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

1,778 篇 会议
14 册 图书
11 篇 期刊文献

馆藏范围

1,803 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,386 篇 工学
- 1,114 篇 计算机科学与技术...
- 818 篇 软件工程
- 457 篇 信息与通信工程
- 331 篇 光学工程
- 303 篇 控制科学与工程
- 199 篇 电气工程
- 181 篇 生物工程
- 152 篇 机械工程
- 126 篇 生物医学工程（可授...
- 97 篇 电子科学与技术（可...
- 85 篇 仪器科学与技术
- 65 篇 安全科学与工程
- 60 篇 化学工程与技术
- 42 篇 材料科学与工程（可...
- 40 篇 交通运输工程
- 25 篇 网络空间安全
615 篇 理学
- 373 篇 物理学
- 194 篇 数学
- 192 篇 生物学
- 61 篇 统计学（可授理学、...
- 58 篇 化学
- 25 篇 系统科学
222 篇 管理学
- 129 篇 管理科学与工程(可...
- 107 篇 图书情报与档案管...
- 46 篇 工商管理
136 篇 医学
- 125 篇 临床医学
- 58 篇 基础医学(可授医学...
- 48 篇 药学(可授医学、理...
37 篇 农学
- 33 篇 作物学
25 篇 艺术学
- 25 篇 设计学（可授艺术学...
20 篇 教育学
18 篇 法学
15 篇 经济学
4 篇 军事学
1 篇 文学

主题

289 篇 computer vision
164 篇 image processing
106 篇 feature extracti...
99 篇 deep learning
99 篇 image segmentati...
50 篇 object detection
47 篇 machine vision
47 篇 computational mo...
47 篇 convolutional ne...
45 篇 image enhancemen...
44 篇 image recognitio...
43 篇 cameras
37 篇 accuracy
36 篇 image edge detec...
36 篇 face recognition
34 篇 machine learning
33 篇 image color anal...
33 篇 training
31 篇 image reconstruc...
30 篇 visualization

机构

6 篇 shenyang institu...
6 篇 university of ch...
6 篇 shenyang ligong ...
5 篇 department of co...
4 篇 key laboratory o...
4 篇 school of softwa...
4 篇 school of inform...
4 篇 department of co...
4 篇 college of compu...
4 篇 beijing informat...
3 篇 school of comput...
3 篇 shanghaitech uni...
3 篇 chitkara univers...
3 篇 university of el...
3 篇 school of comput...
3 篇 institute for co...
3 篇 guangzhou civil ...
3 篇 institutes for r...
3 篇 babol noshirvani...
3 篇 computer vision ...

作者

5 篇 raman balasubram...
5 篇 lu zongqing
4 篇 zhang chao
4 篇 balasubramanian ...
4 篇 ramani sanjeev k...
4 篇 wang wei
4 篇 hossain syed akh...
4 篇 iyengar s.s.
4 篇 sanjeev kaushik ...
3 篇 liu bo
3 篇 kumar krishan
3 篇 zhang ji
3 篇 elizabeth rani g...
3 篇 neehal nafis
3 篇 rabby akm shahar...
3 篇 luc van gool
3 篇 farag aly a.
3 篇 zhao jiewen
3 篇 zou xiaobo
3 篇 zhang hualiang

语言

1,721 篇 英文
65 篇 其他
19 篇 中文
1 篇 土耳其文

检索条件"任意字段=2nd International Conference on Computer Vision and Image Processing, CVIP 2017"

共 1803 条记录，以下是471-480 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：

Parallelization Algorithm of computer vision for Autonomous Vehicles

Parallelization Algorithm of Computer Vision for Autonomous ...

引用

international conference on vision Towards Emerging Trends in Communication and Networking (ViTECoN)

作者： Kaniskaa MS R. Manimegalai Noor Mahammad SK PSG Institute of Technology and Applied Research Indian Institute of Information Technology Design and Manufacturing Kancheepuram

The important features that enable computer vision in autonomous vehicle technology and infotainment function are image processing and object identification. image segmentation is the preliminary step of any image processing algorithm. This work uses the Union-Find algorithm to segment images on a grey scale. It is a simple yet effective algorithm for intense applications. A review of the image segmentation algorithms and parallelization techniques is presented in this paper. Initially, three different profiling techniques are applied in order to identify the hot-spots, i.e. most time-consuming parts of the code. Parallelization techniques are applied to the regions of the hot-spots identified during profiling. The Union-Find algorithm is parallelized using OpenMP, MPI, and CUDA. The execution time decreases with the increase in the number of threads till a certain optimal value of threads. The optimal number of threads is found for the respective parallelization techniques.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Classification of Defects in Injected Parts Through: Moments of image and Multilayer Perceptron 2nd

Classification of Defects in Injected Parts Through: Moments...

