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1371-1380 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：

6th International conference on Big Data Cloud and Internet of Things, BDIoT 2022

6th International Conference on Big Data Cloud and Internet ...

引用

6th International conference on Big Data Cloud and Internet of Things, BDIoT 2022

ISBN: (纸本)9783031283864

The proceedings contain 49 papers. The special focus in this conference is on Big Data Cloud and Internet of Things. The topics include: Knowledge Embeddings for Explainable Recommendation;Design of Blended Learning Course Based on SPOC for Primary School Teachers: Case of Soft Skills;the Impact of the Online Flipped Classroom on the Learning Outcomes and Motivation of Nursing Students in Computer Science;digitizing Writing: An Empirical Exploratory Study Towards Students’ Writing Skill Fluency Improvement in ‘Padletosphere’;AraBERT with GANs for High Performance Fine-Grained Dialect Classification;genetic-Novelty Oversampling Technique for Imbalanced Data;neural Network for Arabic Text Diacritization on a New Dataset;processing Time Performance Analysis of Scheduling algorithms for Virtual Machines Placement in Cloud Computing Environment;Business - IT Alignment in Cloud Environment Comparative Study;machine Learning-Based Intrusion Detection System: Review and Taxonomy;reduce Cheating in e-Exams Using Machine Learning: State of the Art;comparative Study of Bayesian Optimization Process for the Best Machine Learning Hyperparameters;The Effect of Normalization and Batch Normalization Layers in CNNs Models: Application to Plant Disease Classifications;the Role of Ground Truth Annotation in Semantic image Segmentation Performance for Autonomous Driving;fine-Tuning Pre-trained Vision Transformer Model for Anomaly Detection in Video Sequences;An Efficient Real-Time Moroccan Automatic License Plate Recognition System Based on the YOLO Object Detector;evaluation of Selected Machine Learning Models and Features for Electrical Consumption Prediction in Educational Institutions;Credit Card Fraud Detection Using SVM, Decision Tree and Random Forest Supervised Machine Learning algorithms;SNDAE: Self-Normalizing Deep AutoEncoder for Recommendation;Intelligent Evaluation System Using NLP;retrospective Study and Evaluation of School Failure (Junior High School) in Scientific Subj

关键词：

来源：评论

学校读者我要写书评

暂无评论

Correlation between image and Text from Unstructured Data Using Deep Learning 6

Correlation between Image and Text from Unstructured Data Us...

引用

6th International conference on Computing, Communication, Control and Automation, ICCUBEA 2022

作者： Ghorpade, Tushar H. Shinde, Subhash K. Ramrao Adik Institute of Technology Department of Computer Engineering Navi Mumbai India Lokmanya Tilak College of Engineering Department of Computer Engineering Navi Mumbai India

ISBN: (纸本)9781665484510

Information extraction (IE) is a technique for extracting structured data or knowledge from unstructured data by determining the references to words as well as the relationships between them. IE systems can be used to directly extract knowledge from a text corpus, or to extract useful data from a pile of documents which moreover, can be further analyzed with deep learning algorithms to discover more patterns. In today's era, the internet exhibits several characteristics including unstructured data and noisy text information. Unstructured data may contain audio, image, text, video, etc. Information extraction can be useful for topic detection (Twitter, Digital libraries), Breast Cancer detection and many more applications. The proposed system can exploit deep learning for information extraction using image as well as text and can significantly improve its performance with the inclusion of structured and unstructured data. This paper focuses on extraction of information from unstructured data using various deep learning models and concepts of Natural Language processing (NLP), Long Short Term Networks (LSTM) and for topic extraction used Latent Dirichlet Allocation (LDA) etc. © 2022 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

1st EAI International conference on Intelligent systems and Machine Learning, ICISML 2022

1st EAI International Conference on Intelligent Systems and ...

