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

20,242 篇 会议
164 篇 期刊文献
80 册 图书
3 篇 学位论文

馆藏范围

20,489 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

12,755 篇 工学
- 8,298 篇 计算机科学与技术...
- 5,001 篇 软件工程
- 4,985 篇 信息与通信工程
- 4,638 篇 电气工程
- 1,447 篇 控制科学与工程
- 1,321 篇 电子科学与技术（可...
- 1,224 篇 光学工程
- 899 篇 生物医学工程（可授...
- 868 篇 机械工程
- 830 篇 仪器科学与技术
- 811 篇 生物工程
- 326 篇 网络空间安全
- 291 篇 交通运输工程
- 284 篇 安全科学与工程
- 278 篇 化学工程与技术
- 247 篇 动力工程及工程热...
- 189 篇 建筑学
- 179 篇 土木工程
4,662 篇 理学
- 2,149 篇 数学
- 2,072 篇 物理学
- 874 篇 生物学
- 668 篇 统计学（可授理学、...
- 522 篇 系统科学
- 330 篇 化学
1,523 篇 医学
- 1,405 篇 临床医学
- 383 篇 基础医学(可授医学...
- 269 篇 药学(可授医学、理...
1,368 篇 管理学
- 824 篇 管理科学与工程(可...
- 615 篇 图书情报与档案管...
- 208 篇 工商管理
204 篇 法学
136 篇 农学
78 篇 经济学
69 篇 军事学
64 篇 教育学
40 篇 文学
24 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

1,120 篇 image segmentati...
1,067 篇 image coding
1,059 篇 signal processin...
1,010 篇 image processing
987 篇 internet of thin...
952 篇 feature extracti...
830 篇 image reconstruc...
631 篇 internet
553 篇 signal processin...
495 篇 signal to noise ...
476 篇 image edge detec...
475 篇 deep learning
456 篇 training
423 篇 image color anal...
400 篇 cameras
397 篇 robustness
395 篇 image enhancemen...
306 篇 image resolution
292 篇 image recognitio...
287 篇 visualization

机构

58 篇 school of inform...
39 篇 university of sc...
37 篇 signal processin...
29 篇 microsoft resear...
27 篇 university of ch...
26 篇 institute of sig...
26 篇 signal processin...
25 篇 center for signa...
24 篇 university of el...
23 篇 school of electr...
21 篇 ieee
21 篇 college of big d...
20 篇 school of cyber ...
20 篇 department of si...
20 篇 school of inform...
20 篇 signal and infor...
20 篇 school of electr...
19 篇 hsch darmstadt d...
19 篇 peng cheng labor...
19 篇 harbin institute...

作者

31 篇 li zhuo
27 篇 zhuo li
25 篇 sridharan sridha
23 篇 yang yang
23 篇 r.m. mersereau
20 篇 jing zhang
20 篇 wei li
20 篇 gabbouj moncef
19 篇 mansouri majdi
18 篇 zhang lei
18 篇 busch christoph
18 篇 m. gabbouj
17 篇 m.j.t. smith
17 篇 bouzrara kais
17 篇 clinton fookes
17 篇 wang wei
17 篇 zhang yan
16 篇 wang lei
16 篇 takahiro ogawa
16 篇 ghassan alregib

语言

19,942 篇 英文
461 篇 其他
75 篇 中文
7 篇 俄文
6 篇 土耳其文
1 篇 西班牙文

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

共 20489 条记录，以下是4571-4580 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：

Scalable SubXPCA with Extended Morphological Profiles Applied to Hyperspectral image Classification on a Distributed Platform

Scalable SubXPCA with Extended Morphological Profiles Applie...

引用

ieee international conference on Big Data

作者： Bogolu Rupa Atul Negi School of Computer and Information Sciences University of Hyderabad Hyderabad Telangana India Vardhaman College of Engineering Hyderabad Telangana India

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

The resolution of large volumes of high-dimensional hyperspectral images have increased significantly due to the ongoing advancements in satellite remote sensing technology. One of the most well-known, widely used, and open-source distributed processing framework is Apache Spark, which is proven to quickly handle enormous volumes of these remotely sensed hyperspectral images. Therefore, there is a need for dimensionality reduction algorithms to process these high dimensional images and achieve accurate application performance. This paper suggests a distributed approach for spectral and spatial dimensionality reduction of hyperspectral images. We implemented feature partitioning principal component analysis based on the SubXPCA method for spectral dimensionality reduction and Extended Morphological Profiles for spatial dimensionality reduction in a Spark cluster distributed environment. We compared the proposed method against other feature and non-feature partitioning dimensionality reduction methods with Extended Morphological Profiles. Our experiments on different real and synthetic hyperspectral image datasets confirm that the proposed spectral-spatial reduction method classification performance is better than the spectral reduction methods and their competitors. The proposed method’s running time decreases with an increase in the number of cores in the cluster. The proposed methodology showed a speedup factor of 7.12×, 13.17× and more in a standalone Spark cluster and a Google cloud Dataproc cluster respectively, with an increase in the number of cores.

