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

78,699 篇 会议
791 篇 期刊文献
326 册 图书
2 篇 学位论文

馆藏范围

79,818 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

49,796 篇 工学
- 29,044 篇 计算机科学与技术...
- 23,040 篇 电气工程
- 16,838 篇 软件工程
- 16,506 篇 信息与通信工程
- 5,194 篇 电子科学与技术（可...
- 4,826 篇 光学工程
- 4,536 篇 控制科学与工程
- 3,432 篇 生物医学工程（可授...
- 3,097 篇 机械工程
- 2,843 篇 仪器科学与技术
- 2,051 篇 生物工程
- 699 篇 化学工程与技术
- 558 篇 材料科学与工程（可...
- 521 篇 动力工程及工程热...
- 511 篇 航空宇航科学与技...
- 510 篇 交通运输工程
- 499 篇 安全科学与工程
- 494 篇 网络空间安全
19,891 篇 理学
- 12,187 篇 物理学
- 7,864 篇 数学
- 2,310 篇 生物学
- 2,211 篇 统计学（可授理学、...
- 1,567 篇 系统科学
- 899 篇 化学
10,909 篇 医学
- 10,426 篇 临床医学
- 1,072 篇 基础医学(可授医学...
- 1,057 篇 特种医学
- 694 篇 药学(可授医学、理...
3,247 篇 管理学
- 2,018 篇 管理科学与工程(可...
- 1,356 篇 图书情报与档案管...
391 篇 农学
350 篇 法学
286 篇 军事学
177 篇 经济学
118 篇 教育学
117 篇 文学
67 篇 艺术学

主题

7,223 篇 image processing
6,650 篇 signal processin...
5,258 篇 image coding
5,022 篇 image segmentati...
4,064 篇 image reconstruc...
3,853 篇 signal processin...
3,198 篇 feature extracti...
2,242 篇 image analysis
1,996 篇 digital signal p...
1,708 篇 robustness
1,691 篇 image edge detec...
1,680 篇 cameras
1,647 篇 training
1,628 篇 deep learning
1,588 篇 speech processin...
1,462 篇 pixel
1,422 篇 image resolution
1,382 篇 image enhancemen...
1,332 篇 image color anal...
1,187 篇 visualization

机构

53 篇 university of sc...
49 篇 univ chinese aca...
41 篇 department of si...
40 篇 institute for in...
40 篇 shanghai jiao to...
39 篇 tsinghua univers...
38 篇 school of electr...
38 篇 shanghai jiao to...
36 篇 national institu...
36 篇 school of comput...
34 篇 princeton univ d...
34 篇 beijing inst tec...
33 篇 ibm thomas j. wa...
33 篇 shenzhen interna...
30 篇 institute of inf...
30 篇 beijing key labo...
28 篇 zhejiang univers...
27 篇 nanyang technol ...
27 篇 centre for multi...
27 篇 astar inst infoc...

作者

51 篇 zhang lei
46 篇 wiegand thomas
40 篇 yang bin
33 篇 jie yang
32 篇 jing zhang
32 篇 kaup andre
31 篇 m. vetterli
29 篇 vetterli martin
29 篇 m. gabbouj
28 篇 li li
27 篇 guangtao zhai
27 篇 li xin
27 篇 wang jing
26 篇 karam lina j.
25 篇 jian wang
24 篇 zhang tao
24 篇 m.j.t. smith
24 篇 li yang
24 篇 jun wang
23 篇 kuo c. -c. jay

语言

77,938 篇 英文
1,073 篇 其他
503 篇 土耳其文
289 篇 中文
9 篇 俄文
5 篇 西班牙文
2 篇 法文
1 篇 葡萄牙文

检索条件"任意字段=IEEE International Conference on Signal and Image Processing Applications"

共 79818 条记录，以下是4711-4720 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：

Deep Computational Based Blocking Effect Cancellation for Digital image Compression 4

Deep Computational Based Blocking Effect Cancellation for Di...

