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

18,409 篇 会议
217 册 图书
188 篇 期刊文献

馆藏范围

18,811 篇 电子文献
3 种 纸本馆藏

日期分布

学科分类号

13,438 篇 工学
- 9,747 篇 计算机科学与技术...
- 6,612 篇 软件工程
- 3,603 篇 控制科学与工程
- 2,471 篇 信息与通信工程
- 2,304 篇 电气工程
- 1,741 篇 光学工程
- 1,517 篇 机械工程
- 1,118 篇 生物工程
- 909 篇 电子科学与技术（可...
- 864 篇 生物医学工程（可授...
- 785 篇 仪器科学与技术
- 574 篇 动力工程及工程热...
- 543 篇 交通运输工程
- 513 篇 安全科学与工程
- 499 篇 材料科学与工程（可...
- 454 篇 化学工程与技术
- 349 篇 土木工程
- 335 篇 网络空间安全
5,368 篇 理学
- 2,366 篇 物理学
- 2,288 篇 数学
- 1,231 篇 生物学
- 598 篇 统计学（可授理学、...
- 589 篇 系统科学
- 449 篇 化学
2,423 篇 管理学
- 1,722 篇 管理科学与工程(可...
- 830 篇 图书情报与档案管...
- 687 篇 工商管理
1,096 篇 医学
- 972 篇 临床医学
- 561 篇 基础医学(可授医学...
- 362 篇 药学(可授医学、理...
364 篇 法学
259 篇 经济学
253 篇 农学
218 篇 教育学
64 篇 军事学
25 篇 艺术学
20 篇 文学
3 篇 哲学

主题

1,582 篇 computer vision
370 篇 deep learning
314 篇 computer archite...
282 篇 cameras
255 篇 object detection
253 篇 computational mo...
237 篇 control systems
236 篇 computer science
220 篇 image segmentati...
211 篇 feature extracti...
209 篇 internet of thin...
187 篇 access control
173 篇 machine vision
158 篇 neural networks
137 篇 artificial intel...
133 篇 face recognition
130 篇 process control
130 篇 real-time system...
129 篇 data mining
128 篇 support vector m...

机构

47 篇 chitkara univers...
46 篇 school of comput...
43 篇 school of contro...
29 篇 maharishi school...
24 篇 karnataka bangal...
21 篇 school of comput...
19 篇 maharishi school...
17 篇 chitkara univers...
17 篇 college of compu...
15 篇 university of ch...
15 篇 school of comput...
14 篇 south china univ...
14 篇 dept. of compute...
14 篇 department of co...
14 篇 chitkara univers...
14 篇 college of compu...
13 篇 school of comput...
12 篇 school of comput...
12 篇 centre of interd...
12 篇 school of comput...

作者

19 篇 wang lei
18 篇 li yang
17 篇 wang wei
16 篇 yang yang
14 篇 liu yang
13 篇 wang hui
13 篇 ryszard tadeusie...
13 篇 marcin korytkows...
12 篇 wang ping
12 篇 wang jian
12 篇 sato jun
12 篇 jacek m. zurada
11 篇 zhang tao
11 篇 sakaue fumihiko
11 篇 zhang lei
11 篇 huang tinglei
11 篇 liu lei
10 篇 lei wang
10 篇 li xin
10 篇 wang jing

语言

16,844 篇 英文
1,863 篇 其他
133 篇 中文
16 篇 俄文
7 篇 西班牙文
2 篇 法文
2 篇 土耳其文

检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

共 18814 条记录，以下是4331-4340 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：

Collation of Face Recognition Techniques: Image Registration and Dimension Reduction Approaches

Collation of Face Recognition Techniques: Image Registration...

引用

Technological Advancements in Computational Sciences (ICTACS), international conference on

作者： Gaurav Gupta Anuj Kumar Goel Computer Science Engineering Department Chandigarh University Apex Institute of Technology Mohali Punjab India Electronics and Communication Engineering Department Chandigarh University Chandigarh University Mohali Punjab India

Faces must be present in images for intelligent vision-based human computer interaction to work. Since many years ago, face recognition research has been ongoing and significant. This procedure entails facial tracking, expression recognition, and many other things. It is crucial to first register the positions of the photos in this process. However, maintaining such a database is highly challenging because of pose invariance, illumination invariance, shift invariance, scale and noise invariance. The Image Registration Algorithm will be used to register all of the unknown photos that are currently in the database. With the use of a reference, this registration technique tries to align a pattern image. This algorithm will produce features that are independent of translation, scaling and rotation. High dimension space, which must be decreased using a dimension reduction algorithm, is the primary challenge in face recognition. This low dimension subspace can be produced using dimension reduction methods like as Linear Discriminant Analysis, Principal Component Analysis and Locality Preserving Projection. In order to find the needed image from the given database, this study will first minimize the dimensions of every image that is now there.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Clothing Parsing using Extended U-Net 16

