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

5,626 篇 会议
90 篇 期刊文献
10 册 图书

馆藏范围

5,726 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,768 篇 工学
- 2,326 篇 计算机科学与技术...
- 1,325 篇 软件工程
- 565 篇 信息与通信工程
- 466 篇 电气工程
- 200 篇 生物工程
- 175 篇 控制科学与工程
- 174 篇 生物医学工程（可授...
- 108 篇 机械工程
- 84 篇 交通运输工程
- 83 篇 化学工程与技术
- 81 篇 电子科学与技术（可...
- 79 篇 光学工程
- 70 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
- 52 篇 环境科学与工程（可...
898 篇 理学
- 477 篇 数学
- 235 篇 生物学
- 232 篇 物理学
- 191 篇 统计学（可授理学、...
- 119 篇 系统科学
- 67 篇 化学
588 篇 管理学
- 325 篇 图书情报与档案管...
- 306 篇 管理科学与工程(可...
- 163 篇 工商管理
290 篇 医学
- 244 篇 临床医学
- 144 篇 基础医学(可授医学...
- 80 篇 药学(可授医学、理...
76 篇 法学
- 71 篇 社会学
54 篇 经济学
45 篇 教育学
40 篇 农学
26 篇 文学
2 篇 军事学
1 篇 历史学
1 篇 艺术学

主题

1,599 篇 data models
534 篇 predictive model...
529 篇 training
498 篇 machine learning
461 篇 data mining
416 篇 big data
404 篇 computational mo...
343 篇 feature extracti...
333 篇 task analysis
326 篇 prediction algor...
267 篇 deep learning
255 篇 machine learning...
245 篇 classification a...
238 篇 analytical model...
191 篇 clustering algor...
190 篇 support vector m...
182 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

5,682 篇 英文
36 篇 其他
9 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 5726 条记录，以下是4731-4740 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：

Prediction of NMF-based Wiener Filter for Speech Enhancement Using Deep Neural Networks

Prediction of NMF-based Wiener Filter for Speech Enhancement...

引用

IEEE international conference on Signal processing, Communications and Computing (ICSPCC)

作者： Zhigang Bai Changchun Bao Zihao Cui Speech and Audio Signal Processing Lab Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (数字)9781728172026

ISBN: (纸本)9781728172033

In this paper, a novel approach is presented to predict a training target called NMF-based Wiener filter using deep neural networks (DNN) in the nonnegative matrix factorization (NMF) based speech enhancement. The NMF-based Wiener filter, as a masking-based target, is easier than the encoding vectors used in previous algorithms for parameter estimation. The intermediate error of the NMF-based speech enhancement process was reduced due to direct prediction of the NMF-based Wiener filter. The encoding vectors of noisy speech were extracted with the NMF algorithm and normalized to obtain more discriminative input features. The DNN was trained to learn a nonlinear mapping from the encoding vector of noisy speech to the NMF-based Wiener filter. At test stage, the predicted NMF-based Wiener filter was used to enhance noisy speech. The objective evaluations demonstrated that the proposed algorithm outperforms some existing NMF-based and DNN-based methods at various input signal-to-noise ratio (SNR) levels.

关键词： Speech enhancement Noise measurement Wiener filters Encoding Training Feature extraction Training data

来源：评论

学校读者我要写书评

暂无评论

Merchant Category Identification Using Credit Card Transactions

Merchant Category Identification Using Credit Card Transacti...

引用

IEEE international conference on Big data

作者： Chin-Chia Michael Yeh Zhongfang Zhuang Yan Zheng Liang Wang Junpeng Wang Wei Zhang Visa Research

