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

674 篇 会议
12 册 图书
5 篇 期刊文献

馆藏范围

691 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

451 篇 工学
- 322 篇 计算机科学与技术...
- 258 篇 软件工程
- 196 篇 信息与通信工程
- 138 篇 电气工程
- 84 篇 生物工程
- 72 篇 光学工程
- 64 篇 生物医学工程（可授...
- 34 篇 电子科学与技术（可...
- 24 篇 化学工程与技术
- 22 篇 控制科学与工程
- 19 篇 材料科学与工程（可...
- 17 篇 仪器科学与技术
- 13 篇 机械工程
- 12 篇 安全科学与工程
- 9 篇 动力工程及工程热...
- 8 篇 交通运输工程
- 6 篇 网络空间安全
235 篇 理学
- 110 篇 物理学
- 87 篇 生物学
- 85 篇 数学
- 22 篇 化学
- 19 篇 统计学（可授理学、...
- 9 篇 系统科学
104 篇 医学
- 102 篇 临床医学
- 23 篇 基础医学(可授医学...
- 20 篇 药学(可授医学、理...
- 6 篇 公共卫生与预防医...
72 篇 管理学
- 43 篇 图书情报与档案管...
- 31 篇 管理科学与工程(可...
6 篇 法学
6 篇 教育学
- 6 篇 教育学
5 篇 农学
2 篇 军事学

主题

98 篇 signal processin...
58 篇 image segmentati...
58 篇 image processing
54 篇 signal processin...
43 篇 conferences
41 篇 deep learning
38 篇 image enhancemen...
33 篇 image recognitio...
29 篇 feature extracti...
28 篇 training
24 篇 image edge detec...
24 篇 convolution
24 篇 visualization
24 篇 image color anal...
24 篇 image reconstruc...
22 篇 image coding
22 篇 image classifica...
20 篇 neural networks
18 篇 robustness
17 篇 object detection

机构

6 篇 school of inform...
6 篇 college of elect...
5 篇 key laboratory o...
5 篇 university of ch...
5 篇 nanyang technol ...
5 篇 school of mathem...
4 篇 shanghai jiao to...
4 篇 laboratory of be...
4 篇 school of electr...
3 篇 shanghai jiao to...
3 篇 michigan state u...
3 篇 college of mathe...
3 篇 tsinghua shenzhe...
3 篇 shanghai jiao to...
3 篇 national laborat...
2 篇 university of sc...
2 篇 school of comput...
2 篇 school of cyber ...
2 篇 school of mathem...
2 篇 huazhong univers...

作者

6 篇 wang chao
6 篇 yang chuansheng
5 篇 yang yueting
5 篇 wen bihan
5 篇 yang jian
4 篇 jian wang
4 篇 tan anhui
4 篇 anil kumar
4 篇 bo feng
4 篇 chao xu
3 篇 ravishankar saip...
3 篇 zhou jiantao
3 篇 li min
3 篇 zhai guangtao
3 篇 nguyen trong-the
3 篇 feng bo
3 篇 parthasarathy ra...
3 篇 xiaotao huang
3 篇 wang liu
3 篇 fan zhun

语言

691 篇 英文

检索条件"任意字段=2021 International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2021"

共 691 条记录，以下是531-540 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：

Evolution in Computational Intelligence 1

引用

丛书名： Smart Innovation, Systems and Technologies

1000年

作者： Vikrant Bhateja Jinshan Tang Suresh Chandra Satapathy Peter Peer Ranjita Das

ISBN: (数字)9789811666162

ISBN: (纸本)9789811666155;9789811666186

This book presents the proceedings of the 9th international conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2021), held at NIT Mizoram, Aizwal, Mizoram, India, during June 25 – 26, 2021. FICTA conference aims to bring together researchers, scientists, engineers, and practitioners to exchange their new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines.;This volume covers broad areas of Evolution in Computational Intelligence. The conference papers included herein presents both theoretical as well as practical aspects of different areas like ANN and genetic algorithms, human-computer interaction, intelligent control optimization, evolutionary computing, intelligent e-learning systems, machine learning, mobile computing, multi-agent systems, etc. The volume will also serve as a knowledge centre for students of post-graduate level in various engineering disciplines.

