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

14,138 篇 会议
291 篇 期刊文献
196 册 图书
6 篇 学位论文

馆藏范围

14,631 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
- 2,530 篇 电气工程
- 1,453 篇 信息与通信工程
- 939 篇 控制科学与工程
- 742 篇 光学工程
- 548 篇 生物医学工程（可授...
- 532 篇 电子科学与技术（可...
- 511 篇 仪器科学与技术
- 489 篇 机械工程
- 358 篇 生物工程
- 244 篇 测绘科学与技术
- 184 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
- 111 篇 安全科学与工程
- 97 篇 化学工程与技术
3,828 篇 理学
- 2,634 篇 物理学
- 1,008 篇 数学
- 411 篇 生物学
- 276 篇 系统科学
- 257 篇 统计学（可授理学、...
- 132 篇 化学
1,611 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...
782 篇 管理学
- 470 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

2,876 篇 image processing
1,507 篇 image segmentati...
1,202 篇 signal processin...
658 篇 feature extracti...
625 篇 cameras
590 篇 signal processin...
589 篇 image edge detec...
530 篇 image coding
522 篇 image reconstruc...
469 篇 real-time system...
417 篇 algorithm design...
354 篇 image analysis
352 篇 image color anal...
331 篇 image enhancemen...
325 篇 deep learning
311 篇 object detection
307 篇 pixel
299 篇 real time system...
298 篇 hardware
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
7 篇 busch christoph
7 篇 zelensky a.
7 篇 bovik alan c.
7 篇 jerry m. mendel
7 篇 kupriyanov a.v.
7 篇 wei li

语言

14,385 篇 英文
146 篇 其他
82 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 14631 条记录，以下是181-190 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：

Lossless Medical image Compression Using ROI Segmentation with Deep Learning Techniques

Lossless Medical Image Compression Using ROI Segmentation wi...

引用

International conference on Inventive Computation Technologies (ICICT)

作者： Velidi Sai Baba Molaka Ramakrishna Reddy Kombathula Lakshmi Karthik Gandham Lakshmi Tharun Katreddy Surya Mithra Dept. of Information Technology Sagi Rama Krishnam Raju Engineering College Bhimavaram Andhra Pradesh India

ISBN: (数字)9798331512248

ISBN: (纸本)9798331512255

With The increasing use of medical imaging has put a greater requirement on fast and efficient storage and transmission. Compression algorithms need to strike a balance between reducing file sizes without distortion of valuable diagnostic information. In this paper, a hybrid lossless compression method is proposed that uses deep learning-based ROI segmentation. A U-Net model is used specifically to segment the cardiac anatomy on CT scans accurately. Lossless compression is used to preserve large diagnostic areas, and lossy compression is used to compress small areas. The approach strikes an effective balance between the two to yield high compression ratio without compromising medical integrity. Experimental evidence proves its efficacy in minimizing storage needs without compromising diagnostic accuracy. This work recognizes the potential of deep learning for medical image processing and paves the way for upcoming AI-based compression methods.

关键词： Heart Deep learning Learning systems image segmentation image coding Accuracy Computed tomography Transform coding Memory Medical diagnostic imaging

来源：评论

学校读者我要写书评

暂无评论

Vehicle Registration Plate Recognition Using YoloV8 and IOT

Vehicle Registration Plate Recognition Using YoloV8 and IOT

引用

AIML-Applications for Engineering & Technology (ICAET), International conference on

作者： Juber Nadaf Amol Kadam Pramod Jadhav Prasad Kadam Vinod Patil Milind Gaikwad Department of Computer Bharati Vidyapeeth (Deemed to be University) College of Engineering Pune India Department of CSBS Bharati Vidyapeeth (Deemed to be University) College of Engineering Pune India Department of E & TC Bharati Vidyapeeth (Deemed to be University) College of Engineering Pune India Department of Information Technology Bharati Vidyapeeth (Deemed to be University) College of Engineering Pune India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

