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

13,205 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

13,603 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

7,033 篇 工学
- 4,653 篇 计算机科学与技术...
- 2,295 篇 软件工程
- 2,120 篇 电气工程
- 1,334 篇 信息与通信工程
- 867 篇 控制科学与工程
- 689 篇 光学工程
- 503 篇 生物医学工程（可授...
- 470 篇 电子科学与技术（可...
- 469 篇 机械工程
- 462 篇 仪器科学与技术
- 336 篇 生物工程
- 242 篇 测绘科学与技术
- 167 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
- 92 篇 化学工程与技术
3,497 篇 理学
- 2,406 篇 物理学
- 932 篇 数学
- 394 篇 生物学
- 249 篇 系统科学
- 240 篇 统计学（可授理学、...
- 122 篇 化学
1,508 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...
- 89 篇 工商管理
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

2,760 篇 image processing
1,431 篇 image segmentati...
1,168 篇 signal processin...
616 篇 cameras
616 篇 feature extracti...
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

13,372 篇 英文
140 篇 其他
78 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 13603 条记录，以下是161-170 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：

Adaptive KOA: Leaf disease classification using hyperspectral images for Internet of Things (IoT)-based sustainable agriculture

Adaptive KOA: Leaf disease classification using hyperspectra...

引用

Emerging systems and Intelligent Computing (ESIC), International conference on

作者： Pradeep Kumar Mallick Annapareddy V N Reddy Manas Ranjan Mohanty Biswajit Sahoo Alok Kumar Jagadev School of Computer Engineering Kalinga Institute of Industrial Technology(KIIT) DU Bhubaneswar Odisha Department of Information Technology Lakireddy Bali Reddy College of Engg. Mylavaram Andhra Pradesh

ISBN: (数字)9798331522100

ISBN: (纸本)9798331522117

In recent times, the crops as well as the agriculture management is one of the important field to watch out, therefore the image processing business provide more benefit to the crops along with support precaution needs. In this research, an adaptive Kookaburra Optimization Algorithm (Adaptive KOA) is implemented for leaf disease classification using hyperspectral images for Sustainable Agriculture in *** first, the IoT modelis replicated and the routing is conductedto transmit the data from source to the Base Station (BS). Moreover, in BS the following steps are conducted. The input hyperspectral image (HSI)is subjected to a band selection module. The band selection is done using the implemented Adaptive Kookaburra Optimization Algorithm (Adaptive KOA). The developed Adaptive KOA is devised by incorporating Adaptive concept with Kookaburra Optimization Algorithm (KOA). The Selected bands are fed into the leaf segmentation module, where the Deep Embedded Clustering (DEC) technique is utilized for segmentation. Fusion of segmented image from different bands is carried out by the majority voting method. Finally, Leaf disease classification is carried out based on the 3D-Convolutional Neural Network (3DCNN) into normal and abnormal cases. The developed Adaptive KOA-3DCNN method has the maximum value for accuracy as 0.917%, highest value for True negative rate(TNR)as 0.927%, highest value for True positive rate (TPR) as 0.907%.

关键词： image segmentation Plant diseases Adaptation models Clustering algorithms Routing Agriculture Classification algorithms Internet of Things Optimization Hyperspectral imaging

来源：评论

学校读者我要写书评

暂无评论

Quantum-Enhanced Machine Learning for Precision Breast Cancer Diagnosis

Quantum-Enhanced Machine Learning for Precision Breast Cance...

引用

International Communication systems and Networks and Workshops, COMSNETS

作者： Agniva Banerjee Dept. Electrical Engineering and Computer Science Indian Institute of Science Education and Research Bhopal Bhopal India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

