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

15,898 篇 会议
349 篇 期刊文献
193 册 图书

馆藏范围

16,440 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,330 篇 工学
- 5,424 篇 计算机科学与技术...
- 2,992 篇 软件工程
- 2,168 篇 电气工程
- 1,868 篇 信息与通信工程
- 1,124 篇 控制科学与工程
- 890 篇 光学工程
- 646 篇 机械工程
- 644 篇 电子科学与技术（可...
- 536 篇 仪器科学与技术
- 536 篇 生物医学工程（可授...
- 471 篇 生物工程
- 225 篇 测绘科学与技术
- 219 篇 交通运输工程
- 202 篇 材料科学与工程（可...
- 199 篇 航空宇航科学与技...
- 163 篇 化学工程与技术
- 159 篇 网络空间安全
- 141 篇 安全科学与工程
4,012 篇 理学
- 2,402 篇 物理学
- 1,360 篇 数学
- 520 篇 生物学
- 364 篇 统计学（可授理学、...
- 340 篇 系统科学
- 207 篇 化学
1,521 篇 医学
- 1,351 篇 临床医学
- 201 篇 特种医学
- 195 篇 基础医学(可授医学...
1,052 篇 管理学
- 611 篇 管理科学与工程(可...
- 481 篇 图书情报与档案管...
- 138 篇 工商管理
82 篇 法学
65 篇 农学
45 篇 经济学
44 篇 教育学
37 篇 军事学
31 篇 文学
25 篇 艺术学
1 篇 哲学

主题

2,785 篇 image processing
1,555 篇 image segmentati...
1,513 篇 signal processin...
872 篇 feature extracti...
656 篇 image edge detec...
637 篇 cameras
633 篇 signal processin...
619 篇 real-time system...
577 篇 image reconstruc...
519 篇 image coding
498 篇 algorithm design...
404 篇 deep learning
399 篇 clustering algor...
398 篇 image color anal...
385 篇 object detection
371 篇 image enhancemen...
362 篇 accuracy
335 篇 hardware
323 篇 image analysis
313 篇 computer vision

机构

40 篇 xi'an jiaotong u...
32 篇 northwestern pol...
31 篇 xi an jiao tong ...
30 篇 school of electr...
28 篇 school of electr...
26 篇 university of ch...
23 篇 xi an jiao tong ...
22 篇 xi an jiao tong ...
22 篇 national laborat...
21 篇 signal and image...
19 篇 samara national ...
18 篇 xidian universit...
16 篇 school of inform...
16 篇 institute of art...
15 篇 tsinghua univers...
15 篇 department of el...
15 篇 school of automa...
15 篇 national key lab...
15 篇 school of comput...
14 篇 school of electr...

作者

39 篇 chen xi
29 篇 xi chen
24 篇 nanning zheng
24 篇 licheng jiao
20 篇 li xi
20 篇 liu ying
18 篇 xuelong li
17 篇 anon
14 篇 xi ning
14 篇 wei li
14 篇 yuan yuan
13 篇 de-shuang huang
13 篇 yanning zhang
13 篇 xi li
12 篇 jie yang
12 篇 yang xi
12 篇 ying liu
11 篇 p. pirsch
11 篇 liu yang
11 篇 mingyi he

语言

15,621 篇 英文
675 篇 其他
144 篇 中文
20 篇 土耳其文
3 篇 葡萄牙文
2 篇 法文
2 篇 俄文
1 篇 西班牙文

检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

共 16440 条记录，以下是1831-1840 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：

Yaw and Pitch Steering Using a Nonlinear Least Square Approach for Spaceborne SAR systems

Yaw and Pitch Steering Using a Nonlinear Least Square Approa...