Number Plate recognition or the vehicle License Plate recognition is an interesting topic of research in smart cities which utilizes image processing techniques. Since the number of cars is rising at an exponential rate, automated systems are supposed to store vehicle data for a variety of applications. In this intended algorithm, an efficient technique has been identified for recognition of different vehicle number registration plates. Through this technique, we can easily deal with problems like low light, irregular font number plates, wrong angles. We use the method of Optical Character Recognition to identify characters that are extracted from the registration plate. Even though this project works efficiently for common use cases, it has its own drawbacks and limitations even though we are not using deep learning or any other machine learning algorithms. One of the important steps in vehicle plate recognition is the character recognition which is a technique to obtain individual text characters. YOLOv8 (You Only Look Once), and Darknet- 53 are the methods that is used to extract the features of the data. In this model, the input data is the image of the vehicle that is captured from the camera sensors or cell phones and later cropped to display only the registration plate. We undergo data-pre-processing to improve the quality or the pixels of image on the number plate. Testing is done using two different models one is the model which is obtained with more pre-processing data and the other obtained without any pre-processing data. We evaluate two datasets of number plate images: one with no interference and one where the colour intensity of the image has been decreased to test, the accuracy of the model

关键词： Deep learning YOLO Training image recognition Accuracy Feature extraction Data models Internet of Things Character recognition License plate recognition

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Approach for Detection and Reduction of different types of noises in gray scale images

A Hybrid Approach for Detection and Reduction of different t...

引用

International Symposium on Advanced Computing and Communication (ISACC)

作者： Amanpreet Kaur Sandhu University Institute of Computing Chandigarh University Gharuan Mohali Punjab India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

image denoising is a critical task in various fields such as digital photography, medical imaging, satellite or remote sensing, and, also preserving important image details while removing noise is essential. This paper introduces the Hybrid Adaptive Median-Gaussian Filter (HAMGF), a novel method designed to effectively mitigate both salt-and-pepper and Gaussian noise especially in grayscale images. The proposed HAMGF technique combines adaptive median filtering, which dynamically adjusts the window size to remove impulsive noise, with adaptive Gaussian filtering, which varies the smoothing strength based on local image variance to reduce Gaussian noise. However, the proposed hybrid technique is implemented on a variety of noisy images, demonstrating its ability to outperform traditional filtering methods that are typically specialized for single noise types. HAMGF not only excels in reducing noise but also in preserving critical image features or details, such as edges and fine textures, making it particularly suited for applications requiring high-fidelity image restoration. The results highlight the flexibility and robustness of HAMGF, showcasing its potential for broader adoption in noise reduction tasks. The proposed research work demonstrates an important advancement in the area of image processing which is offering a versatile as well as powerful tool for the enhancement of image quality across varied domains.

关键词： Smoothing methods Filtering Gaussian noise image edge detection Noise reduction Adaptive filters Filtering algorithms image restoration Remote sensing image denoising

来源：评论

学校读者我要写书评

暂无评论

The EcoSync: A Comprehensive Study on Water Quality Prediction and Waste image Recognition 3

The EcoSync: A Comprehensive Study on Water Quality Predicti...

引用

3rd International conference on Intelligent systems, Advanced Computing, and Communication, ISACC 2025

作者： Mukherjee, Ahana Chatterjee, Bipasha Das, Indrakshi Chakraborty, Koushiki Pramanik, Madhushree Payra, Anjan Kumar Institute of Engineering and Management Newtown Computer Science (Artificial Intelligence & Machine Learning) Kolkata India Institute of Engineering and Management Newtown Computer Science (Artificial Intelligence & Machine Learning) India Institute of Engineering and Management Kolkata Newtown India