关键词： Dimensionality reduction Satellites Runtime image resolution Partitioning algorithms internet Sparks Hyperspectral imaging Principal component analysis image classification

来源：评论

学校读者我要写书评

暂无评论

Difference Guided VHR Remote Sensing image Change Detection

Difference Guided VHR Remote Sensing Image Change Detection

引用

international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Jiukai Sun Ganchao Liu Xuelong Li Yuan Yuan School of Computer Science Ministry of Industry and Information Technology Xi’an P. R. China School of Artificial Intelligence OPtics and ElectroNics (iOPEN) Ministry of Industry and Information Technology Xi’an P. R. China Northwestern Polytechnical University Xi’an P.R. China Key Laboratory of Intelligent Interaction and Applications (Northwestern Polytechnical University) Ministry of Industry and Information Technology Xi’an P. R. China

VHR remote sensing images have abundant ground features and details, but it is a great challenge for machine understanding. The "same object with different spectral" problem caused by environment changes, such as seasonal alternation, bad weather and shadow, is the biggest challenge in multitemporal image change detection, which is more prominent in VHR images. For this problem, a novel difference guided VHR image change detection (DGCD) method is proposed in this paper. In the feature learning stage of DGCD model, difference features are used to guide the feature extraction to suit with the change detection task. In order to make the model focus on the change features, both of the spatial and channel attention mechanism are introduced. Finally, for the edge region of VHR image which is hard to be discriminated, a new edge enhanced loss function based on BCL loss is designed. Experiments on public datasets show the superiority of proposed DGCD method. It has good generalization ability in different classical challenging scenarios. Compared with the representative methods in recent years, the proposed DGCD method performs better on VHR image change detection.

关键词： Representation learning image edge detection Feature extraction Encoding Decoding Task analysis Speech processing

来源：评论

学校读者我要写书评

暂无评论

Enhancing Emotion Reasoning for image Multi-Emotion Prediction

Enhancing Emotion Reasoning for Image Multi-Emotion Predicti...

引用

international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Bingbing Wang Geng Tu Bin Liang Zhixin Bai Min Yang Xi Zeng Liang Yao Ruifeng Xu Harbin Institute of Technology (Shenzhen) Shenzhen China Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Shenzhen China The Chinese University of Hong Kong Hong Kong China SIAT Chinese Academy of Sciences Shenzhen China The 30th Research Institute of China Electronics Technology Group Corporation Chengdu China Peng Cheng Laboratory Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

image multi-emotion prediction aims to identify the emotions evoked by images in humans. In the real world, individual cognitive differences can lead to different viewers experiencing varied emotions. Most existing researchers primarily focus on analyzing image features, which are limited to the perceptual level, leading to a superficial understanding of emotions. To address this gap, we propose an Emotional Reasoning Chain (EReC) based on a multimodal large language model, which learns both perception and reasoning abilities for multi-emotion prediction. Specifically, we design a parameter-efficient fine-tuning paradigm encompassing three task instructions: perception, reasoning, and prediction instruction. This paradigm involves a progressive process to perform targeted instructions within a domain for fine-tuning, thereby optimizing the model’s capabilities in image perception, cognitive reasoning, and multi-emotion prediction. Furthermore, to alleviate hallucinations of large models, a Reason-level Alignment Score (RAS) is introduced to guide the model toward closer alignment with human cognition. Experiments on four datasets demonstrate that our EReC method, which emulates the human cognitive process of viewing and interpreting images, employs progressive tuning to integrate the perceptual, reasoning, and predictive capabilities of large models, achieving superior performance.

关键词： Cognitive processes Large language models Predictive models signal processing Cognition Acoustics Speech processing Tuning

来源：评论

学校读者我要写书评

暂无评论

image Data Encryption Using des Method 1

Image Data Encryption Using des Method

引用

1st international conference on Computer Science and Artificial Intelligence, ICCSAI 2021

作者： Bastanta, Artha Nuryansyah, Ramadhany Nugroho, Christian Aditya Budiharto, Widodo Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Data encryption has been considered as a way to secure data that is stored either on personal computers or on the internet such as cloud storage and cloud computing. Because advances in data storage technology, the main problem that is often faced is data security, so we apply the concept of data encryption using the DES method. by analyzing using the DES method is the safest data encryption process for safeguarding data stored on personal computers and on the internet. based on the application that has been designed using the DES Algorithm with input in the form of an image, it can successfully encrypt the image. © 2021 ieee.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

InvGS: a Novel Real-Time Inverse Rendering Framework Utilizing 3D Gaussian Splatting

InvGS: a Novel Real-Time Inverse Rendering Framework Utilizi...

