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

6,059 篇 会议
69 篇 期刊文献
42 册 图书

馆藏范围

6,170 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,602 篇 工学
- 2,535 篇 计算机科学与技术...
- 1,799 篇 软件工程
- 1,411 篇 信息与通信工程
- 981 篇 电气工程
- 421 篇 控制科学与工程
- 396 篇 电子科学与技术（可...
- 367 篇 光学工程
- 345 篇 生物工程
- 285 篇 生物医学工程（可授...
- 284 篇 仪器科学与技术
- 232 篇 机械工程
- 148 篇 安全科学与工程
- 137 篇 交通运输工程
- 113 篇 化学工程与技术
- 113 篇 网络空间安全
- 105 篇 材料科学与工程（可...
- 98 篇 动力工程及工程热...
- 81 篇 建筑学
1,476 篇 理学
- 685 篇 数学
- 536 篇 物理学
- 370 篇 生物学
- 229 篇 系统科学
- 214 篇 统计学（可授理学、...
- 116 篇 化学
533 篇 管理学
- 320 篇 管理科学与工程(可...
- 256 篇 图书情报与档案管...
- 127 篇 工商管理
344 篇 医学
- 325 篇 临床医学
- 162 篇 基础医学(可授医学...
- 108 篇 药学(可授医学、理...
98 篇 法学
60 篇 农学
48 篇 经济学
39 篇 教育学
27 篇 军事学
16 篇 文学
5 篇 艺术学

主题

327 篇 feature extracti...
298 篇 internet of thin...
257 篇 real-time system...
189 篇 image segmentati...
186 篇 internet
166 篇 signal processin...
165 篇 image processing
158 篇 accuracy
145 篇 image edge detec...
144 篇 deep learning
139 篇 signal processin...
129 篇 training
128 篇 cameras
121 篇 image coding
116 篇 image color anal...
105 篇 visualization
104 篇 image retrieval
96 篇 robustness
95 篇 computational mo...
90 篇 image recognitio...

机构

11 篇 school of comput...
9 篇 faculty of infor...
8 篇 school of cyber ...
8 篇 school of electr...
8 篇 beijing universi...
8 篇 state key labora...
7 篇 school of inform...
7 篇 school of inform...
7 篇 college of elect...
7 篇 institute of sig...
7 篇 harbin institute...
7 篇 college of infor...
7 篇 school of electr...
6 篇 university of sc...
6 篇 school of inform...
6 篇 school of electr...
6 篇 chaoyang univ te...
6 篇 university of el...
6 篇 wuhan university...
6 篇 department of in...

作者

15 篇 dipanda albert
15 篇 yetongnon kokou
13 篇 yoshitaka sakura...
13 篇 tsuruta setsuo
13 篇 sakurai yoshitak...
13 篇 fan zhun
12 篇 setsuo tsuruta
11 篇 chbeir richard
11 篇 li li
11 篇 wang wei
9 篇 zhang yan
9 篇 lee chin-feng
8 篇 zhang lei
8 篇 jing wang
8 篇 wang hao
7 篇 zhu guijie
7 篇 kinshuk
7 篇 jeon gwanggil
7 篇 ahmad tohari
7 篇 shen jau-ji

语言

5,951 篇 英文
199 篇 其他
35 篇 中文
1 篇 土耳其文

检索条件"任意字段=International Conference on Signal-Image Technology and Internet-Based Systems SITIS"

共 6170 条记录，以下是381-390 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：

QoE Estimation of WebRTC-based Audiovisual Conversations from Facial Expressions

QoE Estimation of WebRTC-based Audiovisual Conversations fro...