引用

4th international conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Shahila, D. Ferlin Deva Stephen, Valantina Rama, R Senthil Prathaban, Banu Priya Rubia, J. Jency Reddy, Sura Rakesh Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Saveetha School of Engineering Department of Eee Thandalam Chennai India Dmi College of Engineering Department of Eee Palanchur Chennai India School of Computing Srm Institute of Science and Technology Department of Networking and Communication Kattankulathur Chennai India

ISBN: (纸本)9798331508845

Large multimedia-based applications need that academics find a more effective approach to use images in their apps as image data continues to grow. image quality evaluation is crucial in image processing systems, especially when images are compressed for transmission. Because of the blocking effect that co-efficient quantification causes during image compression, the decompressed image has poor quality. The coefficient quantification of blocking effect removes high frequency component in the image, consecutively results in discontinuous leaps and reduces the quality of the image. Generally, the objective function is used to perform optimization on complex image processing task. Compression artefacts, noise, and designed linear or non-linear degradations in compressed images. To recover linear and nonlinear distortion from distorted images, image de-blocking techniques are applied. Deblocking techniques accepted by police and vigilance division to improve valuable evidences via ruined pictures of observations. An ordinary encoding and decoding quality characteristic of most digital images is the neighboring pixels that are related and subsequently extracts the unwanted disturbances. Our primary goal is to identify the less correlated representation of the digital photos through our research. There are three steps in our proposed approach, step 1 is the statistical feature removal using curvelet transform, then step 2 is the down-sampling of the image with blocking effect artefacts, finally step 3 is the usage of Quality Defined Convolutional Neural Network (QD-CNN) for the removal of blocking effect artefacts then finally the performance validation is carried out using quality assessment. © 2024 ieee.

关键词： image compression

来源：评论

学校读者我要写书评

暂无评论

Prediction of Most Confident Labelled Output for Fashion image using Deep Learning Model with Tensorflow

Prediction of Most Confident Labelled Output for Fashion Ima...

引用

2024 international conference on Advances in Data Engineering and Intelligent Computing Systems, ADICS 2024

作者： Saranya, M.S. Geetha, P. Vel Tech Rangarajan Dr.Sagunthala R&d Institute Of Science And Technology Dept. Of Dcse Chennai Avadi India Anna University Dept. Of Dcse Ceg Chennai India

ISBN: (纸本)9798350364828

Fashion image classification is an emerging field of research. Examples of numerous e-commerce applications that rely on fashion image classification include recommendation systems, retrieval systems, and apparel recognition tasks. The extensive variety of clothing attributes, including designs, textures, and colours, and the high degree of clothing categorization present formidable challenges to the classification of clothing images. In this paper, a new algorithm called Most Confident Labelled Output (MCLO) algorithm has been proposed. Later, widely used optimization techniques in CNN models like SGD, Adam, AdaGrad and RMSProp are added for classifying the fashion images. Among the CNN optimizers, AdaGrad model achieved better accuracy as well as loss gets decreased. The proposed work was carried on benchmarking Fashion MNIST dataset The MCLO algorithm has been coded using tensorflow with graphics processing unit (GPU). The outcomes demonstrate that the proposed method outperforms state-of-the-art models, as assessed through the Fashion MNIST dataset benchmarks. © 2024 ieee.

关键词： image classification

来源：评论

学校读者我要写书评

暂无评论

Radar-based breathing sensor for child presence detection in automotive applications 67

Radar-based breathing sensor for child presence detection in...

引用

67th ieee international Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Gillner, Jonas Taylor, Roy Thelen, Klaus Ruhr West Univ Appl Sci Measurement & Sensor Technol Mulheim Germany Wayne State Univ Elect & Comp Engn Detroit MI USA

ISBN: (纸本)9798350387186;9798350387179

This study presents a novel sensor system aimed at preventing child heatstroke in unattended vehicles. The developed system integrates a 24 GHz Continuous Wave (CW) radar, engineered to detect the subtle breathing signals of infants. A custom-designed 4-by-1 patch array antenna, optimized for this specific application, is seamlessly embedded into a designed PCB. To enhance efficiency and accuracy, the system incorporates a low-cost 8-bit Microcontroller (MC) and a dedicated hardware filter. These components facilitate a tailored signal processing algorithm specifically designed for efficient and rapid computation of the child's Respiratory Rate (RR). The system's performance evaluation involved monitoring a sleeping infant's respiratory patterns in real-time. Collected data was then compared against established reference standards to assess the system's accuracy in detecting the child's RR, providing compelling evidence of its efficacy. Furthermore, the system has demonstrated compliance with automotive industry standards, assuring seamless integration into existing vehicle frameworks. This innovation holds significant potential to proactively enhance automotive safety standards.

