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

14,163 篇 会议
291 篇 期刊文献
199 册 图书
6 篇 学位论文

馆藏范围

14,659 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
- 2,529 篇 电气工程
- 1,448 篇 信息与通信工程
- 934 篇 控制科学与工程
- 744 篇 光学工程
- 548 篇 生物医学工程（可授...
- 530 篇 电子科学与技术（可...
- 512 篇 仪器科学与技术
- 486 篇 机械工程
- 358 篇 生物工程
- 245 篇 测绘科学与技术
- 182 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
- 110 篇 安全科学与工程
- 96 篇 化学工程与技术
3,825 篇 理学
- 2,633 篇 物理学
- 1,003 篇 数学
- 411 篇 生物学
- 276 篇 系统科学
- 255 篇 统计学（可授理学、...
- 132 篇 化学
1,610 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...
781 篇 管理学
- 469 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

2,875 篇 image processing
1,506 篇 image segmentati...
1,202 篇 signal processin...
660 篇 feature extracti...
625 篇 cameras
591 篇 image edge detec...
590 篇 signal processin...
530 篇 image coding
522 篇 image reconstruc...
473 篇 real-time system...
416 篇 algorithm design...
354 篇 image analysis
352 篇 image color anal...
331 篇 image enhancemen...
329 篇 deep learning
311 篇 object detection
306 篇 pixel
300 篇 hardware
299 篇 real time system...
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
8 篇 ilias maglogiann...
7 篇 busch christoph
7 篇 zelensky a.
7 篇 bovik alan c.
7 篇 jerry m. mendel
7 篇 kupriyanov a.v.

语言

14,421 篇 英文
138 篇 其他
81 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 14659 条记录，以下是801-810 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：

Comparative image processing and Object Detection in Aerial Search and Rescue

Comparative Image Processing and Object Detection in Aerial ...

引用

Cognitive Robotics and Intelligent systems (ICC - ROBINS), International conference on

作者： Sushil Rawat Abhay Singh Rawat Vikas Singh Mewad Himadri Vaidya Department of Computer Science and Engineering Graphic Era Hill University Dehradun India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372755

Aerial search and response plays an important role in finding and rescuing persons in need. Unmanned Aerial Vehicle (UAV) -acquired aerial images provide an intensive profile search area and facilitate identification of potential targets. To improve the effectiveness of aircraft Search and Rescue missions, this study compares many object detection algorithms and image processing methods. The investigated object detection methods are Mask R-CNN, SSD, and YOLOv8, and image processing techniques are contrast improvement and image brightness control. The effectiveness of these strategies has been evaluated by using real aerial images that include different targets such as humans, vehicles, and fire. The results show how well the object detection algorithms work to accurately distinguish targets, and how an attractive image processing approach improves the image performance of the best object detection model, as well as how the performance of the best object detection model with image processing can improve the performance of model. This research shows that combining image processing (contrast and brightness) with an optimal object detection algorithm (Mask R-CNN) significantly improves target detection in aerial search and rescue. While only Mask R-CNN performs best, adding image processing increases its accuracy to 0.92, mAP to 0.89, and makes it more reliable in finding people in need. This shows the potential of this joint approach to save people in air rescue missions.

关键词： image quality image processing Brightness Object detection Search problems Autonomous aerial vehicles Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Diagnosis of Rice Sheath Rot Disease: A Wavelet-Filtered Approach for Feature Extraction and Analysis

Deep Learning-Based Diagnosis of Rice Sheath Rot Disease: A ...

引用

2024 International conference on Knowledge Engineering and Communication systems, ICKECS 2024

作者： Atheeswaran, Athiraja Maheshkumar, K. Jayareka, K.S. Janani, B. Lakshmanan, K. Sobiyaa, P. Malla Reddy College of Engineering Department of Cse Telangana Hyderabad India Bannari Amman Institute of Technonology Dept of Computer Science and Design Tamilnadu Erode India Sona College of Technology Dept of Computer Science and Engineering Tamilnadu Salem India Dr.NGP Institute of Technology Department of Computer Science and Business Systems Tamilnadu Coimbatore India Hindusthan College of Engineering and Technology Dept of Cse Tamilnadu Coimbatore India Bannari Amman Institute of Technonology Dept of Information Technology Tamilnadu Erode India