引用

international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Yang Pu Qingfeng Wu School of Film Xiamen University Xiamen China Xiamen University Xiamen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In this paper, we address the problem of reconstructing geometry, material and illumination from multi-view images of a scene captured in an unknown environment. Compared to prevalent NeRF-based methods, which are typically hindered by slow training and time-intensive evaluating, our approach capitalizes on recent advancements in Volume Rendering: point-based 3D Gaussian Splatting (3DGS) techniques. However, the inherent lack of geometric priors in this point-based representation and the material-lighting ambiguity of the radiance field make it intractable for inverse rendering tasks. To overcome this challenge, our method adopt a two-step approach which we call InvGS. First, our method optimize the original parameters of the initial 3DGS point cloud using flattening and alignment regularization to make the Gaussians closer to the object surfaces for reconstructing a more compact geometry. In the second stage, our method jointly optimize lighting and material parameters of 3DGS point cloud through the differentiable rendering process, thereby following the physically-based rendering equation. Benefiting from the fast rasterization of 3DGS and real-time rendering techniques in physically-based rendering, InvGS can reasonably shade each Gaussian under image-based HDR illumination without compromising real-time performance. We demonstrate that our method is comparable to the state of the arts, and even outperform classic and deep learning-based approaches.

关键词： Point cloud compression Geometry Training Three-dimensional displays Lighting Rendering (computer graphics) Real-time systems Vectors image reconstruction Surface treatment

来源：评论

学校读者我要写书评

暂无评论

Real Object Registration Algorithm based on SURF and RANSAC 18

Real Object Registration Algorithm Based on SURF and RANSAC

引用

18th ieee international conference on Networking, Sensing and Control, ICNSC 2021

作者： Dai, Chuyi Liu, Ding Hu, Weihao Xidian University Intelligent Robot Laboratory Hangzhou Institute of Technology Hangzhou China Xidian University School of Mechano-Electronic Engineering Xi'an China

ISBN: (纸本)9781665440486

In recent years, with the rapid development of smartphone devices and mobile cellular network technology, real-time virtual reality feedback software and games based on mobile phone cameras have developed rapidly. However, current existing real-scene item matching algorithms usually need to rely on internet connections or require the high-performance computing power of devices to meet the demand. For this reason, this paper proposes a real-scene item registration algorithm based on the SURF algorithm, which has the advantages of good real-time performance, low calculation amount, and easy implementation. It can be adopted and further developed in real-scene software for item recognition and registration used in games and intelligent robots. © 2021 ieee.

关键词： image registration

来源：评论

学校读者我要写书评

暂无评论

ECG R-R Interval Automatic Detection Using IOT

ECG R-R Interval Automatic Detection Using IOT

引用

North Karnataka Subsection Flagship international conference (NKCon), ieee

作者： T. Preethi Shanmuga Priya. S Arun Patrick K Swagata Sarkar C. Jency N. Kumareshan Department of Computer science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of CSE Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technolog Chennai India Department of CSE Nehru Institute of Technology Coimbatore India Dept. of AIDS Sri Sairam Engineering College Chennai India Department of Information Technology Hindusthan College of Engineering and Technology India Department of ECE Sri Eshwar College of Engineering Kinathukadavu Coimbatore India

In this day and age, devotion to one's own body is one of the key factors taken into account. An electrical activity of the human heart is represented by the electrocardiogram (ECG) signal. Numerous heart disorders may be diagnosed using it. The tools that provide outcomes quickly while simultaneously maintaining accuracy. With the aid of the Raspberry Pi's cutting-edge technology and classification techniques, a multi-thread approach is provided to detect any falling event as well as the user's relative electrocardiogram (ECG) signal. Bluetooth or Wi-Fi are used for wireless connection, which gives embedded devices flexibility and extensibility. This project's objective is to classify an ECG signal into normal and pathological classifications in order to identify the kind of arrhythmia. Artificial neural networks (ANNs) are used to diagnose cardiac arrhythmia diseases in order to do this. Using MATLAB, EMB (empirical mode decomposition) approach is used to accurately classify ECG signals. Measures including mean squared error (MSE), classification specificity, sensitivity, accuracy, and precision are used to assess the classification performance. The classifier reaches a 100% accuracy rate. It has been investigated how image processing works in IOT-based systems. A variety of technologies based on image processing become a part of IOT-based applications. The article provides a summary of the function of image processing in IOT based intelligent systems in several application fields. The Work might be beneficial for creating and experimenting with the new image processing applications in IOT-based systems.