ISBN: (纸本)9798331523893

This research was devised to analyze how machine learning tools could assess water quality and classify waste aiming to build a better system for sustaining our environment. We unified decision trees, random forests, and convolutional neural networks to create a multi-model system that identifies and sorts waste via image recognition. To strengthen our model's performance, we expanded our dataset to include sundry labelled images. Using a multilayer perceptron with Adam optimizer, our system achieved 89% accuracy in classifying waste types and 94% accuracy in identifying waste materials. Water potability analysis, however, relied on machine learning models that were trained on a comprehensive dataset of chemical and physical water parameters. The system was able to show an accuracy of 87% in predicting water safety with a low false positive rate of 3.2% when real time monitoring was integrated. These systems when integrated gave a solution that was better than traditional methods by 47% and the processing time was reduced by 62%. Our results showed that machine learning can effectively enhance environmental management systems. This scalable, technology-driven approach proved successful for both waste and water management, making it particularly valuable for regions struggling with these challenges, regardless of their development status. © 2025 IEEE.

关键词： Adam Optimizer Classifiers Machine Learning algorithms Sustainable development Waste analysis Waste image Recognition Waste Management Water analysis Water and Waste Management Water potability XG Boost

来源：评论

学校读者我要写书评

暂无评论

Robust Phase Retrieval from Quantized and Noisy Measurements

Robust Phase Retrieval from Quantized and Noisy Measurements

引用

Acoustics, Speech, and Signal processing Workshops (ICASSPW), IEEE International conference on

作者： Yihong Gao Luteng Zhu Zhuoyang An Mingjie Shao Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong SAR China School of Information Science and Engineering Shandong University Qingdao China Computer School Beijing Information Science and Technology University Beijing China Key Laboratory of System and Control AMSS Chinese Academy of Sciences Beijing China

ISBN: (数字)9798331519315

ISBN: (纸本)9798331519322

The phase retrieval (PR) problem involves recovering a signal from amplitude-only measurements and has been extensively studied in various physical measurement and signal processing systems. Recently, there has been increasing interest in the quantized phase retrieval (QPR) problem, where the observed amplitude is quantized to binary values. The existing studies have focused on the noiseless case. In this paper, we address a robust QPR problem that accounts for both quantization and noise. We formulate the robust QPR problem using maximum-likelihood estimation (MLE), which results in a non-convex and challenging optimization problem due to the complexity of its likelihood function. To obtain a high-quality solution, we develop an expectation-maximization (EM) algorithm combined with the Wirtinger flow, allowing us to convert the problem into a more manageable form at each iteration. Our method is implemented on both randomly generated synthetic data and image reconstruction tasks. The results demonstrate that our approach significantly enhances signal recovery performance under the combined effects of quantization and noise. Additionally, the proposed method exhibits better runtime efficiency compared to existing approaches.

关键词： Maximum likelihood estimation Phase measurement Quantization (signal) Runtime Noise Signal processing algorithms Noise measurement Speech processing Optimization Synthetic data

来源：评论

学校读者我要写书评

暂无评论

Research on Collaborative Filtering Algorithm of E-commerce Based on Flink

Research on Collaborative Filtering Algorithm of E-commerce ...

引用

International conference on Intelligent Control and Information processing (ICICIP)

作者： Haohao Zheng Xiaonan Luo Xiaoshu Zhu School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798331516147

ISBN: (纸本)9798331516154

In online shopping, a person’s interest in a product is closely related to whether they will purchase it Analyzing people’s interest in various products on time, along with product recommendations, can increase purchase rates. However, in many cases, We only know user implicit feedback, such as browsing or favoriting items, and cannot directly access user explicit feedback, such as product ratings. Moreover, users have limited exposure to products, resulting in a sparse user-item matrix. The traditional Alternating Least Squares (ALS) algorithm can partially address the is of of matrix sparsity but its accuracy in recommending products based on implicit feedback alone is insufficient. This paper proposes an improved ALS algorithm that converts implicit feedback into explicit ratings. We calculate the browsing frequency of a product based on user browsing counts. For a given product, we represent user preference by suimming the browsing frequencies of all products with browsing frequencies less than or equal to that of the product. Then, by multiplying the preference level by the product’s maximum rating, we derive a product rating, achieving a transformation from implicit feedback to explicit scores. Additionally, traditional collaborative filtering algorithms often use offline data, which may not align with user current preferences. To improve the algorithm’s accuracy, we also utilize Flink for real-time data processing, allowing us to capture the most recent feedback data. This study tests the approach using the UserBehavior dataset from the publicly available Tianchi dataset. Experimental results indicate improvements in both Root Mean Square Error (RMSE) and Mean Absolute Error (MAE).