ISBN: (纸本)9798350359688

A major danger to rice farming, rice sheath rot disease affects the quantity and quality of one of the main food crops grown worldwide. This research uses a large dataset gathered from many sources, such as agricultural universities, research centres, and first hand field observations, to provide a unique method of diagnosing Rice Sheath Rot disease using cutting-edge deep learning algorithms. Our work is primarily focused on creating a dependable and effective diagnostic tool using state-of-the-art image processing and machine learning methods. Wavelet filters are applied in the first step of our approach to pre-process photos. This method is essential for eliminating noise and improving the quality of the dataset, which is made up of high-definition photos of rice plants with the disease Sheath Rot. The colour, shape, and texture of the sick spots are then analyzed using advanced feature extraction techniques. When separating plant tissues that are diseased from those that are not, these characteristics are essential. Convolutional Neural Networks (CNN), our primary diagnostic model's foundation, were selected due to their shown efficacy in picture recognition and classification applications. The preprocessed and feature-enhanced dataset is used to train the CNN model, giving it the ability to recognize the complex patterns and traits connected to Sheath Rot illness. The architecture of the model is built to maximize efficiency and accuracy, guaranteeing quick and accurate illness identification. By utilizing AI and deep learning, the proposed method seeks to not only help farmers and agronomists identify diseases early on but also make a substantial contribution to the area of agricultural disease diagnostics. Combine that our method, which combines CNN-based analysis with wavelet-filtered pre-processing establishes a new standard for the identification and treatment of Rice Sheath Rot disease. This might result in improved crop management techniques and more pot

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

Hybrid prognosis of drill-bits based on direct inspection 5

Hybrid prognosis of drill-bits based on direct inspection

引用

5th International conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Bernini, Luca Malguzzi, Ugo Albertelli, Paolo Monno, Michele Politecn Milan Dept Mech Engn Via Masa 1 I-20156 Milan Lombardy Italy MUSP Macchine Utensili Sistemi Prod Str Torre Razza I-29122 Piacenza Emilia Romagna Italy

Within the paradigm of industry 5.0, manufacturing systems are seeking for human-centred production, where the operator finds high-level supervision tasks. In this context, low-level decision making should be performed by machines themselves. In this paper, a hybrid prognosis algorithm is developed to automatically inspect the cutting edges of drill-bits and to predict their Remaining Useful Life (RUL) and the associated probability density function. The solution relies on the automatic measurement of flank wear through convolutional filtering and edge detection. Prognosis exploits particle filter, which updates multi-layer perceptron with online data, to adaptively predict drill-bits RUL. The solution reduces the experimental preliminary run-to-failures needed for training standard machine learning algorithms, exploiting them in a real-time adaptive scenario, while predicting tool RUL under untested and variable cutting process operations. The algorithm uses direct wear observations, taken during set- up times (e.g., tool changes, workpiece change), thus not interfering with the process. (c) 2023 The Authors. Published by ELSEVIER B.V.

关键词： Hybrid prognostics Direct drill-bit inspection image processing Remaining Useful Life prediction

来源：评论

学校读者我要写书评

暂无评论

Vision-based Human Identification with Face and Nametape Recognition in Aerial Casualty Monitoring System 32

Vision-based Human Identification with Face and Nametape Rec...

引用

32nd IEEE International conference on Robot and Human Interactive Communication (RO-MAN)

作者： Lee, Jaeyeon Quist, Ethan Chambers, Jonathan Peel, Justin Roman, Kelly Fisher, Nathan TATRC Ft Detrick MD 21702 USA Arete Arlington VA USA

ISBN: (纸本)9798350336702

In emergency rescue scenarios, rapid identification of human casualties is a critical first step in enhancing emergency medical response. This task can be limited by the physical and cognitive capacity of rescue personnel, who are exposed to significant risk. The use of small unmanned aerial systems (sUAS) equipped with autonomous casualty assessment abilities can reduce these limitations and risks by enabling remote casualty detection, identification, and vitals assessment, providing standoff protection, and eliminating the need for human personnel to access the potentially hazardous scene. This paper presents a vision-based casualty assessment framework and specifically discusses our casualty identification software, which is designed to recognize the faces of casualties and identify their nametapes in images captured by sUAS under realistic conditions. Our approach addresses the limitations of the sUAS-captured long-distance images to enable accurate identification in challenging casualty monitoring situations. The face and nametape recognition algorithms will be integrated into the larger casualty perception framework and embedded into sUAS platforms to assist with emergency rescue operations. The total casualty perception system will detect, identify, and evaluate the condition of casualties from a remote location, providing standoff protection to first responders and rapid information to inform a suitable medical treatment plan.