Cancer is the leading cause of premature mortality. Globally, the prevalence of cancer is on the rise, and early-stage diagnosis is crucial for cancer recovery and survival. However, the presence of circulating tumor cells (CTCs) and heterogeneity within the tumor makes it hard to track how cancer changes over time and how resistance to treatment develops. Unfortunately, the cancer diagnosis precision remains inadequate, endangering precious human lives and necessitating costly procedures for accurate treatment. Machine learning (ML) has proven capable of discovering meaningful information and making predictions, particularly with large datasets. Moreover, quantum computers (QCs) inherently possess superposition and parallel computation, features not found in classical computing. Researchers have demonstrated that quantum neural networks (QNNs) achieve a significantly better effective dimension than classical NNs. In this context, this study investigates the application of classical and quantum machine learning (QML) algorithms to classify breast cancer images. Region-based segmentation is used to identify regions of interest and image processing algorithms are performed on segmented breast cancer images to extract meaningful features (e.g., perimeter, area, compactness). An user interface (UI) based software is created to swiftly distinguish benign and malignant instances during image analysis. Although QNNs perform poorly than the classical NNs, there is still a long way to go in developing feature maps and techniques for better performance. In contrast, the classical NNs have gone a long way with well-established algorithms and packages available to us. This research shows that with further development, QML has the potential to enhance cancer diagnosis accuracy and speed, ultimately improving early detection and treatment outcomes.

关键词： image segmentation Accuracy Machine learning algorithms Software algorithms Artificial neural networks Machine learning Feature extraction Breast cancer Software Tumors

来源：评论

学校读者我要写书评

暂无评论

High Resolution Millimeter Wave Imaging Based on FMCW Radar systems at W-Band

High Resolution Millimeter Wave Imaging Based on FMCW Radar ...

引用

IEEE Annual Computing and Communication Workshop and conference (CCWC)

作者： Shahrokh Hamidi MR Nezhad-Ahmadi Department of Electrical and Computer Engineering University of Waterloo Canada MMSENSE Technologies Inc. Waterloo Canada

ISBN: (数字)9798331507695

ISBN: (纸本)9798331507701

In this paper, we present a unique 2D high resolution, compact, low-cost, lightweight, and highly accurate millimeter-wave imagery system capable of operating in all weather conditions. We explain different aspects of the imagery system in detail and describe the process of millimeter-wave image formation thoroughly. To create the array, we utilize the Synthetic Aperture Radar (SAR) concept. The imagery system presented in this paper, can strongly compete with the Lidar systems as the resolution limit is at the same level. Furthermore, in contrast to the Lidar systems, our imagery system can operate in heavy rain as well as dense fog and produce high quality images. Finally, we utilize our wide-band custom-made Frequency Modulated Continuous Wave (FMCW) radar, which operates at W-band with 33 GHz bandwidth, for data collection and present the results.

关键词： image resolution Laser radar Frequency modulation Imaging Signal processing algorithms Millimeter wave radar Radar imaging Millimeter wave communication Synthetic aperture radar Signal resolution

来源：评论

学校读者我要写书评

暂无评论

Smart Medical Box using Arduino

Smart Medical Box using Arduino

引用

International conference on ent Computing and Control systems (ICICCS)

作者： Sweadha. M M. Selvi Dept. of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

The Smart Medical Box is a sophisticated IoT-driven solution designed to enhance medication adherence by utilizing computer vision and machine learning. The system automates the identification and extraction of essential information from medication labels, ensuring precision in dosage reminders and reducing human error. It incorporates a high-resolution camera, an OCR engine, and an Arduino-based microcontroller to enable seamless image processing and real-time analysis. With an intuitive interface and GPS-enabled location services, users can efficiently manage their medication schedules while accessing nearby pharmacies when needed. This research focuses on designing and implementing a scalable and cost-effective system that improves medication compliance and minimizes health risks associated with missed or incorrect dosages. By integrating advanced image processing techniques and AI-driven recognition algorithms, the Smart Medical Box ensures high accuracy in identifying medications. Additionally, features such as automated alerts, real-time monitoring, and pharmacy locator tools enhance the system's usability and accessibility. This innovation is particularly beneficial for elderly individuals and patients with chronic conditions, offering a simplified and automated approach to medication tracking. Performance evaluations of the system indicate a significant improvement in medication adherence, a high recognition accuracy rate, and positive user feedback. Future enhancements, including AI-based OCR, voice assistance, and mobile application connectivity, are expected to further improve functionality and ease of use. This paper presents the conceptualization, development, and testing of the Smart Medical Box, highlighting its potential to revolutionize personal healthcare management by providing an intelligent, efficient, and user-friendly solution.