关键词： Accuracy Collaborative filtering Prediction algorithms Real-time systems Electronic commerce Sparse matrices User preference Matrix converters Root mean square Intelligent control

来源：评论

学校读者我要写书评

暂无评论

A Survey on Intelligent Attack Mitigation and Latency Optimization in High-Speed Edge Networks using Deep Learning and Bio-Inspired algorithms

A Survey on Intelligent Attack Mitigation and Latency Optimi...

引用

Trends in Material Science and Inventive Materials (ICTMIM), International conference on

作者： Gandham Kiran Kumar M. Thirumaran Department of Computer Science and Engineering Puducherry Technological University Puducherry India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

As the Internet connected devices and cyber– physical systems (CPS) are exponentially increasing, edge computing has become a crucial enabler to support real time processing in high-speed networks (HSNs). However, integrating edge computing into broadband infrastructure is a challenging problem and that includes mitigating security risks such as DDoS and time-delay attacks and keeping ultra-low latency. Explored for this survey are some recent technologies on how to detect attacks and optimize latency on the edge, focusing on forms of deep learning and bioinspired approaches. It analyzes the lack of effectiveness in traditional mitigation strategies and represents new means, based on the use of ensemble learning, dimensionality reduction and hybrid models. Distributed edge infrastructures are specially emphasized on real time implementation, computational overhead and security. This paper attempts to contribute valuable insight for researchers developing robust, scalable, and intelligent edge-based solutions in high-speed networking environments by consolidating recent methodologies and their outcomes.

关键词： Surveys Deep learning High-speed networks image edge detection Prevention and mitigation Focusing Real-time systems Security Optimization Edge computing

来源：评论

学校读者我要写书评

暂无评论

LLM-Based Task Planning for Mobile Robots Using a Novel SLAM Method for Materials Distribution

LLM-Based Task Planning for Mobile Robots Using a Novel SLAM...

引用

International conference on Autonomous Robots and Agents, ICARA

作者： Aphilak Lonklang Pedro Alejandro Cordero Jara Haichen Xu Wentao Zhang Natabara Máté Gyöngyössy János Botzheim Department of Artificial Intelligence Faculty of Informatics ELTE Eötvös Loránd University Budapest Hungary

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

This paper presents a novel autonomous mobile robot system for material distribution, integrating dynamic map generation, natural language processing (NLP), and efficient path-planning for real-world factory applications. The system begins with a top-view image capture of the environment using a fisheye-lens camera, followed by image correction and color-based object detection to identify stations and generate an occupancy map for navigation, eliminating the need for traditional SLAM techniques. User interaction is facilitated through an NLP module connected to a large language model (LLM) trained on predefined assembly manuals, enabling the robot to interpret requests and determine the required materials for specific assembly tasks. The global path-planning is managed by the Improved RRT* with Reduced Random Map Size (IRRT*-RRMS) algorithm, ensuring optimal and efficient motion in dynamic environments. Experimental validation using a TurtleBot3 Waffle Pi equipped with an OpenManipulator-X demonstrates the system's effectiveness, particularly in handling assembly model H, which includes bolts, nuts, and screws.

关键词： Simultaneous localization and mapping Navigation Heuristic algorithms Robot vision systems Object detection Fasteners Natural language processing Mobile robots Assembly Autonomous robots

来源：评论

学校读者我要写书评

暂无评论

Face Recognition Attendance Framework using Quantum Edge processing

Face Recognition Attendance Framework using Quantum Edge Pro...

