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

12,550 篇 会议
192 篇 期刊文献
161 册 图书

馆藏范围

12,903 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

6,493 篇 工学
- 4,276 篇 计算机科学与技术...
- 2,182 篇 软件工程
- 1,870 篇 电气工程
- 1,278 篇 信息与通信工程
- 824 篇 控制科学与工程
- 652 篇 光学工程
- 462 篇 生物医学工程（可授...
- 438 篇 电子科学与技术（可...
- 434 篇 机械工程
- 424 篇 仪器科学与技术
- 316 篇 生物工程
- 220 篇 测绘科学与技术
- 151 篇 材料科学与工程（可...
- 142 篇 航空宇航科学与技...
- 133 篇 交通运输工程
- 99 篇 安全科学与工程
- 86 篇 网络空间安全
3,122 篇 理学
- 2,082 篇 物理学
- 887 篇 数学
- 359 篇 生物学
- 246 篇 系统科学
- 224 篇 统计学（可授理学、...
- 108 篇 化学
1,429 篇 医学
- 1,268 篇 临床医学
- 192 篇 特种医学
- 158 篇 基础医学(可授医学...
- 99 篇 药学(可授医学、理...
690 篇 管理学
- 421 篇 管理科学与工程(可...
- 291 篇 图书情报与档案管...
- 84 篇 工商管理
58 篇 法学
57 篇 农学
30 篇 教育学
27 篇 文学
25 篇 经济学
17 篇 军事学
16 篇 艺术学
1 篇 哲学

主题

2,645 篇 image processing
1,386 篇 image segmentati...
1,142 篇 signal processin...
610 篇 cameras
595 篇 feature extracti...
582 篇 image edge detec...
521 篇 signal processin...
472 篇 image reconstruc...
462 篇 image coding
460 篇 real-time system...
390 篇 algorithm design...
334 篇 image color anal...
307 篇 deep learning
306 篇 image enhancemen...
306 篇 pixel
300 篇 real time system...
293 篇 object detection
290 篇 computer archite...
283 篇 neural networks
283 篇 hardware

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 tongji universit...
8 篇 university of to...
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 ...
7 篇 school of electr...
7 篇 department of ma...

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
10 篇 r. chellappa
10 篇 a. ortega
9 篇 c.-c.j. kuo
8 篇 frank hannig
8 篇 bovik alan c.
8 篇 hannig frank
8 篇 mahalanobis a
8 篇 ilias maglogiann...
8 篇 carli m.
7 篇 miller jwv
7 篇 busch christoph
7 篇 semenishchev e.
7 篇 zelensky a.

语言

12,608 篇 英文
209 篇 其他
74 篇 中文
20 篇 土耳其文
3 篇 葡萄牙文
2 篇 西班牙文
2 篇 俄文
1 篇 法文

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

共 12903 条记录，以下是871-880 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：

Simple Linear Iterative Clustering with Efficiency 1

引用

17th International conference on Intelligent Information Hiding and Multimedia Signal processing (IIH-MSP) / 14th International conference on Frontiers of Information Technology, Applications and Tools (FITAT)

作者： Liao, Nannan Liu, Hui Li, Cheng Ren, Xia Guo, Baolong Xidian Univ Inst Intelligent Control & Image Engn Xian Peoples R China

ISBN: (数字)9789811910579

ISBN: (纸本)9789811910579;9789811910562

As an instructive work to generate satisfactory superpixels, simple linear iterative clustering (SLIC), has become fundamental and popular in various computer vision tasks. In this work, the algorithm is reconsidered, and an integrated framework is proposed to further improve the running speed and segmentation performance. In the first stage, a fast convergence strategy for clustering is presented on SLIC to redistribute the seeds efficiently. This is done to initialize a set of clustering centers that is fairly representative of local information on the image plane. Then, a followup work of SLIC termed simple non-iterative clustering (SNIC) is utilized to process more accurate segmentation without any post-processing to enforce connectivity. Experimental results show that the framework could generate a synergetic effect and performs better than previous superpixel algorithms in a limited computational time.

