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

13,207 篇 会议
218 篇 期刊文献
176 册 图书
3 篇 学位论文
1 篇 资讯

馆藏范围

13,605 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

7,036 篇 工学
- 4,656 篇 计算机科学与技术...
- 2,295 篇 软件工程
- 2,121 篇 电气工程
- 1,339 篇 信息与通信工程
- 872 篇 控制科学与工程
- 686 篇 光学工程
- 503 篇 生物医学工程（可授...
- 472 篇 机械工程
- 471 篇 电子科学与技术（可...
- 461 篇 仪器科学与技术
- 336 篇 生物工程
- 241 篇 测绘科学与技术
- 169 篇 材料科学与工程（可...
- 160 篇 航空宇航科学与技...
- 145 篇 交通运输工程
- 107 篇 安全科学与工程
- 93 篇 化学工程与技术
- 91 篇 网络空间安全
3,498 篇 理学
- 2,405 篇 物理学
- 936 篇 数学
- 394 篇 生物学
- 249 篇 系统科学
- 241 篇 统计学（可授理学、...
- 122 篇 化学
1,509 篇 医学
- 1,336 篇 临床医学
- 210 篇 特种医学
- 171 篇 基础医学(可授医学...
- 111 篇 药学(可授医学、理...
725 篇 管理学
- 438 篇 管理科学与工程(可...
- 311 篇 图书情报与档案管...
62 篇 法学
61 篇 农学
30 篇 教育学
29 篇 经济学
29 篇 文学
20 篇 军事学
18 篇 艺术学
1 篇 哲学

主题

2,762 篇 image processing
1,431 篇 image segmentati...
1,168 篇 signal processin...
616 篇 feature extracti...
615 篇 cameras
584 篇 image edge detec...
567 篇 signal processin...
489 篇 image coding
489 篇 image reconstruc...
466 篇 real-time system...
399 篇 algorithm design...
352 篇 image color anal...
312 篇 image enhancemen...
311 篇 pixel
309 篇 deep learning
307 篇 real time system...
302 篇 image analysis
301 篇 computer archite...
297 篇 hardware
296 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 carli m.
8 篇 a. ortega
8 篇 egiazarian karen
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

语言

13,369 篇 英文
145 篇 其他
79 篇 中文
20 篇 土耳其文
3 篇 西班牙文
3 篇 葡萄牙文
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 13605 条记录，以下是61-70 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：

12th International conference on Recent Trends in Computing, ICRTC 2024

12th International Conference on Recent Trends in Computing,...

引用

12th International conference on Recent Trends in Computing, ICRTC 2024

ISBN: (纸本)9789819789450

The proceedings contain 34 papers. The special focus in this conference is on Recent Trends in Computing. The topics include: Deep Learning-Based Prediction of Human Ageing Related Proteins;the Insight of Clustering algorithms for Emerging Networking Paradigms;Revolutionizing Cardiovascular Health: Exploring the Potential of AI-Driven Approaches in Diagnosing Arrhythmia Disorders;humor Detection in Telugu Social Media Text Using Cost-Sensitive Learning and Indian Language Embeddings;empirical Comparison of Sleep Disorder Prediction Using Machine Learning Techniques;securing Smart Grids: Decentralized Anomaly Detection Using Federated Learning and Recurrent Neural Networks;machine Learning-Powered Intrusion Detection for Network Security;secure Chat System: Harnessing the Power of Hybrid Encryption for Enhanced Security and Confidentiality;deep Neural Networks for Early Diabetes Mellitus Prediction;advancements in image Deblurring and Performance Metrics Using Deep Learning Technique;emotion-Levitating Music Recommendation System Through Real-Time Facial Recognition;smartVoice TrashMate: The Intelligent Voice-Controlled Trash Bin;an Innovative image Enhancement Algorithm for Color Filter Array images: A Novel Approach;Enhancing Secure and Efficient Communication in Free-Space Optical Networks Using Spectral Amplitude Coding - OCDMA Technology;enhancing Citrus Fruit Classification and Quality Assessment Through Advanced Machine Learning Techniques;connecting Health for a Better Tomorrow Through Internet of Medical Things;image processing in Retail Marketing: Innovations for Customer Engagement, Sales, and Operational Efficiency;Leaf Checker: AI-Based Plant Diagnostic Tool Using Alexnet and Mobilenet;ioT-Supported Indoor Navigation System Using Machine Learning Technique;a Customizable Virtual Assistant Enhanced with Vision and Speech Capabilities;An Unequal Cluster-Based Routing Mechanism Using Lyrebird Optimization Algorithm to Achieve Network Longevity in WSNs.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Perceptual Learning Technology Based on Computer Vision and Machine Learning algorithms 14

Perceptual Learning Technology Based on Computer Vision and ...