ISBN: (数字)9781728162515

ISBN: (纸本)9781728162522

Digital payment volume has proliferated in recent years with the rapid growth of small businesses and online shops. When processing these digital transactions, recognizing each merchant's real identity (i.e., business type) is vital to ensure the integrity of payment processing systems. Conventionally, this problem is formulated as a time series classification problem solely using the merchant transaction history. However, with the large scale of the data, and changing behaviors of merchants and consumers over time, it is extremely challenging to achieve satisfying performance from off-the-shelf classification methods. In this work, we approach this problem from a multi-modal learning perspective, where we use not only the merchant time series data but also the information of merchant-merchant relationship (i.e., affinity) to verify the self-reported business type (i.e., merchant category) of a given merchant. Specifically, we design two individual encoders, where one is responsible for encoding temporal information and the other is responsible for affinity information, and a mechanism to fuse the outputs of the two encoders to accomplish the identification task. Our experiments on real-world credit card transaction data between 71,668 merchants and 433,772,755 customers have demonstrated the effectiveness and efficiency of the proposed model.

关键词： Industries Time series analysis Big data Credit cards data models Task analysis Business

来源：评论

学校读者我要写书评

暂无评论

Narrowing the semantic gap between real and synthetic data

Narrowing the semantic gap between real and synthetic data

引用

IEEE international conference on Intelligent Computer Communication and processing (ICCP)

作者： Radu Beche Sergiu Nedevschi Technical University of Cluj-Napoca Cluj-Napoca Romania

ISBN: (数字)9781728190808

ISBN: (纸本)9781728190815

Image-to-image translation is an emerging method of computer vision dataset augmentation, which allows transferring the style of real life images onto synthetic ones, making them more realistic. In our work we propose an incremental improvement over the adversarial learning generator architectures used by image-to-image translation models. First, we managed to use a single network, instead of 2, thus creating a more memory-efficient model, which allowed for an end-to-end training on high resolutions. Second, inspired from recent work on semantic segmentation architectures, we enhanced our model by implying a multi-scale encoding and stylization phase, allowing for a better control over the contextual and spatial features. Given a synthetic image, our framework allows for its multimodal translation into the real domain. Our model shows promising results at narrowing the semantic gap between synthetic and real data.

关键词： Task analysis Training Decoding Semantics Generators Image segmentation Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

The Automatic option of inference rules for the fuzzy TF-IDF

The Automatic option of inference rules for the fuzzy TF-IDF

引用

international conference on Electronics, Control, Optimization and Computer Science (ICECOCS)

作者： Mariem Bounabi Karim EL Moutaouakil Khalid Satori Computer sciences Imaging and Numerical Analysis Laboratory (LIIAN) Fes Morocco Engineering sciences Laboratories in TAZA Polydisciplinary Faculty Taza Morocco

ISBN: (数字)9781728169217

ISBN: (纸本)9781728169224

For several NLP tasks, we use the Fuzzy Inference System (FIS) to develop a set of decisional systems. Still, the selection rules FIS process needs some modification to be more useful. In this paper, we use FIS to produce terms weight for electronic documents basing on the popular TF-IDF (term frequency-inverse term frequency) components. To insert rules for FIS manually remains a real issue in the text processing domains, where the size of the processed data is enormous. In our work, we suggest including the Association models as automatic technics to produce the inference rules instead of the traditional manual way. Precisely, our approach process in five steps, i.e., preprocessing, limiting membership function for every input and output, nominal representation of the database, call for the Apriori and Filter association as association models to select the most important rules, and finally, post-processing of the received rules. Applying the new technique to produce fuzzy weight for a benchmarked database achieves a significant gain in time, precision rules, and weighting quality. Thus, running the new descriptor matrix with statistical classifiers, e.g., Bayesian Networks, improves accuracy compared with the traditional way and existing methods.

关键词： Fuzzy logic Bayes methods data models Mathematical model Linguistics Task analysis Machine learning

来源：评论

学校读者我要写书评

暂无评论

BERT2DNN: BERT Distillation with Massive Unlabeled data for Online E-Commerce Search

BERT2DNN: BERT Distillation with Massive Unlabeled Data for ...

