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

14,163 篇 会议
291 篇 期刊文献
199 册 图书
6 篇 学位论文

馆藏范围

14,659 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

7,882 篇 工学
- 5,293 篇 计算机科学与技术...
- 2,556 篇 软件工程
- 2,529 篇 电气工程
- 1,448 篇 信息与通信工程
- 934 篇 控制科学与工程
- 744 篇 光学工程
- 548 篇 生物医学工程（可授...
- 530 篇 电子科学与技术（可...
- 512 篇 仪器科学与技术
- 486 篇 机械工程
- 358 篇 生物工程
- 245 篇 测绘科学与技术
- 182 篇 材料科学与工程（可...
- 173 篇 航空宇航科学与技...
- 148 篇 交通运输工程
- 110 篇 安全科学与工程
- 96 篇 化学工程与技术
3,825 篇 理学
- 2,633 篇 物理学
- 1,003 篇 数学
- 411 篇 生物学
- 276 篇 系统科学
- 255 篇 统计学（可授理学、...
- 132 篇 化学
1,610 篇 医学
- 1,422 篇 临床医学
- 250 篇 特种医学
- 185 篇 基础医学(可授医学...
- 113 篇 药学(可授医学、理...
781 篇 管理学
- 469 篇 管理科学与工程(可...
- 338 篇 图书情报与档案管...
- 98 篇 工商管理
67 篇 农学
60 篇 法学
37 篇 教育学
30 篇 经济学
27 篇 文学
20 篇 军事学
19 篇 艺术学
1 篇 哲学

主题

2,875 篇 image processing
1,506 篇 image segmentati...
1,202 篇 signal processin...
660 篇 feature extracti...
625 篇 cameras
591 篇 image edge detec...
590 篇 signal processin...
530 篇 image coding
522 篇 image reconstruc...
473 篇 real-time system...
416 篇 algorithm design...
354 篇 image analysis
352 篇 image color anal...
331 篇 image enhancemen...
329 篇 deep learning
311 篇 object detection
306 篇 pixel
300 篇 hardware
299 篇 real time system...
294 篇 computer archite...

机构

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

作者

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

语言

14,421 篇 英文
138 篇 其他
81 篇 中文
20 篇 土耳其文
6 篇 德文
3 篇 葡萄牙文
2 篇 西班牙文
2 篇 俄文
1 篇 法文
1 篇 波兰文

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

共 14659 条记录，以下是621-630 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：

A Novel Machine Learning Algorithm for Prostate Cancer image Segmentation using mpMRI

A Novel Machine Learning Algorithm for Prostate Cancer Image...

引用

2023 International conference on Sustainable Computing and Smart systems, ICSCSS 2023

作者： Shukla, Tushar Dhar Kalpana, K. Gupta, Richa Kalpanadevi, D. Walid, Md. Abul Ala Keshav Kumar, K. Chandigarh University Uittr Department of Physical Education Punjab India Presidency University Yelahanka School of Cse and Is Karnataka Bangalore India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Kalasalingam Academy of Research and Education Department of Computer Applications Tamilnadu Krishnan koil India Department of Computer Science and Engineering Khulna9203 India Department of Humanities and Mathematics Hyderabad India

ISBN: (纸本)9798350333602

Recently, the advancements in technology and the changes in lifestyle behaviors of people leads to a sedentary routine of everyday habits. For this reason, numerous cancers have been developed and causes death for millions of people every year. Although, cancer is a deadly disease, early detection can help for survival. Especially for prostate cancer (PCa), early detection helps to cure the disease. Several researches have been done in medical image processing using Artificial Intelligence (AI) algorithms, yet accuracy and computational complexities limits the performance. With the intension of introducing a novel model for PCa detection from multi-parametric Magnetic Resonance Imaging (mpMRI), this study introduces an enhanced image segmentation model using the efficiency of Machine Learning (ML) algorithm together with Moth Flame Optimization (MFO) Algorithm to eradicate the previous issues. Generally, segmentation of an image is a partition of the image into multiple regions which enhances the classification performances. The major phases in this research includes 1. Data Pre-processing, 2. Feature Extraction, and finally,3. Segmentation. In data pre-processing, noises in the input images are eliminated using Gaussian filtering. The efficiency of MFO is employed to extract the optimal features from the images, and the extracted images are further subjected for U-Net segmentation. Moreover, the performance of the proposed model is validated through a comparative analysis over state-of the-art models in terms of DSC. © 2023 IEEE.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Implementation of dual-phase grating system phase contrast information extraction based on generative adversarial networks 4

Implementation of dual-phase grating system phase contrast i...