引用

International conference on Signal processing Proceedings (ICSP)

作者： Yongfei Ding Dinghai Xu Yu Li Zheng Fang Tao Chen Hengyang Zhang Key Laboratory on Avionics Integration Aviation Industry of China (AVIC) China Institute of Navigation and Information Airforce Engineering University Xi’an China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

In this paper, we investigate the attitude control algorithms for antenna steering of spaceborne Synthetic Aperture Radars (SAR). They are based on the method of Nonlinear Least Squares (NLS), which has the ability to fast calculate the attitude angles (yaw and pitch) of the satellite platform. Doppler centroid and Doppler slope versus range may both be set to zeros by satellite attitude control. Since the Least Mean Squares (LMS) type algorithm needs many iterations to converge, Newton’s method may be chosen to accelerate its performance. Computer simulations demonstrate the numerical precision and computational efficiency of the proposed algorithms. As a consequence, we may apply the NLS method to the SAR yaw steering issue with good results.

关键词： Satellites Attitude control Spaceborne radar Computer simulation Signal processing algorithms Signal processing Millimeter wave radar Doppler effect Synthetic aperture radar System analysis and design

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Approach to Automated Tomato Plant Leaf Disease Diagnosis 2

Deep Learning Approach to Automated Tomato Plant Leaf Diseas...

引用

2nd International conference on Electronics and Renewable systems, ICEARS 2023

作者： Karthika, I. Megha, M. Roshni, M. M. Kumarasamy College of Engineering Dept. of Computer Science Engineering Tamilnadu Karur India

ISBN: (纸本)9798350346640

India's agriculture is primary occupation and it experiences a yearly loss of 35% in crop productivity due to plant-related issues. Advances in technology, such as precision agriculture and the use of Deep learning algorithms, are helping to make this possible. A number of practical and technological challenges, including dataset collecting and labelling, variability in plant leaf images, inter-class similarity, imbalanced datasets, generalization, and real-time detection, are prevalent in the challenging task of detecting plant leaf disease. The main goal of utilizing a convolutional neural network (CNN) for plant leaf disease detection is to precisely categorize images of plant leaves into categories of healthy or diseased. Depending on the particular application scenario, there could be additional goals that researchers try to accomplish with their CNN models in addition to this main one. Tomato is a widely cultivated vegetable and is an important food crop worldwide. Employing machine learning and image processing methods for detecting diseases in tomato plant leaves can be highly efficient. These techniques can be used to analyze images of tomato leaves taken in the field, and an accurate algorithm can be used to identify the presence of disease symptoms. One such approach is using Convolutional Neural Networks (CNNs) algorithm which have been trained on a dataset of images of tomato leaves with and without disease symptoms. This can be done by gathering the images of the healthy tomato leaves and the infected ones and then training a CNN model to detect the difference. The trained model can categorize new images of tomato leaves into healthy or infected, offering a quick and precise method to identify diseases in tomato plants' leaves. © 2023 IEEE.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Improved Algorithm for Timing Synchronization of OFDM systems Based on ZC Sequences

Improved Algorithm for Timing Synchronization of OFDM System...

引用

Natural Language processing (ICNLP), International conference on

作者： xihai xie xixi Yao School of Communications and Information Engineering Xi’an University of Posts & Telecommunications Xi’an China

ISBN: (数字)9798350349115

ISBN: (纸本)9798350349122

Synchronization technique is the key to determine the performance of OFDM (Orthogonal Frequency Division Multiplexing) system, the wrong timing synchronization point will lead to serious inter symbol interference (ISI) and inter carrier interference (ICI) in OFDM system. In this paper, we analyze three traditional classical algorithms for timing synchronization based on cyclic prefixes, and design an improved Park algorithm for the higher sub-peaks in the Park algorithm. The training sequence in Park's algorithm is constructed with a ZC (Zadoff-Chu) sequence with better autocorrelation, and the autocorrelation function is divided into two parts by using the weighting property to increase the weights of each part, and finally the peaks of the timing metric function are captured. Theoretical analysis and simulation results show that compared with the traditional Park algorithm, the algorithm proposed in this paper has higher timing synchronization accuracy and better synchronization effect.

关键词： Measurement Training Accuracy OFDM Simulation Symbols Interference Synchronization Autocorrelation Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Research on Non-destructive Testing Technology for Downhole Casing Based on Constant False Alarm Rate processing

Research on Non-destructive Testing Technology for Downhole ...

