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

15,887 篇 会议
364 篇 期刊文献
193 册 图书

馆藏范围

16,444 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,342 篇 工学
- 5,434 篇 计算机科学与技术...
- 2,999 篇 软件工程
- 2,166 篇 电气工程
- 1,868 篇 信息与通信工程
- 1,128 篇 控制科学与工程
- 890 篇 光学工程
- 647 篇 机械工程
- 642 篇 电子科学与技术（可...
- 539 篇 仪器科学与技术
- 539 篇 生物医学工程（可授...
- 477 篇 生物工程
- 226 篇 测绘科学与技术
- 219 篇 交通运输工程
- 203 篇 材料科学与工程（可...
- 199 篇 航空宇航科学与技...
- 163 篇 化学工程与技术
- 160 篇 网络空间安全
- 141 篇 安全科学与工程
4,016 篇 理学
- 2,399 篇 物理学
- 1,361 篇 数学
- 527 篇 生物学
- 368 篇 统计学（可授理学、...
- 341 篇 系统科学
- 207 篇 化学
1,522 篇 医学
- 1,349 篇 临床医学
- 201 篇 特种医学
- 197 篇 基础医学(可授医学...
1,055 篇 管理学
- 613 篇 管理科学与工程(可...
- 482 篇 图书情报与档案管...
- 139 篇 工商管理
84 篇 法学
66 篇 农学
45 篇 经济学
44 篇 教育学
37 篇 军事学
32 篇 文学
26 篇 艺术学
1 篇 哲学

主题

2,783 篇 image processing
1,552 篇 image segmentati...
1,511 篇 signal processin...
868 篇 feature extracti...
656 篇 image edge detec...
636 篇 cameras
633 篇 signal processin...
611 篇 real-time system...
579 篇 image reconstruc...
519 篇 image coding
498 篇 algorithm design...
401 篇 deep learning
399 篇 clustering algor...
398 篇 image color anal...
383 篇 object detection
370 篇 image enhancemen...
357 篇 accuracy
334 篇 hardware
323 篇 image analysis
312 篇 computer vision

机构

40 篇 xi'an jiaotong u...
32 篇 northwestern pol...
31 篇 xi an jiao tong ...
30 篇 school of electr...
29 篇 school of electr...
26 篇 university of ch...
24 篇 xi an jiao tong ...
22 篇 xi an jiao tong ...
22 篇 national laborat...
21 篇 signal and image...
19 篇 samara national ...
18 篇 xidian universit...
16 篇 school of inform...
16 篇 institute of art...
15 篇 tsinghua univers...
15 篇 department of el...
15 篇 school of automa...
15 篇 national key lab...
15 篇 school of comput...
14 篇 school of electr...

作者

38 篇 chen xi
29 篇 xi chen
24 篇 nanning zheng
24 篇 licheng jiao
20 篇 li xi
20 篇 liu ying
18 篇 xuelong li
17 篇 anon
14 篇 xi ning
14 篇 wei li
14 篇 yuan yuan
13 篇 de-shuang huang
13 篇 yanning zhang
13 篇 xi li
12 篇 jie yang
12 篇 yang xi
12 篇 ying liu
11 篇 p. pirsch
11 篇 liu yang
11 篇 mingyi he

语言

16,020 篇 英文
279 篇 其他
135 篇 中文
20 篇 土耳其文
3 篇 葡萄牙文
2 篇 法文
2 篇 俄文
1 篇 西班牙文

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

共 16444 条记录，以下是1581-1590 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：

Integrated Design of image processing and Flight Control Based on AMP Architecture

Integrated Design of Image Processing and Flight Control Bas...

引用

International conference on Electronics and Information Technology (EIT)

作者： Songkun Yan Zhuo Xu Tengfei Ma Yike Wang Xi'an Institute of Modern Control Technology Xi’an China

ISBN: (数字)9798350369151

ISBN: (纸本)9798350369168

The ongoing development of intelligent ammunition has resulted in an expansion of the functions that such ammunition must perform, thereby increasing the demand for internal computing capabilities in both scale and complexity. In light of the diverse functional requirements, traditional single-processor architectures are inadequate to address the needs of these varied and complex tasks. Consequently, this article presents an integrated image processing and flight control technology based on an Asynchronous Multi-Processor (AMP) architecture. This approach consolidates two tasks with distinct requirements into a single module, effectively addressing the challenges associated with information exchange between tasks. The feasibility of this method has been validated through simulation testing.