引用

Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), International conference

作者： S. Rajarajeswari Hassan Srinivas Ranjitha Computer Science and Engineering Ramaiah Institute of Technology Bangalore India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

Through the use of a Streamlit web application, the script is a highly intelligent tool that combines cutting-edge quantum processing principles with traditional computer vision approaches to handle a variety of face detection and identification tasks. While other libraries handle computer vision jobs and numerical calculations, such as NumPy and OpenCV, Streamlit is essential to developing the web application interface. While Streamlit WebRTC allows real-time video streaming, PIL is utilized for image processing. The application is set up to have a personalized look and a centered layout. Users may upload photographs, choose detection modes, and modify face detection settings on its header and sidebar. The program detects faces in uploaded photographs by encircling them with bounding boxes using the Haar Cascade Classifier. This may be used to build a face dataset or train a face recognition algorithm. Another important feature is real-time face identification, in which the software uses the Haar Cascade Classifier to identify faces in a video stream. Bounding boxes are used to emphasize faces, and photos containing faces are retained for later study or training. The program may utilize taken photographs to train a model for face recognition. These photos are processed, turned into grayscale, and then the LBPH (Local Binary Patterns Histograms) technique is used to train the model. The trained model is then kept for use in upcoming facial recognition assignments. Moreover, the program may be set up to track attendance in real time by identifying faces in a webcam stream. Time stamps are recorded, attendance is logged using recognized faces, and the information is saved to a CSV file. All things considered, the script provides a complete solution that combines traditional and quantum methods for real-time face identification, picture processing, and attendance monitoring. This makes it an adaptable tool for a range of computer vision and machine learning application

关键词： Quantum computing Codes Face recognition image edge detection Streaming media Real-time systems Libraries Classification algorithms Face detection Monitoring

来源：评论

学校读者我要写书评

暂无评论

6th International conference on Smart Computing and Informatics, SCI 2024

6th International Conference on Smart Computing and Informat...

引用

6th International conference on Smart Computing and Informatics, SCI 2024

ISBN: (纸本)9789819619801

The proceedings contain 46 papers. The special focus in this conference is on Smart Computing and Informatics. The topics include: Resilient Domain Authentication Framework for Enhancing Digital Identity Security;traffic Sign Detection with Pattern Recognition Techniques Using image processing;exploring Advanced Techniques in Natural Language processing and Machine Learning for In-depth Analysis of Insurance Claims;Network Intrusion Detection with SMOTE-ENN and Deep Learning Techniques;leveraging Transfer Learning to Enhance Location Accuracy in Mapping Services: A Case Study of Google Maps;assessment of Enhanced Email Spam Detection System Through Machine Learning algorithms;machine Learning Methods for Predicting Traffic Congestion Forecasting;hybridization of Computational Intelligence Algorithm for Scheduling of Tasks and Balancing of Load in Cloud Network;MDSV: Mobs Detection by Enhanced Fused Feature Base Deep Neural Network from Surveillance Camera;ioT-Based Solution for Enhanced Tracking of Individuals Living with Dementia;a Novel Task Scheduling Algorithm in Heterogeneous Multi-cloud Environment;Evaluating the Integration and Usage of AI in Higher Education;evaluating the Connectional Benefits of Artificial Intelligence in the Digital Classroom;Influence of AI as an Aspect of Modern Education Era in Present World;Hilbert–Huang Transform Framework-Based Email and SMS Spam Detection;the Advancement and Utilization of Artificial Intelligence and Machine Learning in the Financial Industry and Its Impact on Macro and Microeconomics;analysis on the Cutting-Edge Approach to Assess Artificial Intelligence’s Educational Consequences in Contemporary Studies;data Analytics in Sales and Marketing: A Comprehensive Methodology for Business Analysts;Wireless Energy Transfer for UAV (Drone) Using Machine Learning.

关键词：

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 << < 15 16 17 18 19 20 21 22 23 24 > >>

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：