引用

IEEE international conference on data Mining (ICDM)

作者： Yunjiang Jiang Yue Shang Ziyang Liu Hongwei Shen Yun Xiao Sulong Xu Wei Xiong Weipeng Yan Di Jin *** China College of Intelligence and Computing Tianjin University China

ISBN: (数字)9781728183169

ISBN: (纸本)9781728183176

Relevance has significant impact on user experience and business profit for e-commerce search platform. In this work, we propose a data-driven framework for search relevance prediction, by distilling knowledge from BERT and related multi-layer Transformer teacher models into simple feed-forward networks with large amount of unlabeled data. The distillation process produces a student model that recovers more than 97% test accuracy of teacher models on new queries, at a serving cost that's several magnitude lower (latency 150x lower than BERT-Base and 15x lower than the most efficient BERT variant, TinyBERT). The applications of temperature rescaling and teacher model stacking further boost model accuracy, without increasing the student model complexity. We present experimental results on both in-house e-commerce search relevance data as well as a public data set on sentiment analysis from the GLUE benchmark. The latter takes advantage of another related public data set of much larger scale, while disregarding its potentially noisy labels. Embedding analysis and case study on the in-house data further highlight the strength of the resulting model. By making the data processing and model training source code public, we hope the techniques presented here can help reduce energy consumption of the state of the art Transformer models and also level the playing field for small organizations lacking access to cutting edge machine learning hardwares.

关键词： Training Analytical models Temperature distribution Bit error rate Machine learning data models User experience

来源：评论

学校读者我要写书评

暂无评论

Few-Shot Learning for Remote Sensing Image Retrieval With MAML

Few-Shot Learning for Remote Sensing Image Retrieval With MA...

引用

IEEE international conference on Image processing

作者： Qian Zhong Ling Chen Yuntao Qian College of Computer Science Zhejiang University Hangzhou China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Few-shot remote sensing image retrieval is devoted to add new retrieval categories with a small number of labeled samples, and simultaneously achieve favorable retrieval performance for new categories and keep the primary retrieval performance for the original categories as far as possible. Few-shot learning has received considerable attention, however its applications in image retrieval, especially for remote sensing image retrieval, are still very few. In this paper, we redefine the few-shot image retrieval problem formally and further propose a few-shot retrieval method under model-agnostic meta-learning (MAML) framework, combined with ResNet and GeM as feature extraction module. Moreover, the optimal mean average precision (mAP) is used as ranking loss for defining the loss function of learning model, and a histogram binning approximation of mAP, which is differential, is thus employed so that the whole few-shot retrieval model can be end-to-end trained. The retrieval effectiveness and efficiency of our method are verified on UC-Merced and AID data sets.

关键词： Image retrieval Feature extraction Training Remote sensing Task analysis data models Histograms

来源：评论

学校读者我要写书评

暂无评论

Autonomous Driving Architectures, Perception and data Fusion: A Review

Autonomous Driving Architectures, Perception and Data Fusion...

引用

IEEE international conference on Intelligent Computer Communication and processing (ICCP)

作者： Gustavo Velasco-Hernandez De Jong Yeong John Barry Joseph Walsh IMaR Research Centre / Lero The Irish Software Research Centre Institute of Technology Tralee Tralee Ireland

ISBN: (数字)9781728190808

ISBN: (纸本)9781728190815

Over the last 10 years, huge advances have been made in the areas of sensor technologies and processing platforms, pushing forward developments in the field of autonomous vehicles, mostly represented by self-driving cars. However, the complexity of these systems has been also increased in terms of the hardware and software within them, especially for the perception stage in which the goal is to create a reliable representation of the vehicle and the world. In order to manage this complexity, several architectural models have been proposed as guidelines to design, develop, operate and deploy self-driving solutions for real applications. In this work, a review on autonomous driving architectures is presented, classifying them into technical or functional architectures depending on the domain of their definition. In addition, the perception stage of self-driving solutions is analysed as a component of the architectures, detailing into the sensing part and how data fusion is used to perform localisation, mapping and object detection. Finally, the paper is concluded with additional thoughts on the actual status and future trends in the field.

关键词： Software Computer architecture Autonomous vehicles Robot sensing systems Hardware Standards Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Fast Beam Training for mmWave UAV Communications Using Machine Learning

Fast Beam Training for mmWave UAV Communications Using Machi...