关键词： Clustering Initialization Redistribution Superpixels

来源：评论

学校读者我要写书评

暂无评论

Leveraging NVIDIA Clara for Real-Time Cardiac image Segmentation and Diagnosis

Leveraging NVIDIA Clara for Real-Time Cardiac Image Segmenta...

引用

Innovative Computing, Intelligent Communication and Smart Electrical systems (ICSES), International conference on

作者： S. Navaneethan Goalla Hemanth R. Nikilkumar Department of Electronics and Communication Engineering Saveetha Engineering College Chennai Tamilnadu India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

Medical imaging is crucial for heart diagnosis, but outdated algorithms and hardware result in delayed processing and low accuracy. Using NVIDIA Clara, a GPU-accelerated platform, the study proposes real-time cardiac picture segmentation and diagnosis. The proposed system uses advanced DL algorithms built for cardiac imaging to enhance processing speed and accuracy. Employing rigorous data preprocessing and deep learning model able to perform precise partitioning of cardiac structures and positioning defects that lead to quick heart arrhythmia diagnose in a timely manner. It also substantially reduces processing times compared to older systems while improving the contour quality and diagnosability. The system achieves the following DSC values: 0.93 for the left ventricle; 0.92 for right; 0.90 for left atrium; 0.89 for right ventricle and 0.91 for the major blood vessels. With diagnostic accuracy scores higher than the current system Sensitivity 94.2%, Specificity 92.8%, and Accuracy 93.5%. The method has potential to enhance cardiac care by facilitating earlier interventions leading better patient outcomes.

关键词： Heart image segmentation Accuracy Sensitivity Protocols Hospitals Real-time systems Partitioning algorithms Standards Monitoring

来源：评论

学校读者我要写书评

暂无评论

Research on the Design of Robot image Sensing System Based on Artificial Intelligence

Research on the Design of Robot Image Sensing System Based o...

引用

IEEE International conference on Power, Intelligent Computing and systems (ICPICS)

作者： Li Kang Zhengshuo Liu Shandong Institute of Commerce and Technology Shandong Jinan China Lower Kent Ridge Road National University of Singapore Singapore

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

This study focuses on the design and implementation of an artificial intelligence-driven robotic image perception system, aimed at enhancing robots' visual perception capabilities in complex environments. By exploring a cylindrical projection-based global calibration method, this research investigates its model, distortion correction algorithms, and viewpoint switching algorithms, offering an efficient and precise image processing solution. Furthermore, this paper provides an in-depth analysis of image anti-aliasing algorithms, including nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, and conducts a detailed comparison among these three algorithms. The section on panoramic image rapid synthesis achieves efficient stitching and blending of images through SURF feature point extraction and matching. In terms of system design and testing, specific functional design schemes are proposed and comprehensively tested and analyzed, validating the effectiveness and practicality of the system. This study not only provides theoretical support and technological implementation for robotic vision systems but also serves as a robust reference for future developments in robotic vision technology.

关键词： Interpolation Machine vision Switches Robot sensing systems Feature extraction Stability analysis Sensors System analysis and design Testing Visual perception

来源：评论

学校读者我要写书评

暂无评论

2023 IEEE Open conference of Electrical, Electronic and Information Sciences, eStream 2023 - Proceedings

2023 IEEE Open Conference of Electrical, Electronic and Info...

引用

10th IEEE Open conference of Electrical, Electronic and Information Sciences, eStream 2023

ISBN: (纸本)9798350303834

The proceedings contain 19 papers. The topics discussed include: electromagnetic interferences resistant PI/I controller for electrical energy converters;opportunities for automated e-learning path generation in adaptive e-learning systems;development and research of miniature high precision modular rotary encoder kit based on dual optical sensors;dynamic characteristics study of a newly developed suppression system;methodology of low orbit satellites signal processing in the electromagnetically noisy environment;theoretical and experimental research of device for ultrafine particulate matter agglomeration;comparative analysis of the applicability of five clustering algorithms for market segmentation;research and development of information technology for determining shoe size by image;deposition of polydisperse ultrafine particles in a gas flow using an advanced electro-cyclone apparatus;toward bee motion pattern identification on hive landing board;and performance analysis of different ANN-based weight updating algorithms in forecasting short-term load demands in cluster microgrids.