引用

1st EAI International conference on Intelligent systems and Machine Learning, ICISML 2022

ISBN: (纸本)9783031350771

The proceedings contain 75 papers. The special focus in this conference is on Intelligent systems and Machine Learning. The topics include: Mining Ancient Medicine Texts Towards an Ontology of Remedies – A Semi-automatic Approach;a Novel Oversampling Technique for Imbalanced Credit Scoring Datasets;a Blockchain Enabled Medical Tourism Ecosystem;Measuring the Impact of Oil Revenues on Government Debt in Selected Countries by Using ARDL Model;diagnosis of Plant Diseases by image processing Model for Sustainable Solutions;face Mask Detection: An Application of Artificial Intelligence;a Critical Review of Faults in Cloud Computing: Types, Detection, and Mitigation Schemes;video Content Analysis Using Deep Learning Methods;prediction of Cochlear Disorders Using Face Tilt Estimation and Audiology Data;F2PMSMD: Design of a Fusion Model to Identify Fake Profiles from Multimodal Social Media Datasets;quantum Data Management and Quantum Machine Learning for Data Management: State-of-the-Art and Open Challenges;multivariate Analysis and Comparison of Machine Learning algorithms: A Case Study of Cereals of America;competitive Programming Vestige Using Machine Learning;machine Learning Techniques for Aspect Analysis of Employee Attrition;AI-Enabled Automation Solution for Utilization Management in Healthcare Insurance;Real-Time Identification of Medical Equipment Using Deep CNN and Computer Vision;design of a Intelligent Crutch Tool for Elders;an Approach to New Technical Solutions in Resource Allocation Based on Artificial Intelligence;gesture Controlled Power Window Using Deep Learning;novel Deep Learning Techniques to Design the Model and Predict Facial Expression, Gender, and Age Recognition;a Novel Model to Predict the Whack of Pandemics on the International Rankings of Academia.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Maintaining the Integrity of Online Exams using Computer Vision and image processing

Maintaining the Integrity of Online Exams using Computer Vis...

引用

Artificial Intelligence and Smart systems (ICAIS), International conference on

作者： Nanda Kumar K Nandini Guthikonda Mohammad Adil Abdullah S. Sagar Imambi V. Murali Mohan Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur AP India

Due to the growing popularity of online learning, there is a need for efficient methods to assure the validity of online tests, especially multiple-choice exams (MCQs). The application of computer vision and picture pre-processing techniques is one strategy that has shown potential in this situation. With the use of these methods, cheating may be identified and stopped by analysing photos of the test-taker and their surroundings. In the context of online MCQ tests, this article addresses the possible uses of computer vision and picture pre-processing, including the use of facial recognition algorithms and image segmentation to detect and extract particular items or characteristics. The employment of these strategies offers enormous potential for maintaining the integrity of online education, even if there are still issues to be resolved, such as privacy concerns and the requirement for precise and trustworthy algorithms.

关键词： Computer vision Privacy Ethics image segmentation image resolution Face recognition Employment

来源：评论

学校读者我要写书评

暂无评论

Vision Transformer Based Hash Coding for Efficient image and Audio Retrieval with Global and Local Equilibrium Distance Constraints

Vision Transformer Based Hash Coding for Efficient Image and...

引用

IEEE International conference on systems, Man and Cybernetics

作者： Ye Liu Yan Pan Jian Yin School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China Artificial Intelligence and Big Data Department Lizhi Inc. Beijing & Guangzhou China School of Artificial Intelligence Sun Yat-sen University Zhuhai China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

With the application of efficient retrieval in information systems and retrieval augmented generation with vector database for large language models, hash coding algorithms have made progress in recent years. The rise of transformer technology in the field of deep learning has brought the possibility to further improve the effect of hash coding algorithms. We introduce the vision transformer framework to both images and audios, and propose a novel approach for the tasks of multi-label image retrieval and audio event retrieval. In the proposed hash coding model, global and local equilibrium distance constraints are integrated, so that the hash codes for images can be better obtained through the global hash centers and local similar samples. In order to realize end-to-end training and hash code generation for audios, we adopt the adapter of mel spectrogram, thus the proposed approach can be simply converted and applied to audio hash coding. Comparative experiments verify that better results can be achieved on multiple image and audio datasets.