引用

4th International conference on Laser, Optics, and Optoelectronic Technology, LOPET 2024

作者： Zeng, Jiacheng Huang, Jianheng Zhu, Minghui Li, Jiaqi Lei, Yaohu Liu, Xin Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781510681903

In the dual-phase grating system of X-ray phase-contrast imaging, the reduction in structural requirements for the absorption grating relaxes the constraints on its aspect ratio and period, thereby broadening the applicability of X-ray phase-contrast imaging techniques in a wider market. Traditionally, the extraction of phase-contrast information primarily relies on phase-stepping methods or Fourier transform algorithms, which often introduce artifacts and blurring into the images. To achieve higher quality image restoration, this study introduces generative adversarial networks (GANs) for high-quality image reconstruction. Our approach uses ideal images as labels and images containing object stripe information as inputs, utilizing GANs for feature learning to facilitate the transformation from object stripe images to high-quality phase-contrast images. The network also employs transfer learning to process previously unseen object stripe images and generate corresponding phase-contrast images. This technique not only significantly enhances image resolution but also substantially reduces artifacts and blurring in the image processing, paving the way for high-precision demands in medical diagnostics and industrial inspection. © 2024 SPIE.

关键词： image resolution

来源：评论

学校读者我要写书评

暂无评论

Automatic Volume Control Using image processing and Deep Learning Techniques: A Review

Automatic Volume Control Using Image Processing and Deep Lea...

引用

Intelligent systems for Cybersecurity (ISCS), International conference on

作者： Kinshuk Theraja Sakshi Gupta Deepak Kumar Gupta Amity Institute of Information and Technology Amity University Noida

ISBN: (数字)9798350375237

ISBN: (纸本)9798350375244

This paper presents an innovative approach to automatic volume control using image processing and deep learning techniques. The ability to automatically adjust volume levels based on environmental factors and user preferences has significant implications for various audio applications, including teleconferencing systems, smart devices, and public address systems. By combining image processing algorithms with deep learning models, this paper aims to develop a robust and adaptive volume control system capable of accurately adjusting audio levels in real-time. The paper discusses the theoretical foundations, technical implementation, experimental results, and potential applications of the proposed automatic volume control system.

关键词： Deep learning Visualization Teleconferencing Solid modeling image processing Software algorithms Process control

来源：评论

学校读者我要写书评

暂无评论

Chaos Theory Based Gravitational Search Algorithm For Medical image Segmentation 27th

Chaos Theory Based Gravitational Search Algorithm For Medica...

引用

27th International conference on Pattern Recognition, ICPR 2024

作者： Rather, Sajad Ahmad Roy, Partha Pratim Das, Sujit Department of Computer Science and Engineering Indian Institute of Technology Roorkee247667 India Department of Computer Science and Engineering National Institute of Technology Telangana506004 India

ISBN: (纸本)9783031781032

Multilevel thresholding plays a crucial role in image processing, with extensive applications in object detection, machine vision, medical imaging, and traffic control systems. It entails the partitioning of an image into distinct regions based on optimal pixel values. However, as the number of threshold levels increases, so does the computational cost for segmentation. To address this challenge, a novel method is proposed namely Chaos theory based Gravitational Search Algorithm (CGSA) for multilevel thresholding. CGSA combines the standard Gravitational Search Algorithm (GSA) for exploration with chaotic maps for exploitation of the complex pixel problem space. In this study, Kapur’s entropy method is utilized to segment sample images into various partitions based on optimal pixel values. The effectiveness of CGSA in real-world scenarios is evaluated using COVID-19 chest CT scan imaging datasets from Kaggle database. The quality, symmetry, and consistency of the segmented output are assessed using metrics like Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Feature Similarity Index Measure (FSIM). Qualitative analysis includes convergence curves, segmented graphs, colormap images, and box plots. Statistical validation is conducted using the signed Wilcoxon rank sum test. Additionally, a comparison is made between CGSA’s performance and that of eight state-of-the-art heuristic algorithms. The findings demonstrate the superior performance of CGSA, evidenced by its reduced computational time and enhanced image quality metrics values. Specifically, CGSA achieved SSIM of 0.81, FSIM of 0.82, and PSNR of 24.27, surpassing the performance of other competitive algorithms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

I2P-Rec: Recognizing images on Large-scale Point Cloud Maps through Bird's Eye View Projections

I2P-Rec: Recognizing Images on Large-scale Point Cloud Maps ...