引用

14th IEEE International conference on Communication systems and Network Technologies, CSNT 2025

作者： Wang, Tianjian School of Computer Science and Technology Wuhan Qingchuan University Hubei Wuhan430204 China

ISBN: (纸本)9798331531935

To address the issue of low accuracy and poor robustness of perceptual learning in complex scenarios, a new method integrating computer vision and machine learning is adopted, that is, by applying deep neural networks, transfer learning and self-supervised learning, combined with multimodal data fusion strategy, to improve target recognition efficiency and learning ability. First, based on the preprocessing algorithm of improved Gaussian filtering and image segmentation, the quality of image features is improved. Data enhancement methods such as random rotation, flipping, and blurring are used to expand data distribution and improve model adaptability. Secondly, a convolutional neural network (CNN) is utilized in combination with an attention mechanism to extract multi-scale target features, and transfer learning is applied to transfer common features from pre-trained models to reduce dependence on large-scale labeled data. Finally, a contrastive learning framework is constructed to mine the correlation of unlabeled data. Transformer is used to realize the fusion of multimodal data of images and texts, and the model performance is optimized through multi-task learning. The mAP (Mean Average Precision) of the traditional method in dynamic occlusion scenarios is 60.5%, which is relatively weak. This may be because the traditional method cannot fully extract the effective features of the target under the occlusion of complex moving targets. The mAP of the method in this paper is 72.8%, which is higher than that of the traditional method. The perceptual learning method adopted in this paper effectively improves the accuracy and robustness in complex scenarios, and provides reliable technical support for intelligent applications. In the future, it can be combined with edge computing to further optimize the real-time processing capability and promote its application in the fields of unmanned driving and intelligent security. © 2025 IEEE.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Quantum Variational Singular Value Decomposition: A new hybrid approach towards quantum image compression

Quantum Variational Singular Value Decomposition: A new hybr...

引用

International Communication systems and Networks and Workshops, COMSNETS

作者： Britant Abhishek Tiwari CDAC Noida Uttar Pradesh India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

This research paper explores the application of singular value decomposition (SVD) in quantum image processing (QIP), specifically focusing on the computation of eigenvalues using variational quantum algorithms. SVD is a powerful mathematical tool in image processing, used for tasks such as image compression, noise reduction, and feature extraction. In this study, we propose quantum variational singular value decomposition (QVSVD) based on the variational quantum deflation (VQD) algorithm to determine the eigenvalues that contributes in calculating the singular values of the image matrix and eventually doing the SVD. This facilitates the extraction of eigenvalues with exponential speedup on real hardware compared to classical methods. We detail the implementation of this quantum algorithm within the framework of QIP, highlighting its advantages in terms of computational efficiency and accuracy on a Fault-Tolerant Quantum Computing (FTQC). Furthermore, we present a comparative analysis of the quantum and the classical method of SVD, demonstrating the accuracy of the image data. The simulation results validate the theoretical advantages of using quantum algorithms for SVD in image processing. This work not only underscores the potential of quantum computing in enhancing image processing techniques but also sets the stage for future research in the field, exploring more complex image processing tasks and other quantum algorithms. Our findings suggest that quantum image processing can offer unprecedented capabilities, paving the way for advancements in various applications such as medical imaging, remote sensing, and multimedia processing.

关键词： Training Quantum computing Quantum algorithm image coding Accuracy Feature extraction Eigenvalues and eigenfunctions Matrix decomposition Time complexity Singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

Designing Resilient Autonomous systems with the Reflex Pattern

Designing Resilient Autonomous Systems with the Reflex Patte...

引用

Design, Automation and Test in Europe conference and Exhibition

作者： Julian Demicoli Sebastian Steinhorst Department of Computer Engineering Technical University of Munich Germany

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

Autonomous systems face significant challenges due to fluctuating resources and unstable environments, where traditional redundancy strategies for resilience can be inefficient. We present the Reflex pattern, inspired by biological reflexes, promoting system resilience by dynamically adapting to changing resource conditions. By switching between complex and resource-efficient algorithms based on availability, the pattern optimizes efficient resource utilization without extensive redundancy, ensuring essential functionalities remain operational under constraints. To facilitate adoption, we introduce ReflexLang, a domain-specific language (DSL) enabling automated code generation for reflex-pattern-based systems. We validate the pattern's effectiveness in a drone image processing scenario, demonstrating its potential to enhance operational integrity and resilience.