引用

Intelligent Control, Measurement and Signal processing and Intelligent Oil Field (ICMSP), International conference on

作者： Wenkui Zhu Chao Shi Nanan Wu Rongxin Tong Yamin Li xinwei Wang China National Logging Corporation Xi'an China Shaanxi Key Laboratory of Measurement and Control Technology for Oil and Gas Wells Xi 'an Shiyou University Xi'an China

ISBN: (数字)9798331516550

ISBN: (纸本)9798331516567

The uniform linear multi-coil array (ULMA) has been successfully utilised for non-destructive testing of downhole casing. However, the narrow and complex detection environment underground limits the degrees of freedom of the ULMA system, thereby affecting its detection efficiency. Aiming to enhance the detection performance of ULMA in complex noise environments, this paper proposes a non-destructive testing technology for downhole casing based on constant false alarm rate (CFAR) processing. This technology establishes an array signal model for downhole casing non-destructive testing by analysing the structural characteristics of transient electromagnetic signals in the borehole and employs the linearly constrained minimum-variance (LCMV) algorithm to correct the phase offset of the array signals, enhancing detection reliability. By setting reasonable detection thresholds and combining them with CFAR processing criteria, real-time and accurate detection of casing damage is achieved. In the experiments, we built a downhole transient electromagnetic detection system using ULMA and validated the effectiveness of the proposed method through simulations of non-destructive testing of oil well casings.

关键词： Phased arrays Accuracy Array signal processing Oils Signal processing algorithms Real-time systems Reliability Transient analysis Electromagnetics Testing

来源：评论

学校读者我要写书评

暂无评论

A Novel SCD11 CNN Model Performance Evaluation with Inception V3, VGG16 and ResNet50 Using Surface Crack Dataset

A Novel SCD11 CNN Model Performance Evaluation with Inceptio...

引用

International conference on Unmanned Vehicle systems-Oman (UVS)

作者： Adil Hussain Kashif Naseer Qureshi Raja Waseem Anwar Ayesha Aslam School of Electronics and Control Engineering Chang'an University Xi'An China Department of Computer Engineering and Electronics University of Limerick Limerick Ireland Dep of Computer Science German University of Technology in Oman Muscat Oman School of Information Engineering Chang'an University Xi'An China

image processing techniques can be used to detect potential defects in images of infrastructure elements that have been collected or scanned. Aside from image processing, machine learning technologies are increasingly being applied to increase crack detection performance and resilience. A novel Surface Crack Detection Convolutional Neural Network (CNN) named the SCD11 CNN model is proposed. The main aim of this research paper is to improve efficiency and minimize the loss rate. The proposed CNN model is compared with the CNNs, including Inception V3, VGG16, and ResNet50, using a Surface Cracks Dataset. The accuracy and loss of the proposed model are compared. The results show that the proposed SCD11 CNN model performs better in test accuracy than Inception V3 and VGG16 and has a slightly lower accuracy than ResNet50.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Liquid Filling Quality Control System for Beverage Industry Using image processing (CNN)

Liquid Filling Quality Control System for Beverage Industry ...

引用

International conference on Control, Automation and systems ( ICCAS)

作者： B. Chatchapol W. Autanan W. Anan Department of Electrical Engineering Faculty of Electric Engineering Rajamangala University of Technology Lanna Chiang Mai Thailand Robotics Engineering and AI Faculty of Engineering Chiang Mai University Chiang Mai Thailand Department of Electronic Engineering and Automation Control System Faculty of Engineering Rajamangala University of Technology Lanna Chiang Mai Thailand

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

The beverage industry has been leveraging automation to enhance production efficiency. An essential advancement involves the use of AI and image processing to ensure the high quality of products. image processing systems employ sophisticated algorithms to meticulously inspect specific aspects of the production process (liquid level, lid sealing, text print). The CNN algorithm is primarily utilized to scrutinize water bottle images to verify their quality. Maintaining consistent production speed poses a challenge, underscoring the importance of examining the image processing system from various perspectives. The research proposed implementing a system that oversees liquid filling quality through an image processing algorithm, a camera module, and conveyor belt speed control to address. This system monitors liquid levels and bottle capping while the production line is operational. On average, the system achieves a 98.89 percent accuracy rate in detecting liquid levels and a 100 percent accuracy rate in sealing the lids. Furthermore, the conveyor speed control can adjust automatically to detect variations in product movement speed.

