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

12,617 篇 会议
197 篇 期刊文献
163 册 图书
1 篇 学位论文

馆藏范围

12,978 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

6,573 篇 工学
- 4,314 篇 计算机科学与技术...
- 2,196 篇 软件工程
- 1,915 篇 电气工程
- 1,290 篇 信息与通信工程
- 822 篇 控制科学与工程
- 664 篇 光学工程
- 460 篇 生物医学工程（可授...
- 450 篇 电子科学与技术（可...
- 446 篇 机械工程
- 421 篇 仪器科学与技术
- 316 篇 生物工程
- 241 篇 测绘科学与技术
- 157 篇 材料科学与工程（可...
- 149 篇 航空宇航科学与技...
- 134 篇 交通运输工程
- 102 篇 安全科学与工程
- 87 篇 网络空间安全
3,179 篇 理学
- 2,128 篇 物理学
- 907 篇 数学
- 358 篇 生物学
- 244 篇 系统科学
- 225 篇 统计学（可授理学、...
- 120 篇 化学
1,431 篇 医学
- 1,268 篇 临床医学
- 196 篇 特种医学
- 158 篇 基础医学(可授医学...
- 101 篇 药学(可授医学、理...
695 篇 管理学
- 421 篇 管理科学与工程(可...
- 295 篇 图书情报与档案管...
- 86 篇 工商管理
58 篇 农学
56 篇 法学
29 篇 教育学
27 篇 文学
26 篇 经济学
18 篇 军事学
17 篇 艺术学
1 篇 哲学

主题

2,646 篇 image processing
1,385 篇 image segmentati...
1,141 篇 signal processin...
612 篇 cameras
594 篇 feature extracti...
585 篇 image edge detec...
530 篇 signal processin...
465 篇 image reconstruc...
464 篇 image coding
462 篇 real-time system...
386 篇 algorithm design...
334 篇 image color anal...
310 篇 deep learning
307 篇 pixel
305 篇 image enhancemen...
299 篇 real time system...
293 篇 object detection
289 篇 computer archite...
285 篇 hardware
284 篇 neural networks

机构

22 篇 signal and image...
19 篇 samara national ...
14 篇 school of electr...
11 篇 samara national ...
11 篇 univ texas san a...
11 篇 department of el...
11 篇 school of electr...
10 篇 center for signa...
9 篇 information syst...
9 篇 institute of ima...
9 篇 university of to...
9 篇 tongji universit...
8 篇 purdue univ sch ...
8 篇 university of ch...
8 篇 electrical compu...
8 篇 image processing...
8 篇 information syst...
8 篇 samara national ...
8 篇 lockheed martin ...
7 篇 school of electr...

作者

19 篇 anon
13 篇 de-shuang huang
12 篇 jagdish chand ba...
11 篇 p. pirsch
10 篇 jie yang
10 篇 panetta karen
10 篇 j.m. mendel
10 篇 r. chellappa
10 篇 a. ortega
9 篇 c.-c.j. kuo
8 篇 frank hannig
8 篇 hannig frank
8 篇 ilias maglogiann...
8 篇 carli m.
7 篇 miller jwv
7 篇 busch christoph
7 篇 semenishchev e.
7 篇 zelensky a.
7 篇 bovik alan c.
7 篇 jerry m. mendel

语言

12,679 篇 英文
211 篇 其他
75 篇 中文
20 篇 土耳其文
3 篇 葡萄牙文
2 篇 德文
2 篇 俄文
1 篇 西班牙文
1 篇 法文

检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VII"

共 12978 条记录，以下是221-230 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：

Temporal Deep Learning image processing Model for Natural Gas Leak Detection Using OGI Camera

Temporal Deep Learning Image Processing Model for Natural Ga...

引用

2024 Offshore Technology conference Asia, OTCA 2024

作者： Korjani, Mehdi Conley, David Smith, Mark Clean Connect Inc DenverCO United States