关键词： radar sensor 24 GHz radar patch antenna child safety heatstroke prevention automotive safety vital signs monitoring breathing detection

来源：评论

学校读者我要写书评

暂无评论

Spaceborne SAR Ship Data Expansion Based on GAN 2

Spaceborne SAR Ship Data Expansion Based on GAN

引用

2nd international conference on image processing, Computer Vision and Machine Learning, ICICML 2023

作者： Jiang, Jiacheng Fang, Caiting Wang, Junrui Xie, Baorong Shanghai Academy of Spaceflight Technology Shanghai Institute of Aerospace Electronics Technology Shanghai China

ISBN: (纸本)9798350331417

In response to the lack of high-quality and sufficient synthetic aperture radar (SAR) data that can be paired with light ship images in practice, this paper proposes a method to convert optical ship images into SAR images based on GAN networks. In order to improve the coordination of generated images and stabilize the training process, this paper establishes a generator with a self-attention mechanism combined with spectral normalization operations. Secondly, the maximum spatial perturbation consistency loss is introduced to reduce the spatial changes between optical images and SAR images caused by changes in ship size and background noise. Finally, in order to speed up the convergence speed and stability of the model, a relative discriminator is introduced. Experiments conducted on the HRSID and LEVIR remote sensing ship data sets show that the FID (Fréchet Inception Distance) of the SAR ship images generated by this model is reduced to 57.25. At the same time, compared with the current optimal algorithm, the peak signal-to-noise ratio is increased by 5.89% on average. The structural similarity loss is increased by 18.75% on average, and the mean square error is reduced by 13.44% on average. © 2023 ieee.

关键词： data expansion image generation SAR ship image

来源：评论

学校读者我要写书评

暂无评论

AN UNSUPERVISED CROSS-MODAL HASHING METHOD ROBUST TO NOISY TRAINING image-TEXT CORRESPONDENCES IN REMOTE SENSING 29

AN UNSUPERVISED CROSS-MODAL HASHING METHOD ROBUST TO NOISY T...

引用

ieee international conference on image processing (ICIP)

作者： Mikriukov, Georgii Ravanbakhsh, Mahdyar Demir, Beguem Tech Univ Berlin Berlin Germany

ISBN: (数字)9781665496209

ISBN: (纸本)9781665496209

The development of accurate and scalable cross-modal image-text retrieval methods, where queries from one modality (e.g., text) can be matched to archive entries from another (e.g., remote sensing image) has attracted great attention in remote sensing (RS). Most of the existing methods assume that a reliable multi-modal training set with accurately matched text-image pairs is existing. However, this assumption may not always hold since the multi-modal training sets may include noisy pairs (i.e., textual descriptions/captions associated to training images can be noisy), distorting the learning process of the retrieval methods. To address this problem, we propose a novel unsupervised cross-modal hashing method robust to the noisy image-text correspondences (CHNR). CHNR consists of three modules: 1) feature extraction module, which extracts feature representations of image-text pairs;2) noise detection module, which detects potential noisy correspondences;and 3) hashing module that generates cross-modal binary hash codes. The proposed CHNR includes two training phases: i) meta-learning phase that uses a small portion of clean (i.e., reliable) data to train the noise detection module in an adversarial fashion;and ii) the main training phase for which the trained noise detection module is used to identify noisy correspondences while the hashing module is trained on the noisy multi-modal training set. Experimental results show that the proposed CHNR outperforms state-of-the-art methods.