关键词： Backpropagation Heart Wireless communication Training Wireless sensor networks Heart beat image processing

来源：评论

学校读者我要写书评

暂无评论

CabiNet: A Deep Learning Framework for Multiclass Medical image Segmentation from Multiple Single Class Datasets

CabiNet: A Deep Learning Framework for Multiclass Medical Im...

引用

international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Aman Soni Ishita Maiti Nirmalya Ghosh Electrical Engineering IIT Kharagpur Kharagpur India School of Medical Science and Technology IIT Kharagpur Kharagpur India

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The development of deep learning based image segmentation algorithms is often hindered by the lack of adequately annotated datasets, and this issue becomes a severe bottleneck in multi-class segmentation. The models can learn binary image segmentation since the datasets are often labeled for a single class. However, the task becomes more challenging for multi-class annotations and segmentation of regions of interest, e.g., multi-organ segmentation that plays a vital role in computer-assisted diagnosis, surgery planning, and other related applications. This study proposes a framework, CabiNet, that attempts to solve data bottleneck by learning multi-class healthy organ segmentation from partially annotated abdominal MRI data, i.e., multiple single-class datasets. Multiple organ specific expert networks and a Jack of All (JoA) network are trained to generate posterior probability maps of individual organs simultaneously which are accumulated to get the final posterior probability distributions over different organs for each pixel. On benchmark Combined Healthy Abdominal Organ Segmentation (CHAOS) MRI dataset CabiNet yielded very promising dice scores: liver (90.39%), right kidney (87.41%), left kidney (81.09%), spleen (90.78%) and overall average dice score as 87.4%.

关键词： Deep learning image segmentation Annotations Magnetic resonance imaging Posterior probability Surgery Benchmark testing Medical diagnostic imaging Kidney Tuning

来源：评论

学校读者我要写书评

暂无评论

Perceptually Optimized Loss Function for image Super-Resolution 7

Perceptually Optimized Loss Function for Image Super-Resolut...

引用

7th international conference on signal Processing and Intelligent systems, ICSPIS 2021

作者： Arezoomand, Amirhossein Cheraaqee, Poorya Mansouri, Azadeh Kharazmi University Department of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9781665409384

Most of the learning based single image super-resolution networks employ intensity loss which measures pixel-wise difference between the estimated high resolution image and the ground truth. Since image components are different with respect to their saliency for HVS, it is desired to weight their impact on the loss functions accordingly. In this paper, a simple perceptual loss function is introduced based on the JPEG compression algorithm. In fact, the two compared images are transformed into DCT domain and then divided by the weighted quantization matrix. The difference between the resultant DCT coefficients shows the most effective components for HVS and can be considered as a perceptual loss function. The experimental results illustrate that employing the proposed loss promotes the convergence speed, and also, provides better outputs in terms of qualitative and quantitative measures. © 2021 ieee.

关键词： image compression

来源：评论

学校读者我要写书评

暂无评论

A 3D image-domain Filter for Refraction Compensation of Penetrating MIMO Stereoscopic imagery 6

A 3D Image-domain Filter for Refraction Compensation of Pene...

引用

6th international conference on signal and image Processing, ICSIP 2021

作者： Xu, Zhuo Jin, Tian National University of Defense Technology College of Electronic Science and Technology Changsha China

ISBN: (纸本)9780738133737

Autofocusing of MIMO penetrating radar is a recent developing method to obtain precisely-located and well-focused image in unknown environment. However, the ergodic search process in the sub focusing process greatly increases the amount of calculation and an inevitable error of target position will be introduced when two-dimensional (2-D) image is used to represent three-dimensional (3-D) space, which limits the application of traditional autofocusing in practice. To solve the problem, we introduce a 3D-image-domain-filter-based method. All the compensation and correction are based on stereoscopic image domain, and it avoids calculating the position of the refraction point, which saves much time of computation. Both the simulation and the measurement experiments in the paper show the method can complete the compensation precisely, offers better focusing quality and obtain an accurate estimation of the environment parameters. © 2021 ieee.

关键词： Stereo image processing

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 << < 454 455 456 457 458 459 460 461 462 463 > >>

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：