关键词： Missiles image segmentation Program processors Target recognition Computer architecture Software systems Stability analysis Thermal stability Aerospace control Testing

来源：评论

学校读者我要写书评

暂无评论

Crops Classification Using Machine Learning And Google Earth Engine 14

Crops Classification Using Machine Learning And Google Earth...

引用

14th International conference on Intelligent systems: Theories and Applications, SITA 2023

作者： Achahboun, Chakir Chikhaoui, Mohamed Naimi, Mustapha Bellafkih, Mostafa Iav Hassan 2 Ressources Naturelles et Environnement Rabat Morocco Institut National des Postes et Télécommunications Rabat Morocco

ISBN: (纸本)9798350308211

The primary objective of this study was to address the critical challenge of obtaining accurate information regarding the spatial distribution and classification of crops in agricultural areas. The aim was to enhance agricultural decision-making and management, especially in regions with limited water resources, where crop productivity and sustainability are crucial for achieving food security and sustainable development. To achieve this objective, this study utilized machine-learning classification algorithms in conjunction with Landsat and Sentinel satellite imagery. The classification of different crops was based on Normalized Difference Vegetation Index (NDVI) phenology. The classification process and post-processing were conducted using the Google Earth Engine (GEE) platform , as well as utilizing Python, and scikit-learn library. Ground-truth data provided by local experts, along with the EUROMAP 2018 dataset in South Spain, were used to label the classification results. The findings of this study demonstrated a classification accuracy of 72% for certain crop types, indicating significant implications for sustainable agricultural practices and land use planning. © 2023 IEEE.

关键词： image classification

来源：评论

学校读者我要写书评

暂无评论

Application of AI in Histopathological image Analysis 1

引用

1st Serbian International conference on Applied Artificial Intelligence, SICAAI 2022

作者： Štifanic, Jelena Štifanić, Daniel Zulijani, Ana Car, Zlatan Faculty of Engineering University of Rijeka 58 Vukovarska Street Rijeka51000 Croatia Department of Oral Surgery Clinical Hospital Center of Rijeka 40 Krešimirova Street Rijeka51000 Croatia

ISBN: (数字)9783031297175

ISBN: (纸本)9783031297168

Over the past decade, improvements in image analysis methods and substantial advancements in the processing power have allowed the development of powerful computer-aided analytical approaches to medical data. Tissue histology slides can now be scanned and preserved in digital form, thanks to the recent introduction of entire slide digital scanners. In such a form, they can serve as input data for Artificial Intelligence (AI) algorithms that can speed up standard procedures for histology analysis with high accuracy and precision. This research aimed to create an automated system based on AI for histopathological image analysis. The first step was normalizing H&E-stain images and then using them as input to the convolutional neural network. The best results are achieved using ResNet50 with the highest AUC value of 0.98 (±σ = 0.02). Such an approach proved to be successful in analyzing histopathological images. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Histology

来源：评论

学校读者我要写书评

暂无评论

Construction and Characteristic Analysis of Two-Layer Complex Network Model

Construction and Characteristic Analysis of Two-Layer Comple...

引用

International conference on image, Vision and Intelligent systems, ICIVIS 2023

作者： Tang, Chunyang Ye, Zhonglin Zhao, Haixing xiao, Yuzhi Bai, Libing College of Computer Qinghai Normal University Xining810008 China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining810008 China Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province Xining810008 China Key Laboratory of Tibetan Information Processing Ministry of Education Xining810008 China

ISBN: (纸本)9789819708543

To characterize the homogeneity and heterogeneity between nodes or connecting edges, we considered the multi-relationship attributes of nodes and constructed six dual-layer network models. Firstly, based on node homogeneity, we constructed three homogeneous two-layer network models (GEE,R), (GWW,R) and (GBB,R) using the same generation algorithm for intra-layer connections and random connections for inter-layer connections. Secondly, based on node heterogeneity, we constructed three heterogeneous two-layer network models (GEW,R), (GBE,R) and (GBW,R) using different generation algorithms for intra-layer connections and random connections for inter-layer connections. Then, we derived the average degree analytical expressions and node degree distribution analytical expressions for the six two-layer networks. Finally, according to the differences in inter-layer connection probabilities, we depict the experiments with node degree distribution. Experiments have shown that the node degree distribution of (GEW,R) networks exhibits a bimodal characteristic, while the node degree distribution of (GBE,R) networks presents both Power-law and unimodal mixed characteristics. Overall, this study provides insights into the characteristics of different two-level network models and their application in modeling complex systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Complex networks

来源：评论

学校读者我要写书评

暂无评论

Region based image Contrast Enhancement Depending on Local Dominant Colour Component

Region based Image Contrast Enhancement Depending on Local D...