关键词：

来源：评论

学校读者我要写书评

暂无评论

20 Years of Biomedical image Acquisition and processing at BioCAS

20 Years of Biomedical Image Acquisition and Processing at B...

引用

IEEE Biomedical Circuits and systems (BIOCAS)

作者： Amine Bermak Tianyi Liu Ziyao Zhao Bo Wang Milin Zhang College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Department of Electronic Engineering Tsinghua University Beijing China

ISBN: (数字)9798350354959

ISBN: (纸本)9798350354966

The development of biomedical image technology has brought significant advancements to healthcare and frontier research. Over the past 20 years, BioCAS has witnessed and documented comprehensive achievements in biomedical image sensor design and processing algorithms. This paper provides a systematic review of the work related to biomedical image acquisition and processing technology in BioCAS and offers a perspective on future developments in this field.

关键词： Circuits and systems Medical services Artificial intelligence Biomedical imaging Systematic literature review

来源：评论

学校读者我要写书评

暂无评论

7th International conference on Computing inEngineering and Technology, ICCET 2022

7th International Conference on Computing inEngineering and ...

引用

7th International conference on Computing in Engineering and Technology, ICCET 2022

ISBN: (纸本)9781839537042

The proceedings contain 65 papers. The topics discussed include: enhancing sentiment analysis performance with blend of features and deep learning algorithms;a deep learning based approach for mask detection;breast cancer detection using optimized hidden convolutional neural network;plant disease detection and management using deep learning approach;remote sensing image fusion using machine learning and deep learning: a systematic review;smart tour advisor using machine learning and natural language processing;image analysis using convolutional neural network to detect bird species;secure image watermarking using MLDWT and SVD for secure medical data transmission model in healthcare systems;and automatic detection of tuberculosis with the help of image processing and machine learning classifier.

关键词： image fusion

来源：评论

学校读者我要写书评

暂无评论

High-speed AI image space wavefront sensing using embedded computing: achieving 1000 frames per second 12

High-speed AI image space wavefront sensing using embedded c...

引用

2025 conference on Photonic Instrumentation Engineering

作者： Baudat, Gaston Lavanchy, David Muller, Guillaume Innovat Foresight LLC 4432 Mallard Point Columbus IN 47201 USA Univ Arizona Wyant Coll Opt Sci 1630 E. Univ Blvd Tucson AZ 85721 USA Univ Appl Sci Western Switzerland HEIG VD Route Cheseaux 1Case Postale 521 CH-CH1401 Yverdon Switzerland

ISBN: (纸本)9781510684942;9781510684959

Wavefront sensing is fundamental to numerous scientific and industrial applications in optics, particularly in adaptive optics (AO). This paper presents a high-speed image space AI-powered wavefront sensing system, based on a patented technology known as AI4Wave, that eliminates the need for dedicated wavefront sensors, such as Shack-Hartmann, relying solely on fast cameras and AI edge computing devices, specifically an NVIDIA Jetson embedded module in our implementation. This module could also be utilized in the future to directly control actuators, streamlining the entire AO process. The system captures defocused images of a point source or similar, which are processed by a feedforward artificial neural network (NN) trained exclusively on synthetic data [1]. This approach enables real-time phase retrieval, overcoming the local derivative limitations of Shack-Hartmann sensors and handling large wavefront or surface errors spanning multiple wavelengths. It also provides a unique capability for field-dependent wavefront measurement from a single image of multiple sources. Yu Wu et al. [2] proposed a sub-millisecond phase retrieval method that requires two simultaneous images for optimal performance and NN training on physical data. However, this approach necessitates retraining whenever system parameters, such as f/#, wavelength, or pixel size, are altered. In contrast, AI4Wave employs synthetic, normalized data that is agnostic to most optical layout changes, enabling robust and versatile training and validation. Combined with off-the-shelf NVIDIA hardware, it offers a ready-to-use solution for industrial deployment. By integrating optimized algorithms within modern AI acceleration frameworks, such as NVIDIA TensorRT, and leveraging advanced AI edge computers, the system achieves processing speeds of 1000 frames per second or more, effectively providing sub-millisecond wavefront sensing capability. The minimal hardware setup, consisting only of a camera and an NVIDI

关键词： Cameras Education and training Monochromatic aberrations Wavefront sensors Wavefronts Phase retrieval Adaptive optics image retrieval Point spread functions Sensors

来源：评论

学校读者我要写书评

暂无评论

Interpreting and understanding the image using deep learning and imprecise information from the monitoring system

Interpreting and understanding the image using deep learning...

