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

13,266 篇 会议
211 篇 期刊文献
183 册 图书
3 篇 学位论文
1 篇 资讯

馆藏范围

13,664 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

7,046 篇 工学
- 4,663 篇 计算机科学与技术...
- 2,299 篇 软件工程
- 2,127 篇 电气工程
- 1,341 篇 信息与通信工程
- 868 篇 控制科学与工程
- 697 篇 光学工程
- 499 篇 生物医学工程（可授...
- 476 篇 电子科学与技术（可...
- 469 篇 机械工程
- 460 篇 仪器科学与技术
- 331 篇 生物工程
- 242 篇 测绘科学与技术
- 168 篇 材料科学与工程（可...
- 160 篇 航空宇航科学与技...
- 147 篇 交通运输工程
- 107 篇 安全科学与工程
- 92 篇 化学工程与技术
3,500 篇 理学
- 2,414 篇 物理学
- 937 篇 数学
- 388 篇 生物学
- 249 篇 系统科学
- 237 篇 统计学（可授理学、...
- 122 篇 化学
1,508 篇 医学
- 1,337 篇 临床医学
- 211 篇 特种医学
- 170 篇 基础医学(可授医学...
- 111 篇 药学(可授医学、理...
723 篇 管理学
- 436 篇 管理科学与工程(可...
- 311 篇 图书情报与档案管...
- 89 篇 工商管理
61 篇 法学
60 篇 农学
31 篇 教育学
29 篇 经济学
28 篇 文学
20 篇 军事学
17 篇 艺术学
1 篇 哲学

主题

2,767 篇 image processing
1,434 篇 image segmentati...
1,169 篇 signal processin...
624 篇 feature extracti...
620 篇 cameras
586 篇 image edge detec...
568 篇 signal processin...
492 篇 image coding
491 篇 image reconstruc...
479 篇 real-time system...
399 篇 algorithm design...
352 篇 image color anal...
316 篇 deep learning
314 篇 image enhancemen...
310 篇 pixel
307 篇 real time system...
303 篇 image analysis
302 篇 computer archite...
300 篇 hardware
298 篇 object detection

机构

22 篇 signal and image...
20 篇 samara national ...
14 篇 school of electr...
11 篇 samara national ...
11 篇 purdue univ sch ...
11 篇 univ texas san a...
11 篇 department of el...
11 篇 school of electr...
10 篇 samara national ...
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 university of ch...
8 篇 electrical compu...
8 篇 image processing...
8 篇 information syst...
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
9 篇 c.-c.j. kuo
8 篇 frank hannig
8 篇 hannig frank
8 篇 ilias maglogiann...
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
7 篇 kupriyanov a.v.
7 篇 yves wiaux

语言

13,114 篇 英文
460 篇 其他
87 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 IV"

共 13664 条记录，以下是1511-1520 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：

FedDHr: Improved Adaptive Learning Strategy Using Federated Learning for image processing

FedDHr: Improved Adaptive Learning Strategy Using Federated ...

引用

Self Sustainable Artificial Intelligence systems (ICSSAS), International conference on

作者： Anuhya Velagapudi Jhansi B. Hemalikha M. P. Vijayalakshmi Department of Artificial Intelligence and Data Science Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

FL (Federated learning) has grown in popularity as a field of research that allows for the training of an algorithm over many decentralised servers that are having local data samples without requiring data exchange. Numerous application domains (like medical image analysis diagnosis made by doctors) lack a significant amount of properly labeled and full data that can be found in one place. Due to the prevalence of artificial intelligence in new application sectors, there are few rising issues on privacy of data and user. New algorithms of various research works are analysed in this study and it introduces a new technique that address the data heterogeneity and adaptive learning rate of the model to perform image processing, Deep Learning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cluster Analysis: Unsupervised Classification for Identifying Benign and Malignant Tumors on Whole Slide image of Prostate Cancer 5

Cluster Analysis: Unsupervised Classification for Identifyin...