关键词： Aerial image processing Neural network Face and text recognitions Synthetic text data Human detection identification monitoring Unmanned Aerial systems

来源：评论

学校读者我要写书评

暂无评论

An Efficient Hybrid Technique for Automatic License Plate Recognitions 1

An Efficient Hybrid Technique for Automatic License Plate Re...

引用

1st International conference on Recent Developments in Electronics and Communication systems, RDECS 2022

作者： Devi, Terli V. Satyanarayana, V. Singh, Mahesh K. Department of ECE Aditya Engineering College Surampalem India Department of ECE Aditya Engineering College A.P. Surampalem India

ISBN: (纸本)9781643683607

Automatic License Plate Recognition (ALPR) is an embedded real-time technology that automatically recognizes a vehicle's license plate. There are numerous uses, ranging from complex security to shared spaces, parking to acceleration. The ALPR is used to control the traffic and to take hold for those who violate the traffic rules. Automatic recognition of vehicle license plate numbers has become critical in our daily lives due to the rapid expansion of autos and transportation systems, which makes it difficult for the general public to keep up with and monitor. A license plate identification system uses image processing theory and soft computing technology to identify cars based on their number plates. Using fewer and simpler algorithms can reduce both calculation time and execution time needed by most number plate localization approaches. This is because most of these techniques require several operations. License plate recognition is the most used approach in traffic-related applications. Various approaches, tactics, and algorithms have been developed for the identification and recognition of license plates. In the context of Indian license plate identification, only a few research have looked at the topic. Character segmentation and character recognition are two of the three key steps in identifying a license plate. © 2023 The authors and IOS Press.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Benchmarking and Analyzing 3D-aware image Synthesis with a Modularized Codebase 37

Benchmarking and Analyzing 3D-aware Image Synthesis with a M...

引用

37th conference on Neural Information processing systems, NeurIPS 2023

作者： Wang, Qiuyu Shi, Zifan Zheng, Kecheng Xu, Yinghao Peng, Sida Shen, Yujun Ant Group China HKUST Hong Kong CUHK Hong Kong ZJU China

ISBN: (纸本)9781713899921

Despite the rapid advance of 3D-aware image synthesis, existing studies usually adopt a mixture of techniques and tricks, leaving it unclear how each part contributes to the final performance in terms of generality. Following the most popular and effective paradigm in this field, which incorporates a neural radiance field (NeRF) into the generator of a generative adversarial network (GAN), we build a well-structured codebase, dubbed Carver, through modularizing the generation process. Such a design allows researchers to develop and replace each module independently, and hence offers an opportunity to fairly compare various approaches and recognize their contributions from the module perspective. The reproduction of a range of cutting-edge algorithms demonstrates the availability of our modularized codebase. We also perform a variety of in-depth analyses, such as the comparison across different types of point feature, the necessity of the tailing upsampler in the generator, the reliance on the camera pose prior, etc., which deepen our understanding of existing methods and point out some further directions of the research work. We release code and models here to facilitate the development and evaluation of this field. © 2023 Neural information processing systems foundation. All rights reserved.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Optimal Target Interception using Foldable Quadrotor with Rotating Arms

Optimal Target Interception using Foldable Quadrotor with Ro...

引用

International conference on image and Signal processing and their Applications (ISPA)

作者： Zakaria Mehal Yasser Bouzid Mohammed Guiatni Saddam Hocine Derrouaoui Complex Systems Control and Simulators (CSCS) Laboratory Ecole Militaire Polytechnique Bordj el Bahri Algeria Ecole Superieure Ali Chabati Algires Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

This article addresses a critical problem in the field of target interception using a new foldable quadrotor with rotating arms. The primary challenge is maximizing linear acceleration to enhance the quadrotor’s ability to intercept targets effectively. To address this challenge, we introduce a novel optimization framework. Our study employs two distinct optimization algorithms, namely the genetic algorithms and the whales optimization algorithm, to ascertain the maximum attainable linear acceleration for the foldable quadrotor. The results obtained are confirmed through the use of our innovative foldable quadrotor.

