart health big...
16 篇 university of sc...
16 篇 fujian provincia...
16 篇 school of inform...

作者

121 篇 jin hai
118 篇 hai jin
42 篇 xiaofei liao
27 篇 liao xiaofei
26 篇 chen enhong
25 篇 liu jun
23 篇 liu qi
23 篇 hu shengshan
21 篇 haikun liu
19 篇 long zheng
17 篇 zou deqing
16 篇 zhang leo yu
15 篇 deqing zou
15 篇 pan jeng-shyang
15 篇 yu zhang
14 篇 wang meng
14 篇 yu huang
13 篇 jiang xiao
13 篇 li chen
13 篇 li minghui

语言

1,122 篇 英文
57 篇 其他
11 篇 中文

检索条件"机构=Anhui Engineering Lab of Big Data Technology"

共 1189 条记录，以下是241-250 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：

CoCGAN: Contrastive Learning for Adversarial Category Text Generation 29

CoCGAN: Contrastive Learning for Adversarial Category Text G...

引用

29th International Conference on Computational Linguistics, COLING 2022

作者： Sheng, Xin Xu, Linli Xu, Yinlong Bao, Changcun Chen, Huang Ren, Bo Anhui Province Key Laboratory of Big Data Analysis and Application School of Computer Science and Technology University of Science and Technology of China China School of Computer Science and Technology University of Science and Technology of China China State Key Laboratory of Cognitive Intelligence China Tencent Youtu Lab China

The task of generating texts of different categories has attracted more and more attention in the area of natural language generation recently. Meanwhile, generative adversarial net (GAN) has demonstrated its effectiveness on text generation, and is further applied to category text generation in later works. Different from existing methods, which mainly consider the pairwise relations between the text embedding and the corresponding fixed one-hot class label (data-to-class relations), this paper proposes a novel Contrastive Category Generative Adversarial Net (CoCGAN) to incorporate contrastive learning into adversarial category text generation, considering more flexible data-to-class relations as well as relations between the multiple text embeddings in the same batch (data-to-data relations). The discriminator of CoCGAN discriminates the authenticity of given samples and optimizes a contrastive learning objective to capture both more flexible data-to-class relations and data-to-data relations among training samples. Accordingly, the generator tries to produce more realistic samples which can confuse the discriminator. Experimental results on both synthetic and real category text generation datasets demonstrate that CoCGAN can achieve significant improvements over the baseline category text generation models. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Development and Implementation of Automatic Trolley System for Disabled, Aged and Nursing using Arduino

Development and Implementation of Automatic Trolley System f...

引用

2022 IEEE Delhi Section Conference, DELCON 2022

作者： Tetteh, Akiti Kenneth Agordzo, George K. Bright, Amenya Tochukwu, Nwodom Eric-Theophilus Al-Omari, Abdullah Mma Yeboah, Derrick School of Automation Zhejiang University of Science and Technology Hangzhou China School of Big Data and Mathematics Anhui University of Science and Technology Huainan China School of Information Engineering Huzhou University Huzhou China College of Overseas Education Chengdu University Chengdu China

ISBN: (纸本)9781665458832

Every day in different countries, shopping is carried out by every category of persons. Currently, people going shopping have to push around trolleys loaded with a lot of merchandise and this is so stressful and difficult to push around. We aim to solve the current problem stated above and also ease mobility during shopping as customers such as nursing mothers with more than one child to take care of find it stressful to shop. To overcome this, we plan on automating the current trolley system by controlling the robotic trolley with hand gestures. The transmission device interfaces with an Arduino ATMEGA microcontroller, which receives signals and propels the robot based on its user's hand gesture. It reduces the stress of pushing around a shopping cart and can be controlled by hand gestures. © 2022 IEEE.

关键词： Nursing

来源：评论

学校读者我要写书评

暂无评论

Super-Resolution of Diffusion-Weighted Images via TDI-Conditioned Diffusion Model 15th

Super-Resolution of Diffusion-Weighted Images via TDI-Cond...

引用

15th International Workshop on Computational Diffusion MRI, CDMRI 2024, held in conjunction with 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024

作者： Ma, Jiquan Teng, Yujun Chen, Geng Jiang, Haotian Zhang, Kai Liu, Feihong Rekik, Islem Shen, Dinggang School of Computer Science and Technology Heilongjiang University Harbin China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University Shanghai China School of Information Science and Technology Northwest University Xi’an China BASIRA Lab Imperial-X and Department of Computing Imperial College London London United Kingdom

ISBN: (纸本)9783031869198

Diffusion-Weighted Imaging (DWI) is a significant technique for studying white matter. However, it suffers from low-resolution obstacles in clinical settings. Post-acquisition Super-Resolution (SR) can enhance the resolution of DWIs and has gained increasing research interest in recent years. An advanced generative model, the Diffusion Model (DM), exhibits particularly promising performance in image SR. However, effective conditions are required to bootstrap the DM for DWI SR. To this end, we proposed the first DM-based DWI SR model with two effective conditions based on low-solution DWIs and Track Density Imaging (TDI) maps, which possess rich high-resolution prior knowledge Additionally, we consider another condition based on features from low-resolution DWIs. These two conditions are integrated into our model, which comprises three components: DWI Resolution Enhancer (DRE), DWI Feature Extractor (DFE), and TDI Feature Extractor (TFE). DRE combines low-resolution DWI features from DFE with TDI features from TFE to progressively generate high-resolution DWIs. We performed extensive experiments on DWIs of normal subjects from human connectome projects and patients with Parkinson’s disease. The results demonstrate that our model outperforms existing DWI SR models, both qualitatively and quantitatively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Model Combined with SVM and CNN for Community Content Classification 23

A Hybrid Model Combined with SVM and CNN for Community Conte...