关键词： Training Computer vision image coding Codes Large language models image retrieval Transformers Encoding Vectors Spectrogram

来源：评论

学校读者我要写书评

暂无评论

Identification of Human image Mapped with Clothing for Dress Selection

Identification of Human Image Mapped with Clothing for Dress...

引用

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

作者： D Prem Raja Kailasam Selvaraj A. Baranidharan Rajkumar Pandiarajan V. Sivakumar V.Baby Shalini Department of Information Technology Kalasalingam Academy of Research and Education Krishnankoil India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

With a significant increase in the fashion market, consumers can shop from the comfort of own home through e-shopping. However, one of the prominent disadvantages is lack of ability to try a garment before buying through Internet; customers may feel unsure about size and yet look. The selection of dress from the proposed system is made realistic and accurate by implementing image processing, machine learning, and AR. The first step to the process is to isolate the human figure from the input image by using feature extraction such as background subtraction, edge-detection and of body part. Once the human figure is isolated, the system is then in a position to place chosen gargets on the corresponding identified points on the human figure. This mapping process encompasses the placement of clothing item's outline and fabric feel on the figure and gender of the user.

关键词： Industries Scalability image edge detection Clothing Machine learning Prediction algorithms Feature extraction User experience Fabrics Internet

来源：评论

学校读者我要写书评

暂无评论

Design of Legal Judgment Prediction on Knowledge Graph and Deep Learning

Design of Legal Judgment Prediction on Knowledge Graph and D...

引用

image processing and Computer Applications (ICIPCA), IEEE International conference on

作者： Fengyun Liu New Business Science Department Anhui Sanlian University Hefei China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

Legal judgment prediction (LJP) remains a critical task designed through legal artificial intelligence systems. LJP plays a crucial role in predicting judgment results in legal systems. Over the past few years, LJPs have attracted significant attention in Courts in China, given their convenience in optimizing legal processes. This article, therefore, seeks to design a legal judgment prediction system based on knowledge graphs and deep learning. To enhance the designed model's inference speed and prediction accuracy and significantly cut down on memory consumption, this article proposes the design of LJP based on knowledge graphs and deep learning, establishing the importance of using the BERT knowledge distillation system that will reduce the element of resource consumption in the design of the model. In this regard, the designed system will play a critical role in the transfer of knowledge through a systemic process that is efficient and faster than the traditional system.

关键词： Deep learning Accuracy Law Memory management Knowledge graphs Predictive models Prediction algorithms Information retrieval Natural language processing Regulation

来源：评论

学校读者我要写书评

暂无评论

GPU-Accelerated Feature Extraction for Real-Time Vision AI and LLM systems Efficiency: Autonomous image Segmentation, Unsupervised Clustering, and Smart Pattern Recognition for Scalable AI processing with 6.6× Faster Performance, 2.5× Higher Accuracy, and UX-Centric UI Boosting Human-in-the-Loop Productivity

GPU-Accelerated Feature Extraction for Real-Time Vision AI a...

引用

IEEE/SEMI conference and Workshop on Advanced Semiconductor Manufacturing

作者： Kiarash Ahi Stewart Wu Satya Sriram Germain Fenger Siemens EDA USA Siemens EDA Belgium Siemens EDA India

ISBN: (数字)9798331531850

ISBN: (纸本)9798331531867

The high computational cost of digital image processing, requiring high-performance hardware and extensive resources, severely limits real-time applications. While advancements in algorithm design and GPU acceleration have significantly improved efficiency, modern AI-driven applications such as large language models (LLMs), Generative AI (GenAI), medical imaging, autonomous vehicle perception, photography, advanced nano-scale semiconductor metrology, satellite image analysis, high-precision manufacturing, robotics, and real-time anomaly detection, still demand further optimization to reduce computational overhead and improve *** this paper, we introduce GPU-Accelerated Feature Extraction to enhance runtime and efficiency in edge-based simulations. Our approach leverages AI-driven clustering, grouping images with similar visual and pattern characteristics to enable adaptive tuning on a small subset before generalizing across the full dataset. This method achieves a 3.78× reduction in ***, rather than processing an entire image, we recognize and extract a single representative pattern or region of interest (ROI) per image, removing redundant data and background noise. This refinement results in an additional 1.74× runtime improvement, culminating in an overall 6.6× speed boost, enhancing Scalable Real-Time AI processing. We also demonstrated that with a similar runtime, the accuracy achieved is 2.5× *** solution, integrated into Calibre SEMSuite™, supports multicloud and real-time deployment for enhanced scalability, usability, and performance, providing users with a powerful tool for fully automated, AI-driven image classification, making high-throughput image review feasible even at the scale required for cutting-edge *** performance gains, this approach introduces autonomous data cleaning, anomaly detection and defect identification mechanism, allowing failed patterns and defective images to be identified without h