引用

international IEEE conference on signal-image Technologies and internet-based System

作者： Gülnaziye Bingöl Simone Porcu Alessandro Floris Luigi Atzori DIEE University of Cagliari Cagliari Italy CNIT University of Cagliari Cagliari Italy

Online videoconferencing applications have become more popular and occupy a significant portion of consumer internet traffic. Thus, it is crucial to assess the Quality of Experience (QoE) for these applications to effectively implementing high-quality services. Although the major approach to assess the QoE is the conduction of a subjective quality assessment, this method relies on user’s feedback and it is not suitable for real-time management systems. For this reason, in this paper, we propose alternative QoE estimation models based on facial expression features extracted from the face of the users during audiovisual conversations with a WebRTC-based telemeeting service. We first conducted a subjective quality assessment to investigate the QoE of two-party audiovisual conversations impaired by poor network conditions. Then, we used the extracted facial expression features obtained by observing the test participants to train Machine Learning (ML) algorithms and a Fully Convolutional Network (FCN) with the aim to estimate the perceived QoE solely on the base of these features. Finally, we discuss and compare the QoE estimation performance of the proposed models in terms of accuracy, precision, recall, and F1-score metrics. In particular, the ML model (Support Vector Machine) and the FCN achieved the mean estimation accuracy of 0.78 and 0.70, respectively.

关键词： Training Support vector machines Maximum likelihood estimation Oral communication Speech enhancement Feature extraction Video conferencing

来源：评论

学校读者我要写书评

暂无评论

Dense object detection for remote sensing images based on multi-scale partitioning and super-resolution optimization 24

Dense object detection for remote sensing images based on mu...

引用

3rd international conference on signal Processing, Computer Networks and Communications, SPCNC 2024

作者： Li, Lu Zhu, Xia Ni, Shaofeng Gao, Fan State Grid Location based Service Co. Ltd. Beijing China State Grid Information & Telecommunication Group Co. Ltd. Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China

ISBN: (纸本)9798400710834

Detecting dense objects in remote sensing image is a critical yet challenging task due to variations in target scale, image resolution, and complex backgrounds. Traditional detection methods often struggle with these dense regions, particularly for small or overlapping objects. To overcome these limitations, this study introduces an innovative approach that combines multi-scale partitioning with super-resolution optimization to improve the detection of densely packed objects. By applying K-Means clustering to identify regions of interest (ROI) and using a local super-resolution network to enhance these areas, we improve the clarity and detectability of small-scale objects. Additionally, we implement a global-local feature extraction architecture, where global features are captured using Transformer-based attention, while local features focus on fine-grained object details. Non-Maximum Suppression (NMS) is employed to fuse multi-scale features and eliminate redundant detections. Experimental results on the DOTA and HRSC2016 datasets demonstrate the effectiveness of our approach, achieving superior performance over state-of-the-art methods in detecting small and densely packed targets. This method shows significant promise for remote sensing applications requiring high-precision target detection. © 2024 Copyright held by the owner/author(s).

关键词： Proximity sensors

来源：评论

学校读者我要写书评

暂无评论

Bearing Vibration signal Restoration Method based on Fuzzy Adaptive Sliding Mode Algorithm

Bearing Vibration Signal Restoration Method Based on Fuzzy A...

引用

2023 IEEE international conference on Network, Multimedia and Information technology, NMITCON 2023

作者： Mao, Yuze Shi, Lei Wang, Xiaokang Wang, Chao Shanghai Aerospace Control Technology Institute Shanghai China

ISBN: (纸本)9798350300826

With the development of intelligent algorithms on the internet and the widespread application of signal recovery technology in the current mechanical industry, signal recovery systems based on fuzzy adaptive sliding mode algorithms are becoming increasingly important for improving mechanical bearing fault diagnosis. In the construction of the entire mechanical bearing signal recovery model, how to improve the accuracy of signal recovery and reduce the time for model signal feature extraction is currently a key issue that needs to be urgently solved. This article conducts simulation experiments and analysis on the parameter dataset of mechanical bearing components that are prone to faults. based on the fuzzy adaptive sliding mode algorithm process, combined with adaptive law parameter calculation and fuzzy system model design, the following conclusion is drawn: the application of improved signal recovery models on the sampled four bearing component parameters has an average improvement of 6.65% in recovery accuracy and 9.25% in recovery efficiency. This method uses fuzzy adaptive sliding mode algorithm to adaptively extract fault features, accurately identify fault types and degrees, innovatively suppress noise and interference, and improve the accuracy of vibration signal recovery. © 2023 IEEE.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

A Water Body Extraction Network based on Fusing SAR images and DEM Data 2

A Water Body Extraction Network Based on Fusing SAR Images a...