引用

2023 IEEE International conference on Big Data, BigData 2023

作者： Kubanek, Mariusz Bobulski, Janusz Karbowiak, Lukasz Czestochowa University of Technology Department of Computer Science Czestochowa Poland

ISBN: (纸本)9798350324457

The interpretation and understanding of images using deep learning algorithms in monitoring systems is an important area of research in computer vision. In this paper, we propose a novel approach for interpreting and understanding images of human behaviour captured from cameras and drones in monitoring systems. In the work, we presented a pedestrian detection method. This is the first element of a larger system of interpreting the behaviour of traffic participants. We begin by pre-processing the images to remove noise and unwanted artefacts. We then use labelled and unlabelled data to train a deep learning algorithm to accurately classify and predict human behaviour. To account for imprecise information, we incorporate probabilistic models into the algorithm to allow it to make predictions with uncertainty. To evaluate the performance of our proposed approach, we use standard metrics, such as precision, recall, and F1 score, and compare our results to existing methods. We also identify the limitations of existing approaches and propose new methods for interpreting and understanding images that can improve their accuracy and reliability. Our proposed approach has the potential to provide a more accurate and robust method for interpreting and understanding images of human behaviour in monitoring systems. It can be used in various applications like traffic monitoring, security systems, and surveillance. Our results demonstrate the importance of incorporating imprecise information into deep learning algorithms to improve their performance and highlight the potential for future research in this area. © 2023 IEEE.

关键词： autonomous car computer vision pedestrian safety smart city

来源：评论

学校读者我要写书评

暂无评论

An Investigation on Classical Methods and Unsupervised Deep Learning algorithms for image Segmentation in High Variance images for Industrial Application

An Investigation on Classical Methods and Unsupervised Deep ...

引用

Irish Signals and systems conference (ISSC)

作者： Nathan Henry Tamás Reiter

ISBN: (数字)9798350352986

ISBN: (纸本)9798350352993

This paper investigates classical image processing techniques and unsupervised deep learning algorithms for segmenting images with high variance for an under researched industrial problem, focusing on beam burns generated by Focused Ion Beam (FIB) technology. Classical methods (CM) include preprocessing techniques such as edge detection, while Deep Learning (DL) employs Convolutional Neural Networks (CNNs) for unsupervised image segmentation. Experimental results demonstrate the superior accuracy of DL, but with increased computational overhead, in contrast to the efficiency and controllability of CM. Combining both approaches offers a potential solution for optimizing accuracy and efficiency in image segmentation.

关键词： Deep learning image segmentation Accuracy image edge detection Current measurement Noise reduction Noise

来源：评论

学校读者我要写书评

暂无评论

Feature Decoupled Autoencoder: Semi-Supervised Learning for image Dehazing

Feature Decoupled Autoencoder: Semi-Supervised Learning for ...

引用

2022 IEEE International conference on Multimedia and Expo, ICME 2022

作者： Wang, Jindong Wang, Fan Yin, Dong School of Information Science and Technology University of Science and Technology of China China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Single image dehazing plays an important role in image processing. Now, most image dehazing methods only use synthetic datasets to train models which produce some poor results on the real hazy images. To solve this problem, we propose a new network named feature decoupled autoencoder which can be trained by semi-supervised learning due to the real hazy images lacking labels. Our autoencoder includes a feature decoupled encoder and a feature fusion decoder. The clear image feature and the hazy feature are decomposed by the encoder and merged by the decoder. When the hazy feature is set to 0, the decoder will produce a dehazing image relying on the clear image feature. By training on the synthetic datasets and real datasets together, our model has good dehazing ability on the real-world hazy images. On the HazeRD and SOTS, our model's performance is comparable to the state-of-the-art algorithms. © 2022 IEEE.

关键词： Signal encoding

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 << < 84 85 86 87 88 89 90 91 92 93 > >>

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：