引用

5th IEEE International conference on image processing Applications and systems (IPAS)

作者： Bhattacharjee, Subrata Hwang, Yeong-Byn Sumon, Rashadul Islam Rahman, Hafizur Hyeon, Dong-Woo Moon, Damin Carole, Kouayep Sonia Kim, Hee-Cheol Choi, Heung-Kook Inje Univ Dept Comp Engn Gimhae South Korea Inje Univ Dept Digital Antiaging Healthcare Gimhae South Korea JLK Artificial Intelligence R&D Ctr Seoul South Korea

ISBN: (纸本)9781665462198

Recently, many fields have widely used cluster analysis: psychology, biology, statistics, pattern recognition, information retrieval, machine learning, and data mining. Diagnosis of histopathological images of prostate cancer is one of the routine tasks for pathologists and it is challenging for pathologists to analyze the formation of glands and tumors based on the Gleason grading system. In this study, unsupervised classification has been performed for differentiating malignant (cancerous) from benign (non-cancerous) tumors. Therefore, the unsupervised-based computer-aided diagnosis (CAD) technique would be of great benefit in easing the workloads of pathologists. This technique is used to find meaningful clustering objects (i.e., individuals, entities, patterns, or cases) and identify useful patterns. Radiomic-based features were extracted for cluster analysis using the gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and gray-level size zone matrix (GLSZM) techniques. Multi-clustering techniques used for the unsupervised classification are K-means clustering, K-medoids clustering, Agglomerative Hierarchical (AH) clustering, Gaussian mixture model (GMM) clustering, and Spectral clustering. The quality of the clustering algorithms was determined using Purity, Silhouettes, Adjusted Rand, Fowlkes Mallows, and Calinski Harabasz (CH) scores. However, the best-performing algorithm (i.e., K-means) has been applied to predict and annotate the cancerous regions in the whole slide image (WSI) to compare with the pathologist annotation.

关键词： unsupervised classification prostate cancer radiomic texture feature histopathological

来源：评论

学校读者我要写书评

暂无评论

Improving The Hiding Capacity of image Steganography with Stego-Analysis

Improving The Hiding Capacity of Image Steganography with St...

引用

Integrated Circuits and Communication systems (ICICACS), IEEE International conference on

作者： Padmaja Grandhe A.Mallikarjuna Reddy Kavyasri Chillapalli Kavya Koppera Manasa Thambabathula L P Reddy Surasani CSE Department PSCMRCET Vijayawada India Department of CSE Anurag University Hyderabad India

Communicating online without fearing third-party interventions is becoming a challenge in the modern world. Especially the sectors like the military, and government organizations or private companies sharing sensitive information. They invest a lot of effort and cost into obtaining the advancement of safe communication techniques. image processing encryption techniques using various algorithms promote security over communication channels and using different analysis methods make the tool stand out in providing security to the information. In today's world, there are various steganographic mechanisms that convert the secret message into stego medium and send it across various communication channels. Using algorithms like Blind Hide promotes the security of the message along with using multiple analysis methods that will further improve the tool in giving out information of encoded accuracy, size of stego of the secret message. The aim is to generate a tool that will give out a benchmark value of how precisely the message is stored in the cover file. Using Stego and bulk analysis the information about the presence of the stego medium in the message can be known to the user. All these analysis methods make the tool more enhanced and secure.

关键词： Integrated circuits Steganography Costs Communication systems image processing Government Communication channels

来源：评论

学校读者我要写书评

暂无评论

An improved visual reality experience for gaming applications using visual image processing

An improved visual reality experience for gaming application...

引用

International conference on Computing and Networking Technology (ICCNT)

作者： E. D. Kanmani Ruby Anita Titus R. Anitha P. Vijayakumari S. Ravi Department of ECE Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Chennai Department of ECE Jeppiaar University Chennai Department of AI & DS S.A. Engineering College Chennai Department of ECE Sairam Engineering College Chennai Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Saveetha University Chennai

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Digital and augmented truth has increased in recent years, with several packages in various industries. Gaming is one such industry that has benefitted significantly from those technologies, supplying customers with an immersive and interactive revel. But there’s nevertheless room for improvement, especially in visible photograph processing. Cutting-edge digital and augmented fact systems depend upon pre-rendered three-D picks, which could bring a lower fine and much less realistic visual experience. This is especially obtrusive in rapid-paced gaming packages, where photographs may appear pixilated or need more elements. To deal with this difficulty, our research proposes an advanced visual fact enjoyed by gaming applications using superior visible picture processing techniques. Our method mainly includes the realtime processing of visual data to create exceptional realism in the digital environment. This may encompass strategies, texture mapping, dynamic lights, and superior rendering algorithms.

关键词： Industries Visualization Heuristic algorithms Virtual environments Rendering (computer graphics) Paints image enhancement

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence and its Algorithmic Foundations Reshaping the Future

Artificial Intelligence and its Algorithmic Foundations Resh...