ISBN: (纸本)9781959025030

Natural gas extraction systems often encounter manufacturing defects or develop defects over time, leading to gas leaks. These leaks pose challenges, causing revenue losses and environmental pollution. Detecting gas leaks in the vast array of extraction, transfer, and storage equipment within these systems can be arduous, allowing leaks to persist unnoticed. Additionally, natural gas leaks are not visible to naked eyes, further complicating their detection. We developed a novel deep learning image processing model that utilizes videos captured by a specialized Optical Gas Imaging (OGI) camera to detect natural gas leaks. The temporal deep learning algorithm is designed to identify patterns associated with gas leaks and improve its performance through supervised learning. Our model incorporates algorithms to detect background environments, motion, equipment, and classify gas leaks. Our model employs leak identification algorithms to determine the presence of gas leaks. These algorithms calculate the probability of detected motion indicating a gas leak based on long-term and short-term background subtraction, detected motion, motion duration, equipment location, and telemetry data. To minimize false positives, we have developed image segmentation and object detection models to identify known objects, such as equipment, people, and cars, within the video footage. To train our model we collect more than 10,000 short videos from real fields and include simulated data with known rate controlled gas release in different situations. Data consist of wide range of weather situations including different temperature, wind speed, humidity in sunny, rainy, and snowy fields. We validated our model by conducting experiments involving actual footage from the field. The model achieved a 98% true positive rate, and a 100% true negative rate, correctly refraining from sending an alarm for all non-releases. Additionally, we developed a postprocessing algorithm capable of estimating the

关键词：

来源：评论

学校读者我要写书评

暂无评论

Automatic summarization of Instagram social network posts by combining semantic and statistical approaches 6

Automatic summarization of Instagram social network posts by...

引用

6th International conference on Pattern Recognition and image Analysis (IPRIA)

作者： Tabanmehr, Zainab Akhtarkavan, Ehsan Khatam Univ Dept Comp Engn Tehran Iran

ISBN: (纸本)9798350314557

The increasing spread of data and text documents such as articles, web pages, books, posts on social networks, etc. on the Internet, creates a fundamental challenge in various fields of text processing under the title of "automatic text summarization". Manual processing and summarization of large volumes of textual data is a very difficult, expensive, time-consuming, and impossible process for human users. Text summarization systems are divided into extractive and abstract categories. In the extractive summarization method, the final summary of a text document is extracted from the important sentences of the same document without any kind of change. In this method, it is possible to repeat a series of sentences repeatedly and interfere with pronouns. But in the abstract summarization method, the final summary of a textual document is extracted from the meaning of the sentences and words of the same document or other documents. Many of the performed works have used extraction methods or abstracts to summarize the collection of web documents, each of which has advantages and disadvantages in the results obtained in terms of similarity or size. In this research, by developing a crawler, extracting the popular text posts from the Instagram social network, suitable pre-processing, and combining the set of extractive and abstract algorithms, the researcher showed how to use each of the abstract algorithms. and used extraction as a supplement to increase the accuracy and accuracy of another algorithm. Observations made on 820 popular text posts on the Instagram social network show the accuracy (80%) of the proposed system.

关键词： text summarization extractive approach abstract approach natural language processing social networks

来源：评论

学校读者我要写书评

暂无评论

An Effective Threshold Based Technique for Retinal image Blood Vessel Segmentation on Fundus image Using Average and Gaussian Filters 2nd

An Effective Threshold Based Technique for Retinal Image Blo...

引用

2nd International conference on Computing, Communication, and Learning, CoCoLe 2023

作者： Ray, Rahul Jena, Sudarson Parida, Priyadarsan SUIIT Sambalpur University Odisha Burla768018 India SUIIT Sambalpur University Odisha Burla768018 India GIET University Odisha Gunupur765022 India

ISBN: (纸本)9783031569975

The fundamental components of automated retinal blood vessel segmentation for eye disease screening systems are segmentation algorithms, retinal blood vessel datasets, classification algorithms, performance measure parameters and noise removing filters etc. This paper is presenting retinal blood vessel segmentation techniques on 2D retinal images captured by fundus camera and examining the performance of different algorithms for a better and accurate result. The goal of this study is to comprehensively investigate and assess retinal blood vessel extraction algorithms using publicly accessible High-Resolution Fundus Diabetic Retinopathy (HRF-DR) and Iowa Normative Set for processing images of the retina-artery vein ratio (INSPIRE-AVR) datasets, with a focus on important performance measurements and characteristics. The effectiveness of the proposed methodology is measured using the performance metrics like Sensitivity, Specificity and Accuracy with 94.27%, 87.86% and 95.61% for HRF-DR dataset and 91.10%, 86.97% and 95.16% for INSPIRE-AVR dataset respectively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Comparative Study of image processing Neural Networks using Face Mask Dataset 1

Comparative Study of Image Processing Neural Networks using ...