关键词： Heuristic algorithms Signal processing algorithms Life estimation Signal processing Whale optimization algorithms Optimization Robots

来源：评论

学校读者我要写书评

暂无评论

Unveiling the Depths: A Comprehensive Analysis of Natural Language processing and Generative Adversarial Neural Networks for Text Generation Models in Deep Learning 1

Unveiling the Depths: A Comprehensive Analysis of Natural La...

引用

1st International conference on Circuits, Power, and Intelligent systems, CCPIS 2023

作者： Agarwal, Rashi Agarwal, Himanshu Pandey, Senam Gehu India

ISBN: (纸本)9798350315769

Deep Learning comes under Machine Learning that accomplishes more power and flexibility by learning to present different concepts or relations of real world to simpler concepts. We use Deep learning fundaments in this paper because it has massive amount of data that helps in innovations. We include these neural networks of deep learning because it comes with a high accuracy rate with lower computations. Natural processing Language (NLP) and Generative Adversarial Network (GAN) are the methods that individually contribute to the text generation method. Although these are two different technologies giving the output for some common motive where Text generation plays a very important role in smart translations and dialogue systems. This review paper presents a model centered around text generation. This is done because combinedly we want to present what can be different approaches to look at a model like this. To solve the problem of unnecessarily used large texts, unsatisfactory feedback, NLP is used for text generation, GANN is used for text generation model, image generation etc. Finally, this is done to reduce time complexities, speed, efficiency in process because this is noticed that learning for a problem plays a vital role in education to enhance features. © 2023 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

C-ESRGAN: Synthesis of super-resolution images by image classification 5

C-ESRGAN: Synthesis of super-resolution images by image clas...

引用

5th IEEE International conference on image processing Applications and systems (IPAS)

作者： Liu, Jingan Chandrasiri, Naiwala P. Kogakuin Univ Intelligent Media Lab Tokyo Japan

ISBN: (纸本)9781665462198

With the development of deep learning, super-resolution image synthesis techniques for enhancing low-resolution images have advanced remarkably. However, mainstream algorithms focus on improving the quality of the entire image on average and this may result in blurring. In this paper, we propose three key components for synthesizing super-resolution images that can reflect the fine details of an image. We synthesize super-resolution images by image classification. First, the neural network weights learned using the images in the same image category were utilized in synthesizing super-resolution images. For this purpose, image classification was performed using a transfer-trained ResNet. Second, SENet was applied to the generators in our proposed method to obtain detailed information about the images. Finally, the feature extraction network was changed from VGG to ResNet in order to get more important features. As a result, we achieved better image evaluation values (PSNR, NIQE) for the super-resolution images of dogs and cats compared to the previous studies. Furthermore, the images were generated more naturally on the benchmark dataset.

关键词： Super-Resolution Generative Adversarial Networks (GANs) SENet image Classification ResNet

来源：评论

学校读者我要写书评

暂无评论

Hybrid image processing Device as Wearable Aide for Visually Impaired 8

Hybrid Image Processing Device as Wearable Aide for Visually...

引用

8th International conference on Advanced Computing and Communication systems, ICACCS 2022

作者： Papanai, Ashish Kaushik, Harsh Maharaja Agrasen Institute of Technology Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9781665408165

With the advent of technology and algorithms in image processing, many wearable aides are available in the market, and researchers across the globe are developing new solutions. The existing solutions and products fail to provide an economically viable and single solution to the problem of visually impaired people. This study introduces AIde, a novel system amalgamating optimized computer vision algorithms and wearable IoT devices to convert the information extracted from the camera mounted on the user to audio-based signals for assisted mobility. The proposed system has three user modes: indoor, outdoor, and hybrid, which can be modified using the buttons provided on the wearable device. The indoor mode can be used for object detection and classification to increase the accessibility of the objects inside a confined space, and the outdoor mode will provide the user with enhanced mobility and directional sense based on the highlighted path captured by the mounted camera. The hybrid model combines both the features of indoor and outdoor modes, which will detect objects and improve mobility simultaneously. The proposed model is optimized to work in a computationally efficient environment with an at par efficiency and accuracy as the state-of-art and costly market alternatives. © 2022 IEEE.

关键词： Edge computing

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 << < 77 78 79 80 81 82 83 84 85 86 > >>

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：