关键词： Accuracy image recognition Microcontrollers Optical character recognition Medical services Real-time systems Usability Older adults Biomedical imaging Global Positioning System

来源：评论

学校读者我要写书评

暂无评论

AI-Driven Thermal Imaging: A Comprehensive Web-Based Tool for Non-Invasive Medical Diagnostics

AI-Driven Thermal Imaging: A Comprehensive Web-Based Tool fo...

引用

International Symposium on Advanced Computing and Communication (ISACC)

作者： Aniruddha Ghosh Sayan Snigdha Pal Sumedha Das Spandan Bhattacharya Arijit Bhattacharya Nilanjana De Sudipta Sahana Computer Science and Engineering(Artificial Intelligence and Machine Learning) Institute of Engineering & Management Kolkata University of Engineering and Management Kolkata West Bengal India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

Thermography is an innovative technique that creates a heatmap of different portions of the human body by using infrared (IR) radiation where color scales vary for various temperature regions. This work's scope aims to extend thermal imaging applications with machine learning algorithms in conjunction with Azure API services to analyze thermal images and return a preliminary diagnosis. The project consists of generating heatmaps for better visualization results, analyzing them through image processing techniques, and feeding the information to Azure’s Custom Vision API to detect anomalies and classify health conditions and finally producing a proper report. This research allows individuals and healthcare professionals to have a quick, non-invasive diagnostic tool that empowers health monitoring and preventive care. It combines the capabilities of contemporary technologies with uses directed toward health practice, leading to inimical patient outcomes and true practices.

关键词： Visualization Machine learning algorithms image color analysis Infrared heating Infrared imaging Thermal analysis Medical diagnosis Predictive analytics Intelligent systems Monitoring

来源：评论

学校读者我要写书评

暂无评论

AI-Driven Personalized Skincare Recommendations

AI-Driven Personalized Skincare Recommendations

引用

Electronics and Renewable systems (ICEARS), International conference on

作者： Iyyanar Perumal Kalaivani P Naveenkumar A Saran V Sriram K Suruthi N Department of Information Technology Sona College of Technology Salem India Department of CSE Kongu Engineering College Perundurai India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

This study investigates the utilization of artificial intelligence (AI) to transform skincare product recommendations and the formulation of individualized routines through the analysis of user inputs and characteristics. The system utilizes data including skin type, acne count, oiliness level, and UV exposure, using KNearest Neighbors (KNN) for personalized product suggestions. Natural Language processing (NLP) approaches are utilized to develop tailored 7-day skincare regimen recommendations by examining product and user problems, converting unstructured data into actionable insights. Moreover, deep learning algorithms are employed for real-time image-based assessments of skin conditions, facilitating precise acne diagnosis and oiliness evaluation. The system integrates visual data with textual analysis, continually adapting through user feedback to improve accuracy and relevance. This article highlights the capacity of AI-driven methods to automate routine generation and provide tailored product recommendations, fostering innovation in the cosmetics sector through a thorough, data-oriented strategy.

关键词： Deep learning Visualization Accuracy Transforms Nearest neighbor methods Skin Natural language processing Real-time systems Artificial intelligence Wearable devices

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

Perceptual Learning Technology Based on Computer Vision and ...

引用

International conference on Communication systems and Network Technologies (CSNT)

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

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

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.

关键词： Adaptation models Computer vision image segmentation Machine learning algorithms Computational modeling Transfer learning Feature extraction Data models Robustness Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Algorithm Optimization and Immersion Enhancement in Virtual Reality Film

Algorithm Optimization and Immersion Enhancement in Virtual ...

引用

Intelligent systems and Computational Networks (ICISCN), International conference on

作者： Chulei Zhang Hongxing Qian Changchun Humanities and Sciences College Changchun China

ISBN: (数字)9798331529246

ISBN: (纸本)9798331529253

With the widespread application of virtual reality (VR) technology in the fields of entertainment and education, the immersion experienced by users in VR movies and TV shows has become a key factor affecting their acceptance and satisfaction. However, there are still significant shortcomings in terms of image rendering speed in current VR movies and TV shows. This article introduces an algorithm optimization framework based on Convolutional Neural Networks (CNN). Firstly, this article uses CNN algorithm to optimize the image rendering process. Next, use Dynamic Resolution Adjustment (DRS) technology to improve rendering speed and maintain frame rate stability; Then, combining high dynamic range (HDR) rendering and temporal anti aliasing (TAA) technology to enhance the color expression and visual smoothness of the image; Finally, optimize the sensor data processing flow and data transmission protocol. Through experimental evaluation in VR scenes of different complexities, the results showed that the optimized system improved rendering speed by an average of about 58.3%, reduced interaction latency by about 33.3%, and improved image quality indicators PSNR and SSIM by about 26.2% and 9%, respectively. In the above data conclusions, CNN based optimization methods have shown significant advantages in improving VR film and television performance and user experience, providing strong support for the future development of VR film and television technology.