关键词： Autonomous systems Software architecture image processing Heuristic algorithms Redundancy Europe Switches Resource management Faces Resilience

来源：评论

学校读者我要写书评

暂无评论

Breast Cancer Prediction Using Machine Learning 5

Breast Cancer Prediction Using Machine Learning

引用

5th International conference on Emerging systems and Intelligent Computing, ESIC 2025

作者： Dhondiyal, Shiv Ashish Luthra, Pooja Sharma, Bhupender Rajni, Rajni Uniyal, Ishita Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India Chandigarh University Department of Computer Science & Engineering Punjab Mohali India Coer University Department of Computer Science and Application Uttarakhand Roorkee India Guru Jambheshwar University of Science and Technology Department Of Computer Science & Engineering Haryana Hisar India Graphic Era Hill University Department of Electrical Engineering India

ISBN: (纸本)9798331522100

The number of newly diagnosed cases of breast cancer exceeds 2.3 million annually worldwide. There is a severe lack of valid prognostic and predictive indicators for the clinical treatment of breast cancer patients at the present time. In order to decrease the mortality rate and increase the survival time of breast cancer patients, early detection of this deadly disease is crucial. Improving breast cancer prognosis relies on the analysis and processing of mammography data, the gold standard for screening and early detection. In order to detect breast cancer in mammograms, the Fuzzy C-means algorithm is employed for image segmentation. Next, we train it to identify the characteristics of the segmented regions, and then we use an effective classifier to categorise the trained pictures into their respective mammography classes. This research used the Breast Cancer Wisconsin Diagnostic dataset and two ML algorithms: K-Nearest Neighbours (KNN) and Random Forest. After getting the results, we compared and evaluated the performance of these two classifiers. Potentially useful tools for both early diagnosis and treatment planning include breast cancer prediction models that account for a wide range of risk factors. Effective disease management involves the collection, storage, and administration of many data sets, as well as intelligent systems based on several aspects for the prediction of breast cancer. © 2025 IEEE.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

algorithms for image processing of Micro-Objects of Medical Diagnostics systems

Algorithms for Image Processing of Micro-Objects of Medical ...

引用

International Russian Smart Industry conference (SmartIndustryCon)

作者： Isroil I. Jumanov Rustam A. Safarov Department of “Artifical intellegence and information systems” Samarkand State University named after Sharof Rashidov Samarkand Uzbekistan Department of Control Theory and Information Security Samarkand State University named after Sharof Rashidov Samarkand Uzbekistan

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

Constructive approaches, principles, models for optimizing the identification of micro-objects based on the use of statistical, dynamic models with mechanisms for filtering noise, foreign particles on images of medical objects and pollen grains have been developed. Methods for optimizing the identification of micro-objects with the selection of characteristic objects in the image, the combination of image models with the mechanisms of segmentation, filtering, transformation, and alignment of the laser image processing zone with the CAD model are proposed. algorithms for selecting the contours of objects on an image using a border detector in the transverse direction to each vector of the CAD model have been developed. Modeling of images of microsamples for medical diagnostics of chest diseases was carried out. The width, straightness of the boundaries of structural objects, local defects, parameters of regulation and synchronization of the components of the vision system are determined. algorithms for image processing under conditions of a priori insufficiency, uncertainty of parameters, and low accuracy of data processing are studied. A mechanism for suppressing impulse noise and noise is implemented based on various filtering methods, preserving the boundaries of objects and small-sized parts. Mathematical expressions for estimating identification errors due to non-stationarity, inadequacy of approximation, interpolation, extrapolation of the image contourare obtained, which are synthesized with cubic, biquadratic, interpolation spline functions and wavelet transforms. A software package for recognition and classification of micro-objects has been developed.

关键词： Solid modeling Interpolation image segmentation Filtering Measurement by laser beam Laser modes Vectors Object recognition Synchronization Medical diagnosis

来源：评论

学校读者我要写书评

暂无评论

Integrating the dynamic optimization strategies of Adam and AdaGrad

Integrating the dynamic optimization strategies of Adam and ...