引用

23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and big data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Ye, Yukui Xie, Xia Jin, Hai Wang, Duoqiang National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and Technology Services Computing Technology and System Lab Cluster and Grid Computing Lab Wuhan China School of Computer Science and Technology Hainan University Haikou China

ISBN: (纸本)9781665494571

Community websites bring many conveniences to people, and the classification of community content is playing an important role in website management and information searching. As the carrier of community content, posts are difficult to classify manually. According to the characteristics of community content, a hybrid classification model for machine learning is proposed. This model consists of three steps. Firstly, aiming at the problem of fewer features of posts, a weighted word vector is proposed to enrich the features of posts. Secondly, since the single kernel function of SVM can not completely match all data distributions, a mixed kernel function is employed to improve the model. Finally, in order to fully utilize the powerful feature extraction ability of Convolutional Neural Network as well as the classification ability of SVM, a hybrid model is designed and implemented by replacing softmax layer with SVM classifier. The corresponding experiment results indicate that compared with traditional Convolutional Neural Network, the proposed hybrid model has better performance and stability with classification accuracy improved from 0.9% to 1.4% in general. © 2021 IEEE.

关键词： Support vector machines Smart cities Support vector machine classification Machine learning Feature extraction Stability analysis data models

来源：评论

学校读者我要写书评

暂无评论

UniMoCo: Unsupervised, Semi-Supervised and Fully-Supervised Visual Representation Learning

UniMoCo: Unsupervised, Semi-Supervised and Fully-Supervised ...

引用

2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Dai, Zhigang Cai, Bolun Chen, Junying South China University of Technology Key Lab. of Big Data & Intell. Robot MoE School of Software Engineering Guangzhou China Tencent Wechat Ai Guangzhou China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Momentum Contrast (MoCo) achieves great success for unsupervised visual representation learning. However, there are a lot of supervised and semi-supervised datasets, which are already labeled. To fully utilize the label annotations, we propose Unified Momentum Contrast (UniMoCo), which extends MoCo to support arbitrary ratios of labeled data and unlabeled data training. Compared with MoCo, UniMoCo has two modifications as follows: (1) Different from a single positive pair in MoCo, we maintain multiple positive pairs on-the-fly by comparing the query label to a label queue. (2) We propose a Unified Contrastive (UniCon) loss to support an arbitrary number of positives and negatives in a unified pair-wise optimization perspective. Our UniCon is more reasonable and powerful than the supervised contrastive loss in theory and practice. In our experiments, we pre-train multiple UniMoCo models with different ratios of ImageNet labels and evaluate the performance on various downstream tasks. Experiment results show that UniMoCo generalizes well for unsupervised, semi-supervised and fully-supervised visual representation learning. Besides, we surprisingly find that UniMoCo performs best with 60% ImageNet labels for COCO and VOC transfer learning. The code is available: https://***/dddzg/unimoco. © 2022 IEEE.

关键词： Momentum

来源：评论

学校读者我要写书评

暂无评论

Research on emotion recognition of eye movement in realistic environment 8

Research on emotion recognition of eye movement in realistic...

引用

8th International Conference on Electronic technology and Information Science, ICETIS 2023

作者： Hong, Changdi Wang, Jinlan Wang, Yuanxu Ning, Tao Song, Jinmiao Duan, Xiaodong SEAC key Laboratory of Big Data Applied Technology Dalian Minzu University Dalian116000 China Dalian Key Lab of Digital Technology for National Culture Dalian Minzu University Dalian116600 China College of Computer Science and Engineering Dalian Minzu University Dalian116600 China

ISBN: (纸本)9781510666535

Eye tracking technology can show how people focus their attention and emotionally react to their surroundings. In this study, wearable eye tracker was used to conduct eye movement experiments in realistic environment. For signal processing of the data, a finite impulse response (FIR) filter was chosen, and an eye movement data set was created. First, 26 features were chosen by a machine learning algorithm for emotion recognition, and the average rate of recognition on GDBT was 71.1%. 22 noteworthy correlation features were chosen after Spearman and emotion state were used for correlation analysis. GDBT has a recognition rate of 74.61%, while XGBoost has a recognition rate of 75.63%. The experimental results prove the validity of our data set and provide data support for the next research. © 2023 SPIE.

关键词： FIR filters

来源：评论

学校读者我要写书评

暂无评论

Cooperative Relationship Prediction between Scholars in Heterogeneous Academic Network 23

Cooperative Relationship Prediction between Scholars in Hete...