引用

1st IEEE International conference on Advances in Electronics, Communication, Computing and Intelligent Information systems, ICAECIS 2023

作者： Sunny Jindal, Rajni Delhi Technological University Department of Computer Science & Engineering Delhi India

ISBN: (纸本)9798350348057

Over the years there has been huge improvements in the performance of image processing algorithms due to increase in computation power of Devices as well as use of Neural Networks. This paper focuses on comparison of size and performance of different image Classification networks used widely. Each one of the machine learning models studied presents a new technique to process the input images that might be useful in different scenarios. Our main focus is to identify the framework with low latency, high accuracy as they can be used practically in surveillance equipment's that need to be fast and accurate. © 2023 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Realtime Scene Enhancement of Low Light image/Video 5

Realtime Scene Enhancement of Low Light Image/Video

引用

5th International conference on Intelligent Computing and Human-Computer Interaction, ICHCI 2024

作者： Zeng, Huixia Xiao, Ping School of Electronic and Information Engineering Guangzhou City University of Technology Guangdong Guangzhou510800 China

ISBN: (纸本)9798350368284

The quality of image and videos plays a vital role in case of real-Time systems. images are captured without sufficient illumination, lead to low dynamic range and high propensity for generating high noise levels. The processing ideas and networks of several mainstream low-light image enhancement neural network algorithms such as DRBN, DSLR, ZeroDCE, EnlightenGAN, as well as the key technologies used are compared and analyzed. In this paper, the EnglightenGAN neural network is used as the core image enhancement algorithm, and NVIDIA AGX Xavier equipment and video stream processing technology are used to achieve the entire process of video acquisition, video frame encoding, image enhancement processing, frame decoding, and video stream display. It can adapt to most low-light and dark scenes which has a good enhancement effect on video streams collected in low-light scenes. The real-Time performance and image enhancement effect of the system achieved good results, with FPS reaching 10, SSIM reaching 0.51753, and PSNR reaching 27.89973. © 2024 IEEE.

关键词： Video streaming

来源：评论

学校读者我要写书评

暂无评论

Research on Machine Vision Intelligent Detection System Based on Faster R-CNN 4

Research on Machine Vision Intelligent Detection System Base...

引用

4th IEEE International conference on Data Science and Computer Application, ICDSCA 2024

作者： Wang, Xueting Zeng, Fanshuo Song, Weizhao Zhang, Zhipeng He, Huitong Zhou, Zheyuan Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350368239

With the rapid development of artificial intelligence technology, visual inspection and image processing algorithms have been continuously improved in accuracy and efficiency, and intelligent inspection systems based on machine vision have been widely used in product quality control, defect detection and process monitoring. In this paper, a machine vision intelligent inspection system based on Faster Region-based Convolutional Network (Faster R-CNN) is proposed, which aims to improve the detection accuracy and efficiency. In this paper, the overall architecture of the system is introduced, including the image acquisition module, the data preprocessing module and the detection module based on Faster R-CNN. In the data preprocessing module, the Deep Convolution Generative Adversarial Networks (DCGAN) algorithm was proposed for image expansion generation, and high-resolution image samples that were basically consistent with the collected image datasets were obtained. Then, the Faster R-CNN model was optimized and adjusted for specific application scenarios, so that the average accuracy (mAP) of the model reached 78.23% and the FPS value reached 11.0. ©2024 IEEE.

关键词： Faster R-CNN image processing image recognition Machine vision intelligent inspection system

来源：评论

学校读者我要写书评

暂无评论

Research on image Sharpness Evaluation in Microstructure processing

Research on Image Sharpness Evaluation in Microstructure Pro...

引用

2024 IEEE International conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2024

作者： Zhang, Jiajun Wang, Zhe Li, Yiquan Xu, Jinkai Changchun University of Science and Technology Ministry of Education Key Laboratory for Cross-Scale Micro and Nano Manufacturing College of Mechanical and Electrical Engineering China Changchun University of Science and Technology School of Life Science and Technology China

ISBN: (纸本)9798350362107

To address issues of insufficient sensitivity and weak anti-noise characteristics in existing image sharpness evaluation algorithms, we propose a method combining local variance and gradient analysis. Traditional methods like the Tenengrad function use horizontal and vertical gradient values, while multi-directional gradients can increase noise sensitivity and false detections. Our approach integrates the Tenengrad function with gray variance processing, analyzing the deviation of each pixel's brightness from the average to distinguish content from background. Normalizing these values helps reduce background and impurity pixel influence. Preprocessing with an anisotropic diffusion filter smooths the image while preserving edges. Experimental results show this method offers higher sensitivity and better noise resistance than traditional functions, suitable for autofocus systems. © 2024 IEEE.