关键词： cross-modal retrieval unsupervised contrastive learning remote sensing caption-noise

来源：评论

学校读者我要写书评

暂无评论

Video Surveillance Authentication: Real-Time ENF signal Hiding at the Edge 24

Video Surveillance Authentication: Real-Time ENF Signal Hidi...

引用

24th international conference on Digital signal processing, DSP 2023

作者： Lykourinas, Antonios Skodras, Athanassios Department of Electrical and Computer Engineering Faculty of Engineering University of Patras Patras Greece

ISBN: (纸本)9798350339598

Due to the significance of the visual information exchanged in Internet of Video Things (IoVT) networks, attackers are constantly launching new attacks and attempt to exploit new vulnerabilities. One of the most common and difficult-to-prevent attacks on the Visual Layer is the Frame Duplication Attack (FDA). Recently, two techniques were proposed for FDA detection at the edge by using the embedded Electrical Network Frequency (ENF) signals in an effort to surpass limitations of conventional passive methods. In this paper, a Real-Time ENF signal hiding technique at the edge is proposed. Our motivation is to examine the possibility of authenticating the surveillance feed by hiding the ENF signal. Experiments are conducted, including an extensive performance comparison between the proposed and reference encoder, a feasibility study for the proposed encoder's integration to a Raspberry Pi for video streaming purposes and finally the implementation of a proof-of-concept prototype. According to the findings, the proposed approach provides real-time FDA detection at reduced computational complexity and hardware requirements, thus rendering this method appropriate for applications at the edge. © 2023 ieee.

关键词： Security systems

来源：评论

学校读者我要写书评

暂无评论

Advancements in Fisheye Lens image Stitching for Enhanced ADAS in Automated Vehicles 7

Advancements in Fisheye Lens Image Stitching for Enhanced AD...

引用

7th ieee international conference on Computational Systems and Information Technology for Sustainable Solutions, CSITSS 2023

作者： Harsha Vardhan, K. Hegde, Vinay Rv College of Engineering Department of Computer Science Bangalore India

ISBN: (纸本)9798350343144

As Advanced Driver Assistance Systems (ADAS) become integral to the functionality of automated vehicles, the demand for comprehensive and distortion-free visual information is paramount. This survey paper meticulously examines the realm of image stitching utilizing fisheye lenses to cater to the unique needs of ADAS applications. Drawing insights from an extensive analysis of pertinent research papers, this survey delves into the diverse spectrum of techniques devised to enhance fisheye lens image stitching. Key focal points include the rectification of fisheye lens distortion, mitigation of image duplication artifacts, and the seamless synthesis of stitched images. Embracing advancements in computer vision, image processing, and the utilization of OpenGL-based rendering techniques, this survey encapsulates the evolving landscape of image stitching for ADAS in automated vehicles. By dissecting the challenges inherent to distortion correction and object duplication removal, this paper uncovers the progressive strategies employed to elevate the accuracy and visual fidelity of stitched images in the context of ADAS. With a comprehensive synthesis of existing research, this survey serves as an indispensable compass for researchers, engineers, and practitioners navigating the intricate domain of image stitching within the realm of automated vehicle system. © 2023 ieee.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

image based Reversible Data Hiding using Multiple image Layer 5

Image based Reversible Data Hiding using Multiple Image Laye...

引用

5th international conference on Inventive Research in Computing applications, ICIRCA 2023

作者： Rana, Pratham Singh Kalpana Chahat Singh, Bhupinder Singla, Sanjay Kaur, Charnpreet Chandigarh University Department of Computer Science and Engineering Punjab India