引用

IEEE/RSJ International conference on Intelligent Robots and systems (IROS)

作者： Zheng, Shuhang Li, Yixuan Yu, Zhu Yu, Beinan Cao, Si-Yuan Wang, Minhang Xu, Jintao Ai, Rui Gu, Weihao Luo, Lun Shen, Hui-Liang Zhejiang Univ Coll Opt Engn Hangzhou 310027 Peoples R China Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China Zhejiang Univ Ningbo Res Inst Ningbo 315100 Peoples R China Homo Technol Co Ltd Beijing 100192 Peoples R China

ISBN: (纸本)9781665491907

Place recognition is an important technique for autonomous cars to achieve full autonomy since it can provide an initial guess to online localization algorithms. Although current methods based on images or point clouds have achieved satisfactory performance, localizing the images on a large-scale point cloud map remains a fairly unexplored problem. This cross-modal matching task is challenging due to the difficulty in extracting consistent descriptors from images and point clouds. In this paper, we propose the I2P-Rec method to solve the problem by transforming the cross-modal data into the same modality. Specifically, we leverage on the recent success of depth estimation networks to recover point clouds from images. We then project the point clouds into Bird's Eye View (BEV) images. Using the BEV image as an intermediate representation, we extract global features with a Convolutional Neural Network followed by a NetVLAD layer to perform matching. The experimental results evaluated on the KITTI dataset show that, with only a small set of training data, I2P-Rec achieves recall rates at Top-1% over 80% and 90%, when localizing monocular and stereo images on point cloud maps, respectively. We further evaluate I2P-Rec on a 1 km trajectory dataset collected by an autonomous logistics car and show that I2P-Rec can generalize well to previously unseen environments.

关键词： Stereo image processing

来源：评论

学校读者我要写书评

暂无评论

UAV to Cadastral Parcel Boundary Translation and Synthetic UAV image Generation Using Conditional-Generative Adversarial Network 1

引用

2nd International conference on Unmanned Aerial systems in Geomatics (UASG)

作者： Khadanga, Ganesh Jain, Kamal Indian Inst Technol Roorkee Roorkee Uttarakhand India

ISBN: (数字)9783031193095

ISBN: (纸本)9783031193118;9783031193095;9783031193088

The precise boundaries of the cadastral parcels from the Unmanned Aerial Vehicle (UAV) data are essential for any eGovernance application. The pix2pix, image-to-image translation using the conditional Generative Adversarial Network (cGAN) models, has emerged as an alternative to the traditional machine learning and image processing algorithms. It has been used and demonstrated for productive purposes in different domains without any change in the pix2pix network model and loss functions. The pix2pix model is implemented in this research for extracting the cadastral parcel boundaries using the existing UAV data set, and the corresponding digitised data. The input data set is prepared using the python modules. The model is also used to predict the synthetic UAV data from the map data. The predicted boundary of the model is very useful. The proposed model can reduce the manual labour and human interventions in outlining the parcel boundary from UAV data.

关键词： Pix2Pix image-to-image translation c-GAN CNN UAV Deep learning Parcel

来源：评论

学校读者我要写书评

暂无评论

image-Based Pothole Detection System Using YoloV8 Algorithm

Image-Based Pothole Detection System Using YoloV8 Algorithm

引用

2024 International conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence, RAEEUCCI 2024

作者： Tripathy, Asutosh Rajalakshmi, T. Santhosh Kumar, R. Vasudevan Suryakala, S. SRM Institute of science and Technology College of Enginerring and Technology Department of Electronics and Communication Engineering Kattankulathur603203 India SRM Institute of Science & Technology College of Enginerring and Technology Dept of Electronics and Communication Engineering Kattankulathur603203 India

ISBN: (纸本)9798350354539

A pothole is a significant disadvantage in the roadways, resulting from depressions formed due to the improper quality of road materials and external conditions, such as extreme weather forces and the heavy vehicles passing over them. This leads to soil erosion beneath the road surface. Potholes are responsible for various damages including punctures, wheel damages, dents on vehicles, damage to the vehicle floor, collisions, and even severe accidents. The number of deaths and injuries stands at 1481 and 3103 respectively. Therefore, accurate and fast pothole detection is crucial for improving ITS (Intelligent Transport systems). Hence, this proposed study aims to overcome this major issue by implementing the YOLOv8 algorithm to detect the potholes present on the roads, which has the highest accuracy level of 98.18 percent, compared to existing algorithms. The study under consideration includes a comparison with the YOLOv5 algorithm, and the results demonstrate that the proposed approach outperforms the current method. © 2024 IEEE.