引用

International conference on ICT in Business Industry & Government (ICTBIG)

作者： Shalini M Bharat Bhushan Mithun Kumar S Gajanan H Chavhan A. Thangamani Sourav Rampal Department of ECE Prince Shri Venkateshwara Padmavathy Engineering College Chennai Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Mangement - UG Management JAIN (Deemed to be University) Bangalore Karnataka India E&TC Vishwakarma Institute of Technology Pune India Department of Chemistry Karpagam Academy of Higher Education Coimbatore Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

Because AI is built on formulas, numerous industries are evolving. This study examines three types of networks: genetic algorithms, convolutional neural net-works (CNNs), and long short-term memory networks (LSTMs). It investigates how advanced AI approaches influence these networks. This method combines many algorithms to create a versatile artificial intelligence system capable of solving issues. CNNs, on the other hand, acquire hierarchical features quickly and function well with images, while LSTMs excel at sequential data and other tasks. GAs employs genetic optimization to strengthen and improve response capabilities. By combining these technologies in novel ways, you may improve their optimization, natural language processing, and image identification. Even though artificial intelligence is still in its early stages, this study demonstrates the importance of algorithmic roots in predicting when smart systems may begin to challenge technology again.

关键词： Transforms Reinforcement learning Prediction algorithms Smart systems Natural language processing Artificial intelligence Optimization Long short term memory Genetic algorithms Testing

来源：评论

学校读者我要写书评

暂无评论

Research on Traditional Art image Reconstruction Method Based on Computer Vision Analysis

Research on Traditional Art Image Reconstruction Method Base...

引用

Communication, Security and Artificial Intelligence (ICCSAI), International conference on

作者： M. Supriya Kuncham Anvesh B Muruganandham Manasa Krishnan K R Muthu K. Murugan Department of ECE KPR Institute of Engineering and Technology

In the framework of the digital era, the technology of image processing is one of the technologies that is being used increasingly often in all aspects of modern life. image correction may be handled using algorithms based on computer vision, which can increase the correction's influence on the image as a whole. The conventional method of identifying structural systems collects data via the use of wired or wireless measuring systems. The process of establishing sensors and the equipment used for data collection is laborious and takes a lot of time. The process has two stages: the first is the extraction of the line drawing, and the second is the rendering of the line drawing. An edge detection approach that integrates low-level and middle-level visual information is used to extract the line drawing in the process of on-line drawing extraction. This method is used to extract the drawing. The edges are then simplified and linked in accordance with the computer vision theory. Additionally, the image processing technology is used as the research object in order to develop a scientific model for the distorted image. These steps are based on the findings of traditional edge detection. image restoration can be helped along by filtering samples of the image and getting rid of any noise that is there. The fundamentals of computer vision and the technologies that are connected to it are broken down in detail, and the behavioral patterns of visual interaction are investigated. The image of Chinese traditional art serves both the role of art communication and as a medium and symbol for cultural communication. At the same time, it carries on the legacy of a fine traditional culture that has been passed down from generation to generation in China. The image processing technology that is based on computer vision algorithms provides a bigger number of benefits, in addition to a better degree of accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Pre-processing Technique For Eye image Segmentation

An Enhanced Pre-Processing Technique For Eye Image Segmentat...

引用

Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), International conference on

作者： Satrughan Kumar Arun Kumar Deepti Sahu Computer Science and Engineering Sharda University Greater Noida U.P India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Early diagnosis is essential to controlling glaucoma, a progressive disorder that results in irreversible vision loss. Retinal fundus imaging has emerged as a crucial diagnostic technique for retinal disorders, such as glaucoma, in recent times. But because of the intricate vascular patterns and intricate architecture of the retina, it can be difficult to analyze these images appropriately. Areas of interest in fundus pictures are frequently found using image segmentation algorithms; however, this can be challenging. This study examines a variety of segmentation techniques, emphasizing both conventional and cutting-edge ways for splitting retinal fundus pictures. It also covers assessment metrics that are used to evaluate how well segmentation algorithms perform in identifying minute structural alterations associated with glaucoma. The study also looks at how deep learning algorithms can be implemented to separate optic disc and cup. Deep learning models typically perform worse with larger datasets, even though they have demonstrated good accuracy with smaller datasets. The investigation underscores the need for more sophisticated deep learning methodologies and efficient segmentation techniques, as it shows that effectively segmenting the optic disc (OD) and cup (OC) remains a considerable challenge, particularly for large and complex datasets.

关键词： Deep learning Glaucoma Measurement Learning systems image segmentation Accuracy Refining Lighting Retina Optical imaging

来源：评论

学校读者我要写书评

暂无评论

Character Recognition Technique Implementation for Complicated Deteriorated Scene

Character Recognition Technique Implementation for Complicat...