关键词： Liquids image processing Velocity control Production Quality control Inspection Belts Filling Beverage industry Monitoring

来源：评论

学校读者我要写书评

暂无评论

Review on Advanced Vehicle Recognition System: OCR and REST API Integration for Efficient Results 5

Review on Advanced Vehicle Recognition System: OCR and REST ...

引用

5th IEEE International conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Singh, Rohit Kumar Saxena, Aumreesh Kumar Jhapate, Arun Shrivastava, Ritu Srivastava, Rajiv Sirt Bhopal India Csit Sirt Bhopal India Cse Sirt Bhopal India

ISBN: (纸本)9798350383522

Vehicle number plate recognition ranks first in traffic management, especially in densely populated areas like India. This paper presents a conceptual approach that integrates state-of-the-art technologies to accurately identify vehicles using video license plate scanning.[1] Powered by a Raspberry Pi and a set of advanced algorithms, the system is ideal for securing confined spaces including educational institutions and high-security roads Using the power of OpenCV, the system catches on and runs video programs to extract sensitive data. This study digs deep into the difficult areas of acceptable behavior and photo appearance, with license plate recognition being a major focus. A notable feature is the integration of Optical Character Recognition (OCR) technology via a REST API, which provides the ability to quickly and accurately extract colors from license plates REST API continuous capture of license plates creates a plate image, which provides key information from these plates.[3]. Experimental findings confirm the capabilities of the system, showing recognition rates in standard with neural network-based strategies for number plate recognition The proposed model opens up possibilities for various applications, from regulatory requirements to checking forged vehicle registrations, extending to activity-monitoring, and encouraging electronic tax collection In together with OCR and REST API integration, this review shows a remarkable walk away progressive system detection vehicle. The convergence assures increased accuracy and skill in number plate recognition, and helps the system for safer, smarter and safer transportation systems. © 2024 IEEE.

关键词： Advanced image processing Automated Number Plate Recognition Efficient Vehicle Identification License Plate Recognition OCR Technology Optical Text Recognition REST API Integration Vehicle Detection System

来源：评论

学校读者我要写书评

暂无评论

Real Time Cheating Detection Pipeline for Online Exams 30

Real Time Cheating Detection Pipeline for Online Exams

引用

30th IEEE Signal processing and Communications Applications conference (SIU)

作者： Dadak, Ahmet Uyan, Ufuk Ozturk, Mahiye Uluyagmur Huawei Turkey R&D Ctr Istanbul Turkey

ISBN: (纸本)9781665450928

Remote exams and job interviews have gained popularity due to pandemics and the advantage of remote working conditions. Most companies and institutions use online platforms for recruitment and examination. However, one of the critical problems of remote exam systems is that the exams cannot be held in a reliable environment. In this work, we present a cheating detection system for online exams. This system provides real-time detection of suspicious events such as another person, electronic device usage, candidate absent status by accessing the microphone and camera stream of the candidate's device through the browser. The cheating detection system can detect other people than candidates, electronic device usage, voice activity, and candidate absence status using state-of-the-art deep learning algorithms. When a suspicious event is detected, its moments are recorded as a video. The advantages of the real time cheating detection pipeline are as follows: 1) The system provides real time suspicious activity detection and produce instant alarm for proctors, 2) the system does not require an external program installation, 3) the number of user the system will serve at the same time has become scalable since it is run through the browser.

关键词： Cheating detection pipeline Face recognition Object detection image processing Voice processing

来源：评论

学校读者我要写书评

暂无评论

Boosted Spectral Perception via Synergistic Vision for Cross-Domain Few-Shot Hyperspectral image Classification

Boosted Spectral Perception via Synergistic Vision for Cross...