引用

2nd international conference Advanced Research in Technologies, Information, Innovation and Sustainability ARTIIS

作者： Ruiz, Blanca Baltazar, Rosario Casillas, Miguel Santiago, Raul Mosino, Francisco Inst Tecnol Leon Leon Mexico

ISBN: (纸本)9783031203183;9783031203190

Quality control at industry is an important factor to find the desired specifications of the manufactured products, this is often achieved manually with the support of the work staff. It implies that some defects are not detected by workers due to fatigue. This article describes a technological proposal, applied to the quality control of injected parts, using vision machine to give support to quality control. In this article we achieve obtain a set of PVC tee in a previously were environment it for four different faces and two types of parts found: defective and non-defective. Then image processing where we obtain the characteristic vector and using feed forward artificial neuronal network based on a multilayer perceptron mentioned images are classified account to the type expected. An n training procedure and is performance to classifi images are discussed in detail in the contect of quality control.

关键词： Quality control image processing Multilayer perceptron Classification

来源：评论

学校读者我要写书评

暂无评论

Research on the Detection Algorithm of Rural Road Surface Damage Based on image processing 2nd

Research on the Detection Algorithm of Rural Road Surface Da...

引用

2nd international conference on image, vision and Intelligent Systems, ICIVIS 2022

作者： Ye, Pei Jiang, Tao Zhan, Hui Wuchang Institute of Technology HB WuHan China Wuhan University of Technology HB WuHan China

ISBN: (纸本)9789819909223

China's new rural construction project has developed rapidly. The rural landscape has changed a lot. The scale of the rural roads is getting larger and larger. The maintenance cost of rural road diseases is also very large. People use computer technology and artificial intelligence technology to improve the detection effect of road viruses in rural areas. This paper has collected a large number of pictures of rural road surface diseases. The types of disease include: heet damage, potholes, cracks and peeling. We use the SSD algorithm to process and identify these images. with some results, We have achieved some results, but the overall identification rate is not particularly high. To further improve the identification effect, we propose an improved SSD algorithm. We found that the improved SSD algorithm also had some results in the identification of rural road surface diseases. We compare the two algorithms, and we find that improving the SSD algorithm has more advantages. The improved SSD algorithm has a higher recognition rate and a faster recognition speed. We believe that this algorithm can provide a new idea for rural pavement disease identification. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image processing

来源：评论

学校读者我要写书评

暂无评论

Research on the development of image segmentation based on deep learning

Research on the development of image segmentation based on d...

引用

Mechatronics, IoT and Industrial Informatics (ICMIII), international conference on

作者： Kefeng He Wei Peng Yang Zhang Peipei Pei China Energy Engineering Group Gansu Electric Power Design Institute Co. Ltd Lanzhou China

ISBN: (数字)9798350386639

ISBN: (纸本)9798350386646

image segmentation is a prominent research focus in computer vision and constitutes a fundamental task in image processing. It has found wide applications in real-world scenarios such as autonomous driving, medical image analysis, robot perception, intelligent security, augmented reality, and others. Firstly, this paper provides a summary of commonly used publicly available datasets in the field of image segmentation since the emergence of deep learning, along with enumerating popular evaluation metrics. Secondly, it classifies deep learning-based image segmentation frameworks according to segmentation tasks and systematically summarizes the design principles and technological innovations of different models. Finally, it presents prospects for feasible research directions in the field of image segmentation in the future.

关键词： Deep learning Measurement image segmentation Technological innovation computer vision Mechatronics image analysis

来源：评论

学校读者我要写书评

暂无评论

Real-Time 3D Object Detection and Recognition using a Smartphone

Real-Time 3D Object Detection and Recognition using a Smartp...