关键词： Computational Intelligence Artificial Intelligence Mobile and Network Security signal, image and Speech processing

来源：评论

学校读者我要写书评

暂无评论

On the Use of Spectrogram Inversion for Speech Enhancement

On the Use of Spectrogram Inversion for Speech Enhancement

引用

IEEE SSD international Multi-conference on Systems, signals and Devices

作者： Raja Abdelmalek Bedoui Zied Mnasri Faouzi Benzarti Signal Image and Technology of Information Laboratory Ecole Nationale d'Ingénieurs de Tunis University Tunis El-Manar Tunisia Ecole Nationale d'Ingénieurs de Tunis University Tunis El-Manar Tunisia

Spectrogram inversion or phase retrieval is an old topic in digital signal processing, that has been revisited since a few years for its proved relevance to many recent applications, such as source separation, speech enhancement and compressive sensing. Spectrogram inversion aims to reconstruct a signal from partial spectral information, such as the magnitude spectrum or the phase spectrum only, which are obtained by the short-time Fourier transform (STFT). Thus, in this work the relevance of signal reconstruction is studied. First, the proposed algorithm, based on the recent theoretic relationships between STFT magnitude and phase is presented. Secondly, the proposed method is tested on clean and simulated-noisy speech. Finally, the relevance of spectrogram inversion as implemented either in our proposal or in state-of-the-art algorithms is evaluated for the particular application on speech enhancement. The results show the advantages and the limits of using spectrogram inversion in such an application.

关键词： Source separation Fourier transforms signal processing algorithms Digital signal processing Speech enhancement signal reconstruction Iterative algorithms

来源：评论

学校读者我要写书评

暂无评论

Interactive gesture feature recognition method in 3D virtual laboratory based on mobile terminal

Interactive gesture feature recognition method in 3D virtual...

引用

6th international conference on Intelligent Computing and signal processing (ICSP)

作者： Dan Zhao School of Mathematics and Information Science Guangxi College of Education Nanning China

ISBN: (纸本)9781665447300

In order to further improve the accuracy of laboratory interactive gesture recognition. Therefore, this paper proposes an interactive gesture feature recognition method for 3D virtual laboratory under mobile terminal, which extracts gradient direction histogram and local binary pattern features respectively, and carries out feature fusion. The fusion features include not only the gradient direction information of the local region of the image, but also the texture information, which can more comprehensively describe the gesture features. The fusion feature vector is input into SVM classifier to complete gesture recognition. Experiments show that the method of gesture recognition in 3D virtual laboratory under mobile terminal has higher accuracy than traditional methods. In this experiment, a variety of gestures are recognized, and the maximum recognition rate is significantly improved.

关键词： Support vector machines Histograms image recognition Three-dimensional displays signal processing algorithms Gesture recognition signal processing

来源：评论

学校读者我要写书评

暂无评论

image Dehazing via Multilayer Detail Enhancement and Saturation Compensation

Image Dehazing via Multilayer Detail Enhancement and Saturat...

引用

6th international conference on Intelligent Computing and signal processing (ICSP)

作者： Ziye Zhang Tian Pu Ping Zhang School of Optoelectronic Science and Engineering UESTC Chengdu China School of Information and Communication Engineering UEST Chengdu China

images taken in hazy conditions often suffer from severe quality degradation, such as detail loss, low contrast, and color cast. To solve these problems, this paper proposed a naturalness preserved dehazing method. First, a hue histogram distribution prior is used to determine if the input image is color- casted, and a simple color correction method is provided to restore colors. Second, a multilayer detail enhancement unit is applied to sharpen the intensity channel, and an adaptive local gamma correction is used to compensate saturation. Dehazed results can be achieved by converting back to RGB. Extensive experimental results indicate that the proposed method can effectively improve the visibility of hazy images, bring out the details without undesirable halo effects, and reproduce vivid color. The assessment results demonstrate that our method is capable of achieving outstanding dehazing performance, compared with some state-of-the-art methods.