引用

Signal, Information and Data processing (ICSIDP), IEEE International conference on

作者： xinyi Yan Jiaojiao Li Zhiyuan Zhang Haitao Xu Tie Zheng Qian Du ISN Xidian University Xi’an China Key Laboratory of EITSS NSSC Beijing China Department of Electrical and Computer Engineering Mississippi State University Starkville USA

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Cross-domain few-shot learning (CDFSL) hyper-spectral image classification (HSIC) techniques have significantly enhanced the performance of HSIC under a few annotations. Due to the scattered spatial distribution of HSI and limited labels, the spatial information of the HSI sample is restricted, which means the spectral information may contain more discriminative category features than spatial information. However, most existing CDFSL HSIC methods lack targeted spectral discriminative feature extraction and struggle to capture spectral subtleties. To address this, a Human Eye-like Dual-Branch Network (HEDB-Net) is proposed, comprising a central branch and a peripheral branch. The central branch focuses on extracting core features from complete spectral dimension HSI patches. Simultaneously, these patches are input into the peripheral branch via random sampling and reintegration of spectral bands, enabling the model to perceive initially dispersed spectral information. These two branches represent the model’s central and peripheral vision for the spectrum, allowing it to focus on different levels of feature information and significantly boosting spectral perception capabilities. To fully leverage the advantages of synergistic vision, a consistency constraint is applied to align their category probability prediction distributions, which helps ensure consistency in classification decisions between the two branches. Experimental results on the PaviaU dataset demonstrate that HEDBNet outperforms other advanced algorithms in terms of overall accuracy(OA), average accuracy(AA), and Kappa coefficient. This proves that HEDBNet can simultaneously focus on primary and secondary spectral features, thus significantly boosting classification accuracy.

关键词： Visualization Accuracy Visual systems Feature extraction Boosting Classification algorithms Data mining Few shot learning image classification Hyperspectral imaging

来源：评论

学校读者我要写书评

暂无评论

Advances in systems Engineering - Proceedings of the 30th International conference on systems Engineering, ICSEng 2023

Advances in Systems Engineering - Proceedings of the 30th In...

引用

Advances in systems Engineering - Proceedings of the 30th International conference on systems Engineering, ICSEng 2023

ISBN: (纸本)9783031405785

The proceedings contain 49 papers. The special focus in this conference is on systems Engineering. The topics include: Cervical Cancer Tumor Delineation for Brachytherapy Using Diffusion Weighted images;the Use of Strychnos Potatorum in an Environmental IoT System for the Treatment of Commercial and Domestic Washing Discharge in Continuous Column Studies;Applying Machine Learning to Minimize the Impact of Sensor Failures to RTOS Based Internet of Things systems;detecting Cyber-Attacks and Power System Disturbances in Smart Grids with Deep Forest;forensics with IoT Based systems’ Evidences: A Futuristic Review on Forensic and IoT Frameworks;the Analysis of Security Properties for Dynamic Privacy-Policy in Data Collection and Access Control;Design Optimization of Wide TR LC-VCOs;analog Frequency Sampling Filters;aiDashcam: A Vehicle Collision Responsibility Evaluation System Based on Object Detection and OpenStreetMap;the Design and Implementation of Linear Phase Analog Frequency Sampling Filters;xi Bass: Design of a Smart Sound Application that Implements the "Physical Feel" of Playing Slap Bass;a Transposed Jacobian Position Control for Differential Drive Mobile Robots;neural Extended Kalman Filter Tracker Using the ReLu Function;adaptive Spacecraft Attitude Control and Asteroid Parameter Estimation;Joint Power Control and Altitude Planning for Energy-Efficient UAV-Assisted Vehicular Networks;estimating Service Regions for Battery Exchange Stations;proposed Intelligent Energy Management systems for Hybrid Electric Traction System;evaluating the Performance of Intelligent Energy Management systems for Hybrid Electric Vehicles Based on Embedded Raspberry Pi Module;A New Hybrid Method for Electrical Load Forecasting Based on Deviation Correction and MRMRMS;Forecasting the Effect of Dust and Irradiance in PV Panel Using image processing and ANN;blockchain-Based Volunteers Management System.

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 << < 180 181 182 183 184 185 186 187 188 189 > >>

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：