引用

international conference on image processing and vision Engineering (IMPROVE)

作者： Chen, Jin Zhu, Zhigang CUNY Comp Sci Dept Visual Comp Lab Data Sci & Engn Program New York NY 10031 USA CUNY Grad Ctr PhD Program Comp Sci New York NY 10016 USA

ISBN: (纸本)9789897585630

Real-time detection of 3D obstacles and recognition of humans and other objects is essential for blind or low-vision people to travel not only safely and independently but also confidently and interactively, especially in a cluttered indoor environment. Most existing 3D obstacle detection techniques that are widely applied in robotic applications and outdoor environments often require high-end devices to ensure real-time performance. There is a strong need to develop a low-cost and highly efficient technique for 3D obstacle detection and object recognition in indoor environments. This paper proposes an integrated 3D obstacle detection system implemented on a smartphone, by utilizing deep-learning-based pre-trained 2D object detectors and ARKit-based point cloud data acquisition to predict and track the 3D positions of multiple objects (obstacles, humans, and other objects), and then provide alerts to users in real time. The system consists of four modules: 3D obstacle detection, 3D object tracking, 3D object matching, and information filtering. Preliminary tests in a small house setting indicated that this application could reliably detect large obstacles and their 3D positions and sizes in the real world and small obstacles' positions, without any expensive devices besides an iPhone.

关键词： 3D Object Detection 3D Object Tracking Obstacle Detection Assistive computer vision

来源：评论

学校读者我要写书评

暂无评论

A Framework For Single image Dehazing Using DWT Based Cross Bilateral Filter Fusion of Generative and ASM Models 2

A Framework For Single Image Dehazing Using DWT Based Cross ...

引用

2nd international conference on Innovative Sustainable Computational Technologies, CISCT 2022

作者： Revanth, Banala Dwivedi, Sanjay K. Kumar, Manoj Babasaheb Bhimrao Ambedkar University Department of Computer Science Lucknow India

ISBN: (纸本)9781665474160

Due to the latest advancements in technologies like artificial intelligence, machine learning, and deep learning in image processing, computer vision, and their uses in various applications, there has been a lot of interest in the restoration of murky images. This paper gives a novel single-image dehazing (SID) framework for the restoration of single hazy image (SHI). The framework has three parts. The first part of the framework comprises three networks. A white-balanced auto-encoder network in the front, followed by a pair of sequential auto-encoder networks at the end for image dehazing (ID). A white balance auto-encoder network is used for correcting the white balance error in the input hazy image (HI). Pair of sequential auto- encoder networks gives haze-reduced output by taking corrected white balanced error image as input. The second part comprises an ASM-based model Dark Channel Prior (DCP) for ID. DCP produce haze-free images (HFI) by taking HI as input. The third part presents the fusion model for integrating the first and second parts of the framework. DWT-based cross bilateral filter model is the fusion model (FM) to get the final HFI. The first part of the framework is trained by using a hybrid loss function (perceptual loss function combined with MSE loss function) on O- HAZE, I-HAZE, and MRFID data sets. The proposed framework got considerably good result in terms of Structural Similarity Index (SSIM), Peak signal-to-noise ratio (PSNR), compared with cutting-edge methods. © 2022 IEEE.

关键词： Restoration

来源：评论

学校读者我要写书评

暂无评论

Fast image matting based on matting pyramids and surrogate models 2

Fast Image matting based on matting pyramids and surrogate m...

引用

2nd international conference on Robotics, Artificial Intelligence and Intelligent Control, RAIIC 2023

作者： Liang, Yihui Gou, Hongshan Liu, Guisong Huang, Sibo University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China University of Electronic Science and Technology of China Zhongshan Institute School of Computer Zhongshan China Guiyang Institute of Humanities and Technology College of Big Data and Information Engineering Guiyang China Southwestern University of Finance and Economics School of Computing and Artificial Intelligence Chengdu China Huizhou University Network and Information Centre Huizhou China

ISBN: (纸本)9798350328004

image matting is a foundation task in the field of computer vision. Pixel-pair-optimization-based image matting methods have attracted lots of attention due to their distinct advantages on parallelization and handling spatially disconnected foregrounds. However, these methods struggle when the computing time is limited. To address this issue, this study presents the image matting method based on matting pyramid and surrogate model (IMMPSM). IMMPSM speeds up the process of pixel pair optimization by replaces the evolutionary algorithm in the pyramid matting framework, which consumes a lot of computing time, with the efficient surrogate-model-based method. The constructed surrogate model is reused by the presented surrogate model share strategy to save computing time. Specifically, the constructed surrogate model is shared with the pixel pair optimization subproblem adjacent to current subproblem avoiding repeated computation on the surrogate model construction. Extensive experimental results show that IMMPSM can provide acceptable alpha mattes even under limited computing time. © 2023 IEEE.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor Detection with Hybrid Segmentation using Improved Adaptive Network Fuzzy Inference System

Brain Tumor Detection with Hybrid Segmentation using Improve...