关键词： Degradation Histograms image color analysis signal processing algorithms signal processing Nonhomogeneous media Attenuation

来源：评论

学校读者我要写书评

暂无评论

Star image Simulation for Starlight Refraction Sensor

Star Image Simulation for Starlight Refraction Sensor

引用

IEEE international conference on signal and image processing (ICSIP)

作者： Qing Xu Chunhui Zhao Xiao Li Beijing Institute of Control Engineering Space Optoelectronic Measurement and Perception Lab Beijing China

ISBN: (纸本)9781665446006

The indirectly sensing horizon technique of starlight refraction utilizes star sensors to detect refracted starlight under the Earth's atmospheric limb background to achieve high precision attitude and position measurement of satellites. As star images usually can't be obtained in real time, software star image simulation is a quick and easy to implement approach for star identification algorithm validation. This paper firstly introduces the basic theory of starlight atmospheric refraction navigation. Then the atmospheric limb background radiation model and stellar radiation model of starlight refraction sensor are established. On this basis, the process of refraction star image simulation is discussed in detail. According to the given star sensor parameters and simulated radiation data, an example of refraction star image simulation is realized and the offset image coordinates of the refracted stars are analyzed for verification.

关键词： image sensors Satellites Atmospheric measurements Atmospheric modeling Software algorithms Position measurement Satellite navigation systems

来源：评论

学校读者我要写书评

暂无评论

A Homogeneity-Based Multiscale Hyperspectral image Representation for Sparse Spectral Unmixing

A Homogeneity-Based Multiscale Hyperspectral Image Represent...

引用

IEEE international conference on Acoustics, Speech and signal processing

作者： Luciano C. Ayres Sergio J. M. de Almeida Jose C. M. Bermudez Ricardo A. Borsoi Catholic University of Pelotas Pelotas RS Brazil Federal University of Santa Catarina Florianópolis SC Brazil CNRS OCA Université Côte d’Azur Nice France

Several approaches have been proposed to solve the spectral unmixing problem in hyperspectral image analysis. Among them the use of sparse regression techniques aims to characterize the abundances in pixels based on a large library of spectral signatures known a priori. Recently, the integration of image spatial-contextual information significantly enhanced the performance of sparse unmixing. In this work, we propose a computationally efficient multiscale representation method for hyperspectral data adapted to the unmixing problem. The proposed method is based on a hierarchical extension of the SLIC oversegmentation algorithm constructed using a robust homogeneity testing. The image is subdivided into a set of spectrally homogeneous regions formed by pixels with similar characteristics (superpixels). This representation is then used to provide prior spatial regularity information for the abundances of materials present in the scene, improving the conditioning of the unmixing problem. Simulation results illustrate that the method is capable of estimating abundances with high quality and low computational cost, especially in noisy scenarios.

关键词： Simulation signal processing algorithms signal processing Spatial databases Computational efficiency Noise measurement Speech processing

来源：评论

学校读者我要写书评

暂无评论

Unveiling Anomalous Nodes Via Random Sampling and Consensus on Graphs

Unveiling Anomalous Nodes Via Random Sampling and Consensus ...

引用

IEEE international conference on Acoustics, Speech and signal processing

作者： Vassilis N. Ioannidis Dimitris Berberidis Georgios B. Giannakis University of Minnesota Minneapolis USA Carnegie Mellon University Pittsburgh USA

The present paper develops a graph-based sampling and consensus (GraphSAC) approach to effectively detect anomalous nodes in large-scale graphs. GraphSAC randomly draws sub-sets of nodes, and relies on graph-aware criteria to judiciously filter out sets contaminated by anomalous nodes, before employing a semi-supervised learning (SSL) module to estimate nominal label distributions per node. These learned nominal distributions are minimally affected by the anomalous nodes, and hence can be directly adopted for anomaly detection. The per-draw complexity grows linearly with the number of edges, which implies efficient SSL, while draws can be run in parallel, thereby ensuring scalability to large graphs. GraphSAC is tested under different anomaly generation models based on random walks, as well as contemporary adversarial attacks for graph data. Experiments with real-world graphs show-case the advantage of GraphSAC relative to state-of-the-art alternatives.