关键词： image processing

来源：评论

学校读者我要写书评

暂无评论

Building surface damage recognition based on synthetic data 9

Building surface damage recognition based on synthetic data

引用

9th IEEE International conference on Information Technology and Nanotechnology, ITNT 2023

作者： Zherdeva, L.A. Minaev, E. Yu. Firsov, N.A. Samara National Research University Samara Russia Image Processing Systems Institute Samara Russia

ISBN: (纸本)9798350397338

To detect surface damage to buildings, it is necessary to involve workers who are at risk of industrial injuries when inspecting hard-to-reach areas of industrial premises. Attraction of special means, such as aerial platforms, safety systems, etc. increase the financial costs with this approach. The use of unmanned aerial vehicles, coupled with neural network algorithms, can simplify this procedure. Due to the inaccessibility, the problem of obtaining training data for neural networks arises, which can be solved by synthesizing them in a virtual environment. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Survey on One-Shot Learning for image Recognition using Machine Learning and Deep Learning Techniques 5

Survey on One-Shot Learning for Image Recognition using Mach...

引用

5th International conference on Smart Electronics and Communication, ICOSEC 2024

作者： Kadam, Ganesh Vitthal Dubey, Ghanshyam Prasad Computer Science Amity School of Engineering & Technology Gwalior Maharajpura Madhya Pradesh Gwalior474005 India Amity School of Engineering & Technology ASET-CSE Maharajpura Madhya Pradesh Gwalior474005 India

ISBN: (纸本)9798331504403

Despite their success, the traditional deep neural networks are unable to rapidly generalize from a limited number of samples. To address the issue of large training data requirements with deep neural networks, one-shot learning restricting the number of data in each category is developed to attain enhanced results. Specifically, the traditional neural networks lead to over-fitting problems in training with a limited number of samples. In contrast, Machine Learning algorithms are capable of one-shot learning from limited samples like humans have the ability of oneshot learning. Hence, it is necessary to analyze one-shot object recognition techniques prevalent in image processing systems. This study will explore different one-shot learning techniques and methods from the state-of-the-art models and examine the merits and challenges of the approach with 25 literature papers. The effectiveness of the existing approaches will be evaluated by various techniques, datasets, and performance metrics are discussed in detail. At last, the paper discusses the potential future studies and challenges in achieving better detection accuracy. © 2024 IEEE.

关键词： Zero-shot learning

来源：评论

学校读者我要写书评

暂无评论

Dual-Source CBCT for Larger Longitudinal Coverage: System Design and image Reconstruction 46

Dual-Source CBCT for Larger Longitudinal Coverage: System De...

引用

46th Annual International conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Zhang, Xusheng Lyu, Tianling Shi, Yijie Zhong, Xinyun Wu, Zhan Xi, Yan Wang, Shijie Chen, Yang Zhu, Wentao Southeast University School of Software Nanjing China Zhejiang Lab Hangzhou China First-Imaging Tech. Shanghai China Southeast University Laboratory of Image Science and Technology The School of Computer Science and Engineering Nanjing China Southeast University Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing The Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Nanjing China

ISBN: (纸本)9798350371499

The application of CBCT systems in intraoperative environments has become increasingly common, but concurrent CBCT systems are unsuitable for situations that require a large longitudinal imaging FoV, such as orthopedics. To increase longitudinal coverage, we developed a dual-source CBCT (DS-CBCT) system in which two ray sources are symmetrically placed along the central plane. After further analyzing its geometric characteristics, we propose an analytical reconstruction algorithm termed DT-FDK specialized for DS-CBCT, which combines cone-beam rebinning and two rays with smaller cone angles among the four conjugate rays to further suppress cone beam artifacts. The system design and reconstruction algorithm are tested on both simulated and real-scanned data. Results show that the DS-CBCT can expand the effective imaging volume by 37.1% compared to single-source CBCT systems. The reconstructed images by DT-FDK also show improved image quality compared to traditional reconstruction algorithms. © 2024 IEEE.

关键词： Cones

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 << < 59 60 61 62 63 64 65 66 67 68 > >>

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：