引用

Disruptive Technologies (ICDT), international conference on

作者： Devanshu Dube Ashok Kumar Vijay Kumar Tiwari Department of Computer Science BanasthaliVidyapith Banasthali India Department of Computer Science ITS Engineering College G.Noida India

In the past, numerous researchers used a variety of cutting-edge deep learning models to work on biomedical image classification and segmentation systems. The results of deep learning are better than those of the current conventional computer vision methods. Currently various automated image segmentation methods have been used for feature extraction. These methods generally use a brain tumor classification approach and color detection schemes to predict the class label of neighboring pixels and the classification by validating the extracted features. These techniques' parameter improvement is dependent upon the signal processing approaches. The accuracy has increased significantly as a result of the usage of optimal parameter sets by numerous researchers, which are produced for a particular dataset. On the other hand, the model does not scale on any other collection of data. We have presented a novel hybrid approach for brain tumor segmentation that combines wavelet and watershed transform. This hybrid approach can be applied to a wide range of image types. When the model is used on a variety of images, the accuracy improves even when noise is present.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Realization of Anti-counterfeiting and Traceability of Ceramics Based on computer vision and Blockchain Technology-Taking Jingdezhen Ceramics as an Example

Realization of Anti-counterfeiting and Traceability of Ceram...

引用

Algorithm, image processing and Machine vision (AIPMV), international conference on

作者： Yangyang Chang Jingfang Hu Xien Cheng School of Information Engineering Jingdezhen Ceramic University Jingdezhen China

ISBN: (数字)9798350390254

ISBN: (纸本)9798350390261

Jingdezhen ceramics have a long history and are world-famous, and thus often become the object of imitation. Aiming at the current ceramic anti-counterfeiting traceability technology is not precise enough, a new treatment program is proposed. Firstly, professional equipment is used to collect the ceramic micropores, due to the randomness and uniqueness of the arrangement of micropores in the ceramic microstructure. afterwards, these micro-holes are processed by Canny edge detection method and then combined with high-precision SIFT method of computer vision for feature extraction. In the next part, this paper introduces the Interplanetary File System (IPFS) combined with decentralized and difficult to tamper with blockchain technology to write a smart contract for traceability. Finally, In the identification process, the picture to be compared with the picture stored on IPFS is compared using knnmatch, and if it meets the principle of 3 times the standard deviation, it is authentic, and vice versa, it is a fake. The experimental results show that the results can be used as a powerful basis for ceramic anti-counterfeiting traceability.

关键词： computer vision image edge detection System performance Smart contracts Ceramics Blockchains InterPlanetary File System Microstructure Protection Standards

来源：评论

学校读者我要写书评

暂无评论

Advancing image processing through Cutting-Edge Optimization Methods: State-of-the-Art Techniques and Applications

Advancing Image Processing through Cutting-Edge Optimization...

引用

Self Sustainable Artificial Intelligence Systems (ICSSAS), international conference on

作者： Usman Ahmad Usmani Junzo Watada Mohammed Umar Usmani Universiti Teknologi Petronas Waseda University Shinjuku City Tokyo Japan University of Malaysia Pahang

ISBN: (数字)9798350368413

ISBN: (纸本)9798350368420

In the image processing domain, the growth of digital data has intensified the need for efficient and robust optimization techniques. This research study aims to develop and evaluate advanced optimization methods tailored specifically for improving the performance of image processing tasks. It explores the latest advancements in optimization algorithms, including evolutionary algorithms, metaheuristic approaches, and deep learning-based optimization techniques. The study provides an in-depth analysis of these methods, elucidating their strengths, weaknesses, and areas of applicability across diverse image processing tasks such as image denoising, image reconstruction, image segmentation, and image enhancement. By comparing their performance through comprehensive experiments, the paper demonstrates substantial improvements in computational efficiency, accuracy, and generalization. These results highlight the potential of optimization methods to significantly enhance the quality and speed of image processing pipelines, opening new avenues for breakthroughs in computer vision, medical imaging, remote sensing, and other domains. Ultimately, this research not only empowers practitioners with cutting-edge tools but also paves the way for future exploration in the application of optimization techniques within image processing.

关键词： image segmentation computer vision image processing Pipelines Metaheuristics Optimization methods Evolutionary computation Computational efficiency Remote sensing image reconstruction

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181页 << < 44 45 46 47 48 49 50 51 52 53 > >>

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：