引用

2nd IEEE international conference on signal, Information and Data Processing, ICSIDP 2024

作者： Wang, Jianyu Tian, Ye Chen, Lei Wang, Ning Zhang, Ningning Liu, Siao China Telecom Co. Ltd. Satellite Communications Branch Beijing China

ISBN: (纸本)9798331515669

Synthetic Aperture Radar (SAR) plays a crucial role in flood monitoring and early warning systems through water body extraction techniques. However, unlike optical remote sensing images, SAR images are affected by unique imaging characteristics, including shadows, noise, and complex environments, which complicate interpretation. Most existing deep learning methods rely solely on single SAR images for model training, without incorporating additional information, leading to lower accuracy in water body interpretation, especially in challenging scenarios such as mountainous areas and densely vegetated regions. To address these challenges, we propose a water body extraction algorithm that fuses SAR images with Digital Elevation Model (DEM) data to improve the accuracy and robustness in complex environments. Four different fusion strategies are explored at both the image level and feature level, incorporating DEM and slope data into an existing encoder-decoder architecture. These enhancements effectively address the aforementioned issues. Experimental results demonstrate that the fusion approach significantly improves water body extraction precision and reduces false alarm rates compared to non-fusion methods. Through a comparative analysis of the different fusion strategies, the best approach was identified as image-level fusion using DEM data, achieving a mean Intersection over Union (mIoU) of 0.95 on the GF-Floodnet dataset. © 2024 IEEE.

关键词： Radar warning systems

来源：评论

学校读者我要写书评

暂无评论

A three-dimensional DV-Hop algorithm based on the improved grey wolf algorithm for wireless sensor networks 3

A three-dimensional DV-Hop algorithm based on the improved g...

引用

3rd international conference on Advanced Algorithms and signal image Processing, AASIP 2023

作者： Ye, Shuai Yu, Xiuwu Liu, Yong School of Electrical Engineering University of South China Hengyang China

ISBN: (纸本)9781510668522

Location technology has become one of the core technologies of the internet of Things, especially for wireless sensor networks. The DV-Hop algorithm is used in various situations as one of the representative algorithms. Aiming at the large positioning error of the DV-Hop algorithm, this paper proposes a three-dimensional DV-Hop algorithm based on the improved Grey Wolf algorithm (TDIGW). First of all, the algorithm refines the number of hops through a multicommunication radius strategy, which reduces errors caused by the number of node hops. Then, mean square error is introduced to optimize the average hop distance of the beacon nodes. Finally, the grey wolf algorithm with dynamic weight factor optimization is used instead of least squares to calculate the coordinate positions of the unknown nodes. The simulation results show that compared with the traditional 3D-DVHop algorithm and other *** average localization error of this algorithm is reduced by 20.13%, 12.62% and 8.98% respectively. The algorithm proposed in this paper reduces the localization error effectively © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

Tucker Decomposition based Lossless image Compression for 3D Medical image 8

Tucker Decomposition Based Lossless Image Compression for 3D...