ISBN: (纸本)9798350321425

Reversible Data Hiding (RDH) is a widely used method to embed data into digital images while preserving the integrity of the original image. The idea behind RDH is to allow decoding of embedded data while the cover image remains unchanged. This technique is particularly useful in applications where the original image must be preserved, such as medical image processing and authentication. The main objective of RDH is to maximize the delivered power and at the same time minimize the distortion due to the delivery process. Different embedding techniques have been proposed to achieve high embedding power and low distortion. These techniques include difference expansion, histogram transformation, and prediction error expansion. These methods change the pixel values of the cover image to accommodate the hidden data. The extracted key is then used to restore the original pixel values, allowing the original image to be restored. This paper proposes a new RDH algorithm that achieves high embedding power with low distortion and high security. The proposed algorithm uses a combination of image layers, encryption and histogram shift to embed the data. The suggested technique shows promising results in terms of embedding power, image quality, and computing complexity while maintaining a low amount of distortion and low computational cost, making it appropriate for real-time applications and promising results in terms of embedding power, image quality and computational complexity. The future direction of RDH research is to explore new immersive technologies and applications in various fields such as security, forensics and multimedia communication © 2023 ieee.

关键词： Restoration

来源：评论

学校读者我要写书评

暂无评论

HARDLESS: A Generalized Serverless Compute Architecture for Hardware processing Accelerators 10

HARDLESS: A Generalized Serverless Compute Architecture for ...

引用

10th ieee international conference on Cloud Engineering (IC2E)

作者： Werner, Sebastian Schirmer, Trever TU Berlin ISE Berlin Germany TU Berlin MCC Berlin Germany TU Berlin ECDF Berlin Germany

ISBN: (数字)9781665491150

ISBN: (纸本)9781665491150

The increasing use of hardware processing accelerators tailored for specific applications, such as the Vision processing Unit (VPU) for image recognition, further increases developers' configuration, development, and management overhead. Developers have successfully used fully automated elastic cloud services such as serverless computing to counter these additional efforts and shorten development cycles for applications running on CPUs. Unfortunately, current cloud solutions do not yet provide these simplifications for applications that require hardware acceleration. However, as the development of specialized hardware acceleration continues to provide performance and cost improvements, it will become increasingly important to enable ease of use in the cloud. In this paper, we present an initial design and implementation of HARDLESS, an extensible and generalized serverless computing architecture that can support workloads for arbitrary hardware accelerators. We show how HARDLESS can scale across different commodity hardware accelerators and support a variety of workloads using the same execution and programming model common in serverless computing today.

关键词： serverless engineering accelerated computing

来源：评论

学校读者我要写书评

暂无评论

MRI Based Brain Tumor Detection Comprising a Hybrid Segmentation Technique

MRI Based Brain Tumor Detection Comprising a Hybrid Segmenta...

引用

2024 international conference on Decision Aid Sciences and applications, DASA 2024

作者： Akonda, Jasim Alvi, Syada Tasmia Era, Chowdhury Abida Anjum Mitu, Sadia Jannat Uddin, Mohammed Nasir Jagannath University Dept. of CSE Dhaka Bangladesh Daffodil International University Dept. of CSE Dhaka Bangladesh Fachhochschule Dortmund Dept. of CSE Dortmund Germany

ISBN: (纸本)9798350369106

The growth of abnormal tissue in the brain causes brain tumors. There are two main types of tumors, such as-non-cancerous (benign) and cancerous (malignant). Because of the several unique types of brain tumors, it is difficult to forecast the survival of a patient. Tumor classification and detection is a vital sector in medical science and diagnosis of patients. The usual technique of detecting brain tumors is a Magnetic Resonance Imaging (MRI) scan. However, it is an iterative and human interactive task that greatly varies depending on the personal expertise of radiologists and clinical experts. Simple image processing method sometime fails to expose the problem of the human organ. In this issue, researchers are trying to adopt the emerging techniques of Machine Learning, and they overcome many challenging issues by using Machine Learning (ML) algorithms. This work implies the detection and classification of MRI brain tumors by feature extraction and ML classifiers. After prepeocessing and feature extract of MRI image classifiers are applied. Laplacian filter, Discrete Wavelet Transformation, and Principal Component Analysis are used for the preprocessing stage. Finally, kernel support vector machine (KSVM) is used to effectively detect and classify brain tumors as benign or malignant with an accuracy of 89%. This research has thrown light on the field of diagnosing brain tumors. © 2024 ieee.

关键词： Discrete wavelet transforms

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 << < 468 469 470 471 472 473 474 475 476 477 > >>

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：