引用

作者： Shi, Jia Jin, Hai Xie, Xia National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and Technology Services Computing Technology and System Lab Cluster and Grid Computing Lab Wuhan China School of Computer Science and Technology Hainan University Haikou China

ISBN: (纸本)9781665494571

The real academic network belongs to a heterogeneous network, therefore, for the link prediction tasks, some information on the network may be lost if only using homogeneous network methods. In order to make good use of the rich semantic information in a heterogeneous network for better predicting the cooperative relationship between scholars, this paper proposes a cooperative relationship prediction (CoRP) model. The CoRP model includes the following three steps. Firstly, a structural feature extraction module is designed based on meta path by using the similarity metric function to measure the meta path similarity between scholars. Secondly, to overcome the defects that the existing methods usually ignore the attribute information on nodes, three attribute feature presentation functions are constructed to fully utilize the attribute information of scholars in the academic network. In the end, a machine learning classifier which combines the structural similarity and attribute similarity is utilized to learn each attribute feature and complete the task of cooperative relationship prediction. The experimental results reveal that compared with the benchmark method, the proposed method has better performance and interpretability with improvement from 3% to 10% of AUC value for the AMiner academic data set. © 2021 IEEE.

关键词： Measurement Smart cities Semantics Machine learning Benchmark testing Predictive models Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Mitigating label-Noise for Facial Expression Recognition in the Wild

Mitigating Label-Noise for Facial Expression Recognition in ...

引用

2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Yan, Huan Gu, Yu Zhang, Xiang Wang, Yantong Ji, Yusheng Ren, Fuji School of Computer and Information Hefei University of Technology S2AC Lab China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data China Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation China National Institute of Informatics Tokushima University Japan

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

label-noise constitutes a major challenge for facial expression recognition in the wild due to the ambiguity of facial expressions worsened by low-quality images. To deal with this problem, we propose a simple but effective label-noise Robust Network (LRN) which explores the inter-class correlations for mitigating ambiguity that usually happens between morphologically similar classes. Specifically, LRN leverages a multivariate normal distribution to model such correlations at the final hidden layer of the neural network to suppress the heteroscedastic uncertainty caused by inter-class label noise. Furthermore, LRN utilizes a confidence-based label-free loss to extract compact intra-class feature representations under label noise while preserving the intrinsic inter-class relationships. Experiments on three in-the-wild facial expression datasets demonstrates the superiority of our method. © 2022 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Football player identification based on YOLOv5 backbone and SPD-Conv 8

Football player identification based on YOLOv5 backbone and ...

引用

8th International Conference on Electronic technology and Information Science, ICETIS 2023

作者： Liu, Jiwei Li, Yanchao Ning, Tao Song, Jinmiao Duan, Xiaodong SEAC key Laboratory of Big Data Applied Technology Dalian Minzu University Dalian116000 China Dalian Key Lab of Digital Technology for National Culture Dalian Minzu University Dalian116600 China College of Computer Science and Engineering Dalian Minzu University Dalian116600 China

ISBN: (纸本)9781510666535

With the rapid development of computer technology and Internet technology, the information age has come. The combination of computer technology and sports is one of the most popular research fields. This paper mainly completes the construction of football player number dataset and identification of football players through the jersey number. Firstly, the dataset is constructed based on player detection and number region detection. Then in the player identification task, we uses part of the backbone network of YOLOv5 model as the feature extraction module of the player identification network. Moreover, SPD-Conv module is added to improve the network recognition performance under the condition of small size target and low resolution. A series of experiments were also done to verify the performance of our proposed model. Finally, the recognition accuracy of our proposed model reached 92.75%. © 2023 SPIE.

关键词： Sports

来源：评论

学校读者我要写书评

暂无评论

Text-Video Completion Networks With Motion Compensation And Attention Aggregation

Text-Video Completion Networks With Motion Compensation And ...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jianan Wang Zhiliang Wu Hanyu Xuan Yan Yan School of Computer Science and Engineering Nanjing University of Science and Technology China CCAI Zhejiang University China School of Big Data and Statistics Anhui University China Department of Computer Science Illinois Institute of Technology USA

The purpose of video inpainting is to fill a specified area with reasonable content. However, in the case of multiple targets and complex textures, current methods struggle to distinguish between feature information of the targets, leading to confusing or fuzzy inpainting results. In this paper, we design a new text-video completion network based on a motion compensation and temporal attention feature aggregation. Our network utilizes information from reference frames and target frames to complete the damaged region of the target frame. We first employ motion compensation to align the features of reference frames, and then use the temporal attention module to aggregate these features, resulting in accurate and reasonable content. To evaluate the effectiveness of our method, we introduce a new text video dataset with multiple text objects and complex textures, presenting a novel and challenging task for inpainting research. Through quantitative and qualitative comparison experiments, we demonstrate that our model outperforms existing baseline models in scenarios with multiple objects and complex textures.

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119页 << < 21 22 23 24 25 26 27 28 29 30 > >>

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：