引用

International conference on Imaging, Signal processing and Communication (ICISPC)

作者： Debashis Das Diptadip Maiti Dept. of CSE Techno India University West Bengal India

ISBN: (数字)9798350367157

ISBN: (纸本)9798350367164

In this paper, we propose an image contrast enhancement mechanism by analysing the dominant colour component of every contributory pixel. The contrast enhancement is performed on the regions having similar dominating colour components by employing local histogram equalization. The process ensures the increment of the colour purity by preserving the level of brightness which is a major drawback of histogram equalization-based methods. The proposed method provides satisfactory results without any learning mechanism applied in the system which reduces the execution time of the process as well. The proposed algorithm is formulated, experimented and tested on a large set of standard colour images, in RGB format, collected from various databases. We compare the proposed method with both standalone and learning based image enhancement algorithms from the literature. The comparative analysis establishes the efficacy of the proposed method.

关键词： Learning systems Histograms Phase measurement image color analysis Signal processing algorithms Imaging Signal processing

来源：评论

学校读者我要写书评

暂无评论

Application of Lossless Compression Method in image Compression

Application of Lossless Compression Method in Image Compress...

引用

International conference on Information systems and Computer Aided Education (ICISCAE)

作者： Weifeng Ni Tianqiu Pu Yuxi Wang College of Information Science and Engineering Hohai University Changzhou China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

This paper is based on the application of lossless compression algorithms in image compression, aiming to solve problems such as insufficient storage space, low transmission efficiency, and heavy data processing burden. In order to optimize the image lossless compression algorithm, a combination of Huffman encoding and LZW compression algorithm is proposed. The implementation process and advantages and disadvantages of the two are compared, and the compression ratio and encoding efficiency of image lossless compression technology are discussed. We need to optimize decoding speed, image quality, and other aspects to improve overall image lossless compression capability. By applying Huffman encoding and LZW compression algorithms to images separately, the results show that Huffman encoding can dynamically construct the optimal encoding based on the frequency of characters appearing in image data, while LZW technology is good at utilizing repeated patterns and contextual information in image data to further improve compression efficiency by establishing dictionaries. The complementary advantages of the two can further improve the lossless compression ability of images.

关键词： image quality Deep learning image coding Dictionaries Propagation losses Decoding image storage Huffman coding Compression algorithms Information systems

来源：评论

学校读者我要写书评

暂无评论

Ayurvedic Medicinal Plant Identification System Using Embedded image processing Techniques 1

引用

4th International conference on Communication, Computing and Electronics systems, ICCCES 2022

作者： Das, Arnab Siva Sai Kumar, B. Shiva Shankar Reddy, S. Naveen Reddy, S. Peeyush, K.P. Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (数字)9789811977534

ISBN: (纸本)9789811977527

Plants can be classified based on various classification methods such as cell, genetic and serum etc. It's difficult for an individual to explore the various classification methods and it's practically not feasible as it demands good knowledge in plant taxonomy and long-term time investment. Due to the shortage of experienced and qualified taxonomists in identification and classification of medicinal plants, with the help of different image processing algorithms and computer vision, the above difference can be bridged. The main objective is to develop a Deep Learning and Machine Learning based model to identify and classify plants based on various features, which is done with the help of Gabor filter and Gray Level Co-occurrence Matrices (GLCM) and using classifiers such as Random Forest (RF), and Light Gradient Boosting Machine (LGBM), and made a comparative analysis which resulted an accuracy of 95.5% with LGBM and GLCM filter and used to develop a standalone device that clicks a picture and identifies the medicinal plant. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Gabor filters

来源：评论

学校读者我要写书评

暂无评论

RecOpt: A Recommender-Based Optimization Framework for Enhanced Multi-Objective Decision-Making in Autonomous Driving

RecOpt: A Recommender-Based Optimization Framework for Enhan...