引用

8th IEEE international conference on Computational System and Information technology for Sustainable Solutions, CSITSS 2024

作者： Makandar, Aziz Biradar, Rekha Ksa Wuv Computer Science department India

ISBN: (纸本)9798331505462

The successful operation of a telecommunication system depends on the maintaining and transferring of high compression three-dimension medical images that produce reconstructions of excellent quality after decompression. To address this issue, we presented a Tucker Decomposition based lossless image compression for three-dimension medical image. Tucker decomposition, the extended form of Singular Value Decomposition (SVD), can handle high dimensional information;SVD is limited to two dimensions. Use the Selective Bounding volume (SBV) to find and retrieve the Volume of Interest (VOI). Tucker decomposition is used to break down the extracted volume of interest (VOI) into its component major tensor, coefficient matrices, and distinct parameters. subsequently, an Adaptive Binary Range Coder (ABRC) is utilized for compress these values. By inverting the compression procedure and integrating the uncompressed VOI with the surrounding area employing the bound volume coordinates connected to the compressed three-dimensional image, the final uncompressed VOI is produced. utilizing a range of 3D medical images obtained through different forms of imaging, the proposed approach's performance was assessed using analytical evaluation metrics like the Compression Ratio (CR), Peak signal-to-Noise Ratio (PSNR), and Structural Similarity Index Measure (SSIM). The proposed compression methodology produces consistently high-quality image compressions and produces larger-scale results, as shown by the method's outcome. © 2024 IEEE.

关键词： Voice/data communication systems

来源：评论

学校读者我要写书评

暂无评论

Fish Detection and Quantity Estimation based on Sonar images 1st

Fish Detection and Quantity Estimation Based on Sonar Images

引用

1st international conference on Extended Reality, ICXR 2024

作者： Du, Wenxiang Yan, Shuai Qi, Yue State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China Qingdao Research Institute of Beihang University Qingdao266100 China

ISBN: (纸本)9789819636785

Due to the complex underwater environment and dense targets, it is difficult to quickly and accurately calculate the location and quantity of fish targets in marine ranching. We have developed an underwater target detection and counting algorithm based on sonar images, which includes four parts: image preprocessing, background subtraction, contour detection, and target counting. Firstly, we design a sliding-window-based gain algorithm based on the uneven grayscale value of sonar images, which amplifies the effective signal while smoothing the grayscale of the image. Secondly, background subtraction is used to separate the foreground and background of the sonar image, which can remove background noise and filter the target using a filtering algorithm to generate a binary image with clear targets. Then, target detection is combined with morphological processing techniques and contour detection algorithms. Finally, we use image erosion technology to separate overlapping targets, calculate the contour position of the targets, and count the quantity. A large number of results indicate that our algorithm can quickly and accurately detect the position of fish in sonar images while also counting the number of fishes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Binary images

来源：评论

学校读者我要写书评

暂无评论

Indoor Accidents Detection for Elderly based on Features Fusion and LSTM 21

Indoor Accidents Detection for Elderly Based on Features Fus...

引用

21st IEEE international conference on Computer Applications, ICCA 2024

作者： San, Win Pa Pa Zaw, Sai Maung Maung University of Computer Studies Mandalay Image and Signal Processing Lab Mandalay Myanmar University of Computer Studies Mandalay Faculty of Computer Systems and Technology Mandalay Myanmar

ISBN: (纸本)9789998601673

Nowadays, with aging of the human society, the 'ratio of family care givers and elderly' is not equivalent and cannot give enough caring to the elderly in some countries. Therefore, automatic health monitoring system for elderly draws the interests of many researchers and become as special issue. In the implementation of elderly people monitoring system, the detection of fall events plays as an important role because the fall is the common cause which is very risky and threaten the health of elderly. The aim of this research is to implement the vision-based fall detection system which is important for health monitoring of elderly by applying the computer vision and deep learning technology. Most of the traditional vision-based fall detection systems which based on the height, width of human posture, fail to detect the fall events from different camera viewpoints. In this research, to accurately detect the fall from different camera viewpoint, the features fusion approach is applied over the deep learning model. In the implementation of the system, firstly, the human silhouette image is created by using the background subtraction. After that, the human silhouette image which have been extracted from two consecutive frames are fused as a single image called Silhouette History image (SHI). Then, the SHI results are used as shape feature. On the other hand, the motion features called Dense Optical Flow (DOF) is extracted over the two consecutive video frames and fuse SHI and DOF as a single input image. Then, the results of features fusion are feed as input for pretrained Convolution Neural Network (CNN) for extracting the deep CNN features. Finally, the Recurrent Neural Network (RNN) called Long-Short-Term-Memory (LSTM) is trained over those CNN features for recognizing the sequence of fall event. The experiments are performed using the publicly available dataset of UP-fall detection dataset for evaluating and confirming the effectiveness of the proposed method. © 2024