引用

International conference on Intelligent Control and Information processing (ICICIP)

作者： Zhixuan Huang Xiaonan Luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798331516147

ISBN: (纸本)9798331516154

Artificial intelligence (AI) has been a key research area since the 1950s, initially focused on using logic and reasoning to create systems that understand language, control robots, and offer expert advice. With the rise of big data and deep learning, AI has advanced in applications like recommendation systems, image recognition, and machine translation, primarily through optimizing loss functions in deep neural networks to improve accuracy and reduce training *** descent is the core optimization method but faces challenges like slow convergence and local minima. To overcome these, algorithms like Momentum, AdaGrad, RMSProp, Adadelta, Adam, and Nadam have been developed, introducing momentum and adaptive learning rates to accelerate convergence. This paper presents a new optimization algorithm that combines the strengths of Adam and AdaGrad, offering better adaptability to different learning rates.

关键词： Training Heuristic algorithms Optimization methods Machine translation Logic Artificial intelligence Robots Recommender systems Convergence Intelligent control

来源：评论

学校读者我要写书评

暂无评论

Precision Fruit Harvesting: Stem Detection and Cutting Techniques using image processing for Robotic systems

Precision Fruit Harvesting: Stem Detection and Cutting Techn...

引用

Mobile Computing and Sustainable Informatics (ICMCSI), International conference on

作者： Madhura Rajesh Shankarpure Dipti D. Patil STE's Smt Kashibai Navale College of Engineering Savitribai Phule Pune University Pune Maharashtra India MKSSS's Cummins College of Engineering for Women Savitribai Phule Pune University Pune Maharashtra India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

To enhance robotic fruit harvesting systems, the proposed methodology uses image processing techniques to recognize orange stems. The method highlights only the stem of an orange fruit in an image by utilizing gray-scale conversion, contour-based filtering, Gaussian blur, and Canny edge recognition. The technique can be incorporated into agricultural robots to improve fruit harvesting accuracy. After detecting the fruit stem, it is crucial to ensure precise cutting of the fruit to prevent damage to both the fruit and the tree. The paper also assesses the performance of the method in terms of robustness in complicated situations and detection accuracy, demonstrating its potential for real-world agricultural applications.

关键词： Accuracy Machine learning algorithms Filtering image edge detection Heuristic algorithms Machine learning Gray-scale Robustness Informatics Mobile computing

来源：评论

学校读者我要写书评

暂无评论

Comparative Study of Machine Learning and Deep Learning Models for Food Waste Detection Using image processing

Comparative Study of Machine Learning and Deep Learning Mode...

引用

IEEE Students' conference on Electrical, Electronics and Computer Science (SCEECS)

作者： R. Rajagopal Chaithanya. k Ankita Sonth Prasanna Basanagouda Kallappagoudar Mohammadzaid Mohammadishaq Nadaf Ananda Theertha H Dept of Computer Science Alliance College of Engineering and Design Alliance University Bangalore India Bangalore India Dept of Computer Science Alliance College of Engineering and Design Bangalore India Dept of Computer Science and Engineering Alliance College of Engineering and Design Bangalore India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

For the purpose of reducing financial losses and environmental impacts, food waste detection is essential. Inorder to detect food waste using image processing, this study investigates the efficiency of several machine learning algorithms, including Convolutional Neural Network (CNN), K-Nearest Neighbors (KNN), Random Forest, and Inception Model (iv3). A set of images of food are then processed. Before each algorithm is used for classification, pre-processing methods like segmentation and feature extraction are used.

关键词： Food waste Measurement Analytical models Machine learning algorithms Accuracy Computational modeling Nearest neighbor methods Data models Convolutional neural networks Random forests

来源：评论

学校读者我要写书评

暂无评论

Generalizable Real-time Accelerated Dynamic MRI

Generalizable Real-time Accelerated Dynamic MRI

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Silpa Babu Wahidul Alam Rushdi Zahid Rusho Sajan Goud Lingala Namrata Vaswani ECE Dept Iowa State University USA BME Dept University of Iowa USA

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

We introduce a real-time undersampled dynamic MRI algorithm, termed FewShot-AltGDmin-MRI, that is generalizable: works for many different applications and sampling trajectories without any application-specific parameter tuning. FS-AGM-MRI operates in real-time after processing the first short mini-batch, i.e., it can provide a reconstruction of each new image frame as soon as the MRI scan data for that frame arrives. It also provides a second set of improved quality reconstructions after a short delay. We compare our algorithm against many state of the art batch MRI algorithms, including Deep Learning (DL) based ones, on 17 different retrospectively undersampled datasets and two prospective datasets. FS-AGM-MRI is the only approach that provides accurate recovery for all datasets while also being one of the fastest.

关键词： Magnetic resonance imaging Heuristic algorithms Signal processing algorithms Signal processing Real-time systems Trajectory Delays Speech processing image reconstruction Tuning

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 << < 3 4 5 6 7 8 9 10 11 12 > >>

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：