关键词： Scalability image edge detection conferences signal processing algorithms Clustering algorithms Semisupervised learning signal processing

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Stacked Capsule Autoencoder for Hyperspectral image Classification

Unsupervised Stacked Capsule Autoencoder for Hyperspectral I...

引用

IEEE international conference on Acoustics, Speech and signal processing

作者： Erting Pan Yong Ma Xiaoguang Mei Fan Fan Jiayi Ma School of Electronic Information Wuhan university Wuhan China Institute of Aerospace Science and Technology Wuhan university Wuhan China

Since CapsNet [1] shattered all previous records of algorithms for image recognition, the capsule's conception has attracted bright attention. It interprets an object by the geometrical arrangement of parts. We think it can be transferred to hyperspectral images. In a hyperspectral data cube, each pixel spectrum can be regarded as a continuous curve representing its inherent properties. In the spatial domain, there are various spatial distributions in different positionsand there is usually a specific structural relationship between adjacently distributed categories. Based on HSI data's aforementioned structural characteristics, combined with the stacked capsule autoencoder, we propose our model to achieve an unsupervised HSI classification. In our model, the ConvLSTM is employed to discover part capsules of HSI, and we utilize Set Transformer to encode relations among all parts and indicate object capsules. The decoders of both phases use Gaussian mixture models to reconstruct specific information. Experimental results of the Pavia Center dataset show the exceptional of our model.

关键词： image recognition Graphical models signal processing Decoding Task analysis Speech processing image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Clustering of Time Series signals Using Neuromorphic Energy-Efficient Temporal Neural Networks

Unsupervised Clustering of Time Series Signals Using Neuromo...

引用

IEEE international conference on Acoustics, Speech and signal processing

作者： Shreyas Chaudhari Harideep Nair Jose M. F. Moura John Paul Shen Carnegie Mellon University

Unsupervised time series clustering is a challenging problem with diverse industrial applications such as anomaly detection, bio-wearables, etc. These applications typically involve small, low-power devices on the edge that collect and process real-time sensory signals. State-of-the-art time-series clustering methods perform some form of loss minimization that is extremely computationally intensive from the perspective of edge devices. In this work, we propose a neuromorphic approach to unsupervised time series clustering based on Temporal Neural Networks that is capable of ultra low-power, continuous online learning. We demonstrate its clustering performance on a subset of UCR Time Series Archive datasets. Our results show that the proposed approach either outperforms or performs similarly to most of the existing algorithms while being far more amenable for efficient hardware implementation. Our hardware assessment analysis shows that in 7 nm CMOS the proposed architecture, on average, consumes only about 0.005 mm~2 die area and 22 μW power and can process each signal with about 5 ns latency.

关键词： Performance evaluation Neuromorphics image edge detection Time series analysis Neural networks signal processing algorithms Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Bimodal Emotion Recognition for the Patients with Depression

Bimodal Emotion Recognition for the Patients with Depression

引用

IEEE international conference on signal and image processing (ICSIP)

作者： Xuesong Wang Shenghui Zhao Yingxue Wang School of Information and Electronics Beijing Institute of Technology Beijing China China Academic of Electronics and Information Technology

ISBN: (纸本)9781665446006

With the rapid development of the society, over three hundred million people from worldwide suffer from depression, which has become one of the most serious health problems in the world. On the other hand, emotion recognition research works barely focuses on the depression patients although their emotion differs from that of the normal people obviously. Firstly, a speech/text emotion dataset was built up under the dialogue scenes with both the depressed patients and the normal people, and the speech/text fragments were classified into five common emotions: sadness, anger, happy, fear and neutral. Secondly, a bimodal emotion recognition algorithm is proposed, which uses a multimodal Transformer model as the feature fusion module. The experimental results show that it achieves an accuracy of 69.2% for the normal people and 59.4% for the depression patients.

关键词： Emotion recognition image recognition conferences Depression Transformers Classification algorithms Optimization

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70页 << < 50 51 52 53 54 55 56 57 58 59 > >>

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：