引用

image processing, Computer Vision and Machine Learning (ICICML), International conference on

作者： Sihan Chen Zheng Lan xiupeng Shi School of Microelectronics Shanghai University China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Autonomous driving systems operate in highly complex environments, necessitating real-time, balanced decisionmaking across multiple objectives such as safety, efficiency, and passenger comfort. This study introduces RecOpt, a novel framework that combines recommender algorithms with advanced optimization techniques to enhance multi-objective optimization (MOO) in decision-making. RecOpt tackles the challenges of large-scale mixed-integer MOO by identifying and restructuring key decision variables, thereby reducing the optimization scale and increasing efficiency. By integrating recall and finesorting technologies inherent in recommender systems, RecOpt efficiently screens and selects optimal solutions, surpassing the speed and scalability limitations of traditional MOO methods. Experiments utilizing the NGSIM dataset validate RecOpt’s efficacy in balancing safety, comfort, and efficiency, minimizing decision-making latency, and adapting to dynamic environments. Furthermore, RecOpt offers data-driven insights into explainable decision-making, providing a robust and transparent model for autonomous vehicle decision processes.

关键词： Machine learning algorithms Scalability image processing Decision making Real-time systems Safety Vehicle dynamics Optimization Autonomous vehicles Recommender systems

来源：评论

学校读者我要写书评

暂无评论

AI-Enable Machine Learning for Lung Cancer Prediction and Classification 1

AI-Enable Machine Learning for Lung Cancer Prediction and Cl...

引用

1st International conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Singh, Kamred Udham Kumar, Ankit Sinha, Anurag Kumar, Gaurav Singh, Teekam Pandey, Saroj Kumar School of Computing Graphic Era Hill University Dehradun India Gla University Department of Computer Engineering & Apllications UP Mathura India Amity University Department of Computer Science Ranchi India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350330915

In comparison to other types of cancer, lung cancer has the highest fatality rate, making it one of the most dangerous illnesses in the world. In India, there are over 70,000 new cases recorded each year, which demonstrates a startlingly rapid growth in the frequency of the disease. Lung cancer's sneaky nature makes early detection difficult. Early lung cancer identification improves survival rates, making it a top priority. Technology is crucial for early detection since it is more reliable. Many scholars have proposed innovative concepts after extensive study. Computer-Aided Diagnosis (CAD) systems, which use computers to diagnose, are a major advancement in this field. These cutting-edge methods employ machine learning, deep learning, and image processing to predict malignant lung cancer risk. This article evaluates and compares technologies for early lung cancer detection and diagnosis. This category includes image segmentation, feature extraction, and classification algorithms. This essay examines these current technological options to help fight this life-threatening sickness. The article's ultimate goal is to improve the outlook for those who are at risk of acquiring lung cancer due to the sickness. © 2023 IEEE.

关键词： CAD Classification CT Scan Lung Cancer MRI PET Pre-processing ReLU

来源：评论

学校读者我要写书评

暂无评论

Joint Visual and Semantic Information image Retrieval

Joint Visual and Semantic Information Image Retrieval

引用

image processing, Computer Vision and Machine Learning (ICICML), International conference on

作者： Ziao Qin xinyue Hu Yijia Chen Qingyun Xu Zhenting Li Northwestern Polytechnical University Xi'an China Oxford Brookes University Brookes UK Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

In image retrieval, there exists a "semantic gap" problem, which refers to the discrepancy between the image semantics understood by computers through extracted image features and the image semantics perceived by humans. This paper studies an image retrieval algorithm based on image visual information and semantic information. The algorithm utilizes image features combined with hash encoding to describe the visual characteristics of images, and employs a word vector generation model to convert semantic words of images into word vectors, thereby describing the semantic features of the images. To better combine the similarities of visual features and semantic features, the algorithm establishes a reranking retrieval matrix for image searching. The paper validates the effectiveness of the proposed algorithm through experiments, demonstrating that the retrieved images highlighted by this algorithm are consistent in terms of semantic information while ensuring the similarity of visual features.

关键词： Visualization image coding Machine learning algorithms Semantics image retrieval Machine learning Feature extraction Vectors Matrix converters Sorting

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 << < 155 156 157 158 159 160 161 162 163 164 > >>

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：