关键词： image quality Visualization TV Heuristic algorithms Virtual reality Motion pictures Rendering (computer graphics) User experience Convolutional neural networks Optimization

来源：评论

学校读者我要写书评

暂无评论

Rectifying Irregular Boundaries Stereoscopic images Using Deep Learning and Evolutionary algorithms

Rectifying Irregular Boundaries Stereoscopic Images Using De...

引用

IEEE SSD International Multi-conference on systems, Signals and Devices

作者： Muntasser A. Wahsh Zainab M. Hussain Department of Computer Science Informatics Institute for Postgraduate Studies (IIPS) Baghdad Iraq Department of Political Science Al-Iraqia University Baghdad Iraq

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Application of stereoscopic technology has increased significantly in several industries, including the media and entertainment sectors, medical imaging, and virtual reality. However, the overall viewing experience and the feeling of depth can be negatively impacted by uneven boundaries in stereoscopic images. To have a realistic and immersive stereoscopic experience, fixing these wavy edges is an essential process. This work present a distinctive approach for optimizing the rectangular bounds of stereoscopic images using a hybrid of deep learning and evolutionary algorithms. The suggested method uses a genetic algorithm to optimize the parameters of a convolutional neural network (CNN) to extract useful features for residual regression. Due to the lack of compatible datasets, a set of stereoscopic images was constructed from monocular images by calculating the depth of the objects using MiDaS pretrained depth estimation algorithm. Several metrics, including as mean squared error, peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and Fréchet inception distance (FID), were used to evaluate the performance of the suggested technique. The experimental findings show that the proposed method effectively optimizes rectangular borders with excellent accuracy, even for images with complicated shape and orientations. Various parameter settings were also tested, revealing that increasing the number of generations and population size contributes to improved performance. The combination of the deep learning algorithm, specifically the CNN, and the optimization algorithm, specifically the genetic algorithm (GA), leads to an increase in the accuracy of rectified images. Notably, the average PSNR reached 24.42, SSIM measured at 0.7793, and FID scored 18.26. The proposed method holds promise for a wide range of applications, including image cropping, object detection, and image segmentation, among others. By effectively optimizing rectangular boundaries in ster

关键词： Deep learning Visualization Accuracy PSNR Stereo image processing Depth measurement Evolutionary computation Feature extraction Convolutional neural networks Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Online Optimization of Offloading Video Analytics Tasks to Multiple Edges for Accuracy Maximization

Online Optimization of Offloading Video Analytics Tasks to M...

引用

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

作者： Yu Liang Sheng Zhang Jie Wu School of Computer and Electronic Information and the School of Artificial Intelligence Nanjing Normal University State Key Laboratory for Novel Software Technology Nanjing University Center for Networked Computing Temple University US

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Real-time video analytics (VA) presents challenges due to its computational intensity and latency sensitivity, especially when processed on mobile devices with limited local resources. We propose to offload VA tasks to edge servers with diverse computational capabilities. We present a "detect + track" approach with on-device object tracking and edge-assisted object detection. We formulate a long-term nonlinear integer programming to maximize the overall accuracy within detection frequency and latency constraints. We then design a queue-based online optimization algorithm to solve it: relax the original problem from the integer domain to the real domain, then employ a queue-based adaptation and randomized rounding strategy. Via rigorous proof, both dynamic regret regarding detection accuracy and the real-time requirement are ensured. Evaluation results also demonstrate the effectiveness of our approach.

关键词： Accuracy image edge detection Visual analytics Signal processing algorithms Streaming media Signal processing Real-time systems Servers Speech processing Optimization

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 << < 13 14 15 16 17 18 19 20 21 22 > >>

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：