关键词： Anisotropy

来源：评论

学校读者我要写书评

暂无评论

A study on advancing Edge Detection and Geometric Analysis through image processing 24

A study on advancing Edge Detection and Geometric Analysis t...

引用

8th International conference on Graphics and Signal processing

作者： Hamza, Syed Amir Jesser, Alexander Heilbronn Univ Heilbronn Germany Heilbronn Univ Professorship Embedded Syst & Commun Engn Heilbronn Germany

ISBN: (纸本)9798400717024

In the realm of Printed Circuit Board (PCB) manufacturing, the alignment process is pivotal for ensuring the functional integrity of the final product. Traditional image measurement techniques, while foundational, often fall short of achieving the high degree of accuracy and precision necessary for today's complex PCB designs. This research presents a novel approach that significantly enhances measurement accuracy through the application of optimized image processing techniques. By leveraging advanced algorithms within the OpenCV library, we introduce a methodology that accurately transforms pixel coordinates into real-world measurements, crucial for precise PCB alignment. Our technique employs edge detection algorithms such as Canny, Sobel, and Prewit filters, combined with a machine learning model that adapts to variations in real-time imaging conditions. The study delineates the development of a user-friendly graphical interface that streamlines the measurement process, making it accessible for practical industrial application. Results from experimental validations indicate a substantial improvement in measurement precision, with a demonstrable reduction in alignment errors compared to conventional methods. This leap forward not only promises to elevate the standards of PCB manufacturing but also opens avenues for similar advancements in other domains where image measurement is essential. The implications of this work are far-reaching, with the potential to significantly boost the efficiency and reliability of electronic manufacturing processes globally.

关键词： image measurement techniques microns edge detection algorithms real-world coordinate transformation machine learning in imaging graphical user interface (GUI) Printed Circuit Board (PCB)

来源：评论

学校读者我要写书评

暂无评论

High-Fidelity Audio Compression with Improved RVQGAN 37

High-Fidelity Audio Compression with Improved RVQGAN

引用

37th conference on Neural Information processing systems (NeurIPS)

作者： Kumar, Rithesh Seetharaman, Prem Luebs, Alejandro Kumar, Ishaan Kumar, Kundan Descript Inc San Francisco CA 94118 USA

ISBN: (纸本)9781713899921

Language models have been successfully used to model natural signals, such as images, speech, and music. A key component of these models is a high quality neural compression model that can compress high-dimensional natural signals into lower dimensional discrete tokens. To that end, we introduce a high-fidelity universal neural audio compression algorithm that achieves 90x compression of 44.1 KHz audio into tokens at just 8kbps bandwidth. We achieve this by combining advances in high-fidelity audio generation with better vector quantization techniques from the image domain, along with improved adversarial and reconstruction losses. We compress all domains (speech, environment, music, etc.) with a single universal model, making it widely applicable to generative modeling of all audio. We compare with competing audio compression algorithms, and find our method outperforms them significantly. We provide thorough ablations for every design choice, as well as open-source code and trained model weights. We hope our work can lay the foundation for the next generation of high-fidelity audio modeling.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

Empirical Analysis of Denoising algorithms for CCTV Face images

Empirical Analysis of Denoising Algorithms for CCTV Face Ima...

引用

International conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Bhagwat, Sumedha Rahul Ragha, Leena Ramrao Adik Inst Technol Dept Comp Engn Navi Mumbai India

ISBN: (纸本)9789819984756;9789819984763

image denoising is a critical task in image processing that involves the removal of noise or unwanted distortions from an image while preserving its essential features. Most of the commonly captured pictures are obtained using mobile cameras or CCTV surveillance cameras producing video footage of the activities of people who are stationary or in motion. There is a need to restore such captured footage from noise so that it can become evidence for different criminal cases. Denoising face images captured using CCTV is a challenging task due to fine details being affected by noise. In this paper, we evaluate three image denoising techniques Block-Matching and 3D (BM3D), k-Means Singular Value Decomposition (KSVD), and Weighted Nuclear Norm Minimization (WNNM). The performance of these methods is analyzed using Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Visual Information Fidelity (VIF). It is observed that the overall performance of KSVD is better for a Gaussian and Salt and Pepper noise.

关键词： image denoising BM3D WNNM KSVD Video surveillance images CCTV images

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 << < 19 20 21 22 23 24 25 26 27 28 > >>

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：