关键词： Fall detection

来源：评论

学校读者我要写书评

暂无评论

SuperTA-Net: A Supervised Transmission-Augmented Network for image Compressive Sensing Reconstruction 6

SuperTA-Net: A Supervised Transmission-Augmented Network for...

引用

6th international conference on Data-Driven Optimization of Complex systems (DOCS)

作者： Zhang, Zhijie Bai, Huang Stankovic, Ljubisa Sun, Junmei Li, Xiumei Hangzhou Normal Univ Sch Informat Sci & Technol Hangzhou Peoples R China Univ Montenegro Fac Elect Engn Podgorica Montenegro

ISBN: (纸本)9798350377859;9798350377842

Compressive sensing (CS) has seen extensive use in signal processing, particularly in tasks related to image reconstruction. CS simplifies the sampling and compression procedures, but leaves the difficulty to the nolinear reconstruction. Traditional CS reconstruction algorithms are usually iterative, having a complete theoretical foundation. However, these iterative algorithms are constrained by significant computational complexity. While modern deep network-based methods can achieve high-precision reconstruction in compressed sensing (CS) with satisfactory speed, they often lack theoretical analysis and interpretability. To leverage the strengths of both types of CS methods, the deep unfolding networks (DUNs) have been developed. In this paper, a novel DUN named supervised transmission-augmented network (SuperTA-Net) is proposed. based on the framework of our previous work PIPO-Net, the multi-channel transmission strategy is put forward to reduce the influence of critical information loss between modules and improve the reliability of data. Besides, in order to avoid the issues such as high information redundancy and high computational burden when too many channels are set, the attention based supervision scheme is presented to dynamically adjust the weight of each channel and remove the redundant information. Through experiments focused on reconstructing CS images, the proposed neural network architectures are shown to be highly effective.

关键词： Compressive sensing deep unfolding network multi-channel transmission attention based supervision alternating optimization

来源：评论

学校读者我要写书评

暂无评论

IOT based Smart Wheelchair for Elderly Healthcare Monitoring

IOT Based Smart Wheelchair for Elderly Healthcare Monitoring

引用

2023 international conference on Power, Instrumentation, Energy and Control, PIECON 2023

作者： Dar, Reyaz Ahmad Khatoon, Shahida Saleem, Basharat Khan, Huma Jamia Millia Islamia Department of Electrical Engineering New Delhi India Uttrakhand Technical University Department of Computer Science Dehradun India

ISBN: (纸本)9798350399769

With every field of technology witnessing advancement and innovation, application of such innovations with refined expertise has eased human welfare. In present times also, internet of Things (IOT) is proving to be panacea of all hiccups for handicapped patients. Patients enduring physical disabilities cannot take care of themselves sans help of other individuals, and therefore need artificial tools to move around like wheelchair. Under a promising technology, smart/capable wheelchairs are supposed to be developed which are laced with pro-active sensory system. The technology incorporated is internet of Things (IOT). The disabled patients using these rare wheelchairs, no longer need to depend on others rather sensors fitted with the wheelchairs, monitor the vital bio indices as that of blood, heart, lungs and neural system. In case of any irregularity, signal transaction using embedded systems, onto cloud takes place. This results in flagging a signal which can be accessed by doctors available in online mode. Hence the redressel of medical problems would become much more effective, easier and in less time. IOT is certainly a promising technology for medical care also. © 2023 IEEE.

关键词： internet of things

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 << < 35 36 37 38 39 40 41 42 43 44 > >>

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：