引用

international conference on Wireless Communications and Signal processing (WCSP)

作者： Yong GU Weizhi ZHONG Qiuming ZHU Penghui LI Xiaomin CHEN College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing CHINA College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing CHINA

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

Establishing and training beams in unmanned aerial vehicle (UAV) assisted millimeter-wave (mmWave) communications is a challenging task. In this paper, a novel beam training method is proposed by employing the machine learning (ML) method. Firstly, we analyze the applicable conditions of ML and preplan an ideal relationship of received signals. The required beam patterns based on this ideal relationship can be obtained by using the Fourier series method (FSM). We then formulate the beam selection issue as a polynomial regression problem based on hand-crafted features. Especially, we utilize the denoising autoencoder (DAE) to modify the error caused by the channel noise. Numerical simulation results demonstrate that our proposed beam training algorithm is able to provide precise beam selection for the mmWave UAV communications.

关键词： Training Noise measurement data models Training data Machine learning Unmanned aerial vehicles Slot antennas

来源：评论

学校读者我要写书评

暂无评论

Facial landmark detection on thermal data via fully annotated visible-to-thermal data synthesis

Facial landmark detection on thermal data via fully annotate...

引用

IEEE international Joint conference on Biometrics (IJCB)

作者： Khawla Mallat Jean-Luc Dugelay EURECOM Sophia-Antipolis France

ISBN: (数字)9781728191867

ISBN: (纸本)9781728191874

Thermal imaging has substantially evolved, during the recent years, to be established as a complement, or even occasionally as an alternative to conventional visible light imaging, particularly for face analysis applications. Facial landmark detection is a crucial prerequisite for facial image processing. Given the upswing of deep learning based approaches, the performance of facial landmark detection has been significantly improved. However, this uprise is merely limited to visible spectrum based face analysis tasks, as there are only few research works on facial landmark detection in thermal spectrum. This limitation is mainly due to the lack of available thermal face databases provided with full facial landmark annotations. In this paper, we propose to tackle this data shortage by converting existing face databases, designed for facial landmark detection task, from visible to thermal spectrum that will share the same provided facial landmark annotations. Using the synthesized thermal databases along with the facial landmark annotations, two different models are trained using active appearance models and deep alignment network. Evaluating the models trained on synthesized thermal data on real thermal data, we obtained facial landmark detection accuracy of 94.59% when tested on low quality thermal data and 95.63% when tested on high quality thermal data with a detection threshold of 0.15×IOD.

关键词： Faces databases Annotations Active appearance model Training Shape Face recognition

来源：评论

学校读者我要写书评

暂无评论

Reasoning With Interval-Valued Probabilities

Reasoning With Interval-Valued Probabilities

引用

international conference on Information Fusion

作者： Janith Heendeni Kamal Premaratne Manohar N. Murthi Translational Genomic Research Inst. (TGen) Phoenix AZ USA University of Miami Coral Gables FL USA

ISBN: (数字)9780578647098

ISBN: (纸本)9781728168302

Adequate representative statistical training data needed for machine learning algorithms are often unavailable and, when available, they are often mired in incomplete/missing data. Imputation of such data must be guided by the relationships among different variables and/or by data `missingness' mechanisms. Interval-valued (IV) probabilities are better suited in situations where such information is unavailable. We take the viewpoint that IV probabilities (IVPs) emerge from a single underlying probability distribution about which one has only partial information. PrBounds, the IVPs that this vantage point engenders, offer a fresh perspective of the IV counterpart notions of conditioning and independence and enable reasoning to be carried out in much the same manner as one would with probabilities. When the attribute values are unknown/missing or are known to lie within a set of values, PrBounds can be efficiently learnt by a frequency counting method. The probabilities associated with an arbitrary imputation strategy, including the underlying `true' probabilities, are guaranteed to lie within the PrBounds learnt in this manner. We present an experiment to illustrate the proposed framework.

关键词： Training data Probability distribution data models Bayes methods Probabilistic logic Cognition

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 << < 470 471 472 473 474 475 476 477 478 479 > >>

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：