关键词： Accuracy Runtime image edge detection Clustering algorithms Feature extraction Real-time systems Computational efficiency Artificial intelligence Anomaly detection Tuning

来源：评论

学校读者我要写书评

暂无评论

Secure QIM-Based image Watermarking in JPEG Compression Domain 12th

Secure QIM-Based Image Watermarking in JPEG Compression Doma...

引用

12th International conference on Soft Computing and Pattern Recognition, SoCPaR 2020 and 16th International conference on Information Assurance and Security, IAS 2020

作者： Fedoseev, Victor Kozlov, Daniil Samara National Research University Moskovskoe Shosse 34 Samara443086 Russia Image Processing Systems Institute of RAS – Branch of the FSRC "Crystallography and Photonics" RAS Molodogvardeyskaya 151 Samara443001 Russia

ISBN: (纸本)9783030736880

Previously, we proposed two secure watermarking algorithms (IM-QIM and SIM-QIM) based on the Quantization image Modulation (QIM) technique that showed its robustness against a specific histogram attack with multiple images. Traditional QIM versions, including DM-QIM, DC-QIM, and others, are vulnerable to this attack. Our algorithms are based on a modified "correlation immune" scalar quantizer and do not introduce any correlation between the key bits and signal values. Earlier, these algorithms were implemented for grayscale images in the spatial domain. In this paper, we apply our approach in JPEG compression domain and analyze IM-QIM performance in this case. The experimental results have shown that IM-QIM maintains its security in the JPEG domain, while its robustness to typical distortions such as AGWN and JPEG compression improves, compared with spatial domain watermarking. This fact, along with the prevalence of QIM usage in the JPEG (block DCT) domain, indicates the high practical potential of the proposed algorithm. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： image watermarking

来源：评论

学校读者我要写书评

暂无评论

Biological Random Dynamic Focusing Disparity Estimation Within Time-Sequence images

Biological Random Dynamic Focusing Disparity Estimation With...

引用

image processing and Computer Applications (ICIPCA), IEEE International conference on

作者： Shijun Chen Juan Du Jie Lin Yongchao Tang Dawei Chen Qiang Chen Zhijun Zhang Zhongxing Telecom Equipment Shenzhen China School of Automation Science and Engineering South China University of Technology Guangzhou China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

In traditional computer stereo vision systems, a single focus is employed for capturing and processing stereo image pairs to estimate depth. However, the inherent variability of object distances in real world stereo images imposes limitations on this method, rendering it less reliable. To tackle this issue, a novel biological random dynamic focusing theory grounded in time-sequence images is proposed in this paper. In the proposed framework, the images of different focal points are captured according to the time sequence, the target is extracted and manipulated, ultimately yielding either a single focus or multi-focus image processing output depending on the application scenario. Moreover, a biological focusing disparity estimation algorithm is proposed and this theory is subsequently extended to the domain of disparity estimation, with its foundation rooted in the Semi Global Matching (SGM) algorithm. The disparity map obtained by this algorithm exhibits a more accurate disparity values and achieves a good balance between speed and accuracy. Experimental results on real world images demonstrate that our method enhanced robustness and flexibility compared to traditional methodologies.

关键词： Accuracy Heuristic algorithms image processing Focusing Estimation Reliability theory Aerodynamics Biology Stereo vision Biomedical imaging

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 << < 134 135 136 137 138 139 140 141 142 143 > >>

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：