引用

International conference on Information systems and Computer Networks (ISCON)

作者： Saurabh Sharma Binay Kumar Pandey Digvijay Pandey Rohit Anand Arti Sharma Shilpa Saini KIET Group of Institutions Delhi NCR Ghaziabad India College of Technology Govind Ballabh Pant University of Agriculture and Technology Pantnagar India IET Dr. A.P.J. Abdul Kalam Technical University Uttar Pradesh India G.B. Pant DSEU Okhla-1 Campus (formerly GBPEC) New Delhi India Department of Computer Science and Engineering University Centre for Research and Development Chandigarh University Gharuan Mohali India

There has been an increase in interest in digitizing and preserving old books and papers in the last few years. The quick advancement of data innovation and the Internet’s quick spread has also contributed to the enormous volume of image and video data. The texts that are included in the image and video assist us in analyzing them and are also utilized for indexing, archiving, and retrieval. Different noises, such as Gaussian noise, salt and pepper noise, speckle noise, etc., can readily damage an image. Several image filtering algorithms, including the Gaussian filter, mean filter, median filter, etc., are employed to eliminate these various noises from images. This article analyses the impact of several pre-processing approaches, such as thresholding, morphology, and blurring procedures, to maximise text extraction strategies. The experiment’s findings demonstrate that pre-processing approaches unquestionably improve the document’s structural and visual quality.

关键词： Visualization Technological innovation Gaussian noise Morphology Filtering algorithms Speckle image filtering

来源：评论

学校读者我要写书评

暂无评论

Deepfake image and Video Detection Using Deep Learning algorithms

Deepfake Image and Video Detection Using Deep Learning Algor...

引用

Multi-Agent systems for Collaborative Intelligence (ICMSCI), International conference on

作者： Srivanth Srinivasan Nischitha P Akshita Chavan Mohana Artificial Intelligence & Machine Learning Engineering RV College of Engineering® Bengaluru India Computer Science & Engineering (Cyber Security) RV College of Engineering® Bengaluru India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

Deep learning (DL) algorithms are swiftly finding applications in computer vision and natural language processing. Nonetheless, they can also be employed for creating convincing deepfakes, which are challenging to distinguish from reality. The advancements in image and video technology and tools, especially on social media platforms, potentially lead to misuse for malicious purposes like blackmail or defamation. To tackle this issue, several group of researchers tried upon spreading or creating awareness on real or fake data. The proposed approach involves combining Deepfake generation using GANs and Autoencoders with a Deepfake detection method. The aim of this initiative is exclusively to combat disinformation and online fraud for the welfare of the general population. Deepfakes, products of AI, have become increasingly realistic, rendering it nearly difficult to distinguish the content. Auto-encoders with sufficient time can achieve about 92 % accuracy. As the generator improves, the discriminator performance worsens as it struggles to differentiate real or fake data. A perfect generator results in 50% accuracy. With advancements in computational capacity and data availability, the proposed DDM (Deepfake Detection Model) has achieved greater accuracy rate of up to 92.3%.

关键词： Deep learning Deepfakes Accuracy Social networking (online) Streaming media Feature extraction Generators Convolutional neural networks Artificial intelligence Research and development

来源：评论

学校读者我要写书评

暂无评论

Real-time image Edge Detection System Design and algorithms for Artificial Intelligence FPGAs

Real-time Image Edge Detection System Design and Algorithms ...

引用

2022 International conference on Artificial Intelligence of Things and Crowdsensing (AIoTCs)

作者： Caizeng Ye Shandong Institute of Commerce and Technology Jinan China

Extraction of image edges is the basis of image processing class algorithms, for image edge extraction is of great significance. Nowadays, video image data is greatly increases the amount of image data and the processing difficulty. FPGA technology stands out for its parallel processing method and pipeline structure, which enables high-speed processing of large amounts of image data, and its high processing speed ensures real-time image data processing. The application of FPGA technology in the field of image data processing will be unstoppable. The main objective of this paper is to investigate the design and algorithms of a real-time image edge detection system using artificial intelligence and FPGAs. Median filtering and edge detection algorithms in video acquisition and pre-processing systems are an important part of complex algorithms in the field of target recognition and tracking, and the quality of image pre-processing plays an important role in the high accuracy of subsequent algorithms. This paper presents an in-depth study and analysis of the hardware implementation of the HD video capture and pre-processing system, combining the characteristics of FPGA parallel high-speed and pipeline structure, and completes the system design and verification on the hardware platform, fully proving the feasibility and correctness of the system.

关键词： Target tracking image edge detection Streaming media Real-time systems Hardware Detection algorithms Artificial intelligence

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 << < 148 149 150 151 152 153 154 155 156 157 > >>

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：