Clothing Parsing using Extended U-Net

引用

16th international Joint conference on computer vision, Imaging and computer Graphics Theory and Applications (VISIGRAPP) / 16th international conference on computer vision Theory and Applications (VISAPP)

作者： Vozarikova, Gabriela Stana, Richard Semanisin, Gabriel Pavol Jozef Safarik Univ Kosice Inst Comp Sci Jesenna 5 Kosice Slovakia

ISBN: (纸本)9789897584886

This paper focuses on the task of clothing parsing, which is a special case of the more general object segmentation task well known in the field of computer vision. Each pixel is to be assigned to one of the clothing categories or background. Due to complexity of the problem and lack of data (until recently) performance of the modern state-of-the-art clothing parsing models expressed in terms of mean Intersection over Union metric (IoU) does not exceed 55%. In this paper, we propose a novel multitask network by extending fully-convolutional neural network U-Net with two side branches - one solves a multilabel classification task and the other predicts bounding boxes of clothing instances. We trained this network using a large-scaled iMaterialist dataset (Visipedia, 2019), which we refined. Compared to well performing segmentation architectures FPN, DeepLabV3, DeepLabV3+ and plain U-Net, our model achieves the best experimental results.

关键词： U-Net Clothing Parsing Segmentation computer vision Multitask Learning Deep Learning Fully-convolutional Network

来源：评论

学校读者我要写书评

暂无评论

Classification of Bipolar Disorder Using Deep Learning Models on fMRI Data 1

引用

3rd international conference on Innovations in Computational Intelligence and computer vision, ICICV 2022

作者： Chauhan, Harsh Gadhiya, Poojan Sharma, Abhishek Department of Computer Science and Engineering The LNM Institute of Information Technology Rajasthan Jaipur302031 India Department of Electronics and Communication Engineering The LNM Institute of Information Technology Rajasthan Jaipur302031 India

ISBN: (数字)9789819926022

ISBN: (纸本)9789819926015

The use of functional magnetic resonance imaging (fMRI) has been widely used to detect brain abnormalities linked to Bipolar Disorder. These borderline diseases are either inherited or the result of parental exposure to great stress and worry during a child’s formative years. Using machine learning models to predict such diseases has been widely adopted, but deep learning models are gone unseen. Our experiments are conducted on fMRI datasets consisting of bipolar disorder subjects and other neuropsychiatric disease subjects. The fMRI data passes through a pipeline that preprocesses the image, extracts time series, and removes non-essential features before passing it to the deep learning models. Preprocessing is performed on FuNP software rather than normal software like fMRIprep. The preprocessed fMRI image is converted to a NIFT1 object that allows us to extract the time series of an image. Spatial maps of the time series reveal there are many irrelevant components not contributing to the training of our model, so feature selection was a necessary approach to reduce space as well as time. We find it by taking an average of all brain signals in all components of all Bipolar Subjects to estimate which brain signals affect which region of our brain. This helps us to pick out only the important components which will contribute to being an actual feature in our input. The features then come down to the two models ANN and LSTM. Results show that deep learning models like ANN are not too efficient with neuroinformatics diseases due to the low availability of datasets, but recurrent neural networks have proved to be efficient. The deep learning model achieves 72% accuracy in predicting the correct classes for the dataset. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

A New Simple 7D Hyperchaotic System with Hidden Attractors and Electronic Circuit 4

A New Simple 7D Hyperchaotic System with Hidden Attractors a...

引用

4th international conference on Current Research in Engineering and Science Applications, ICCRESA 2022

作者： Aziz, Shua’a M. Al-Azzawi, Saad Fawzi University of Mosul Dept.: Mathematics / College College of Computer Science and Mathematics Mosul Iraq

ISBN: (纸本)9798350334944

A new 16-term simple 7D hyperchaotic system with three control parameters is constructed from a 5D hyperchaotic Yang system via nonlinear and linear state feedback strategies. The proposed system belongs to hidden attractors since it has no equilibria or an infinite number of equilibria points. With changing parameters, different behaviors are founded, such as hyperchaotic, hyperchaotic with 2-torus, and hyperchaotic with 3-torus. This system's dynamical analysis investigated numerically and theoretically, including divergence, equilibria points, Lyapunov exponents, phase portrait, coexisting attractors, Lyapunov dimension, and circuit realization. In addition, hybrid projective synchronization (HPS) has been done between the two identical 7-dimensional systems. This work is exceptionally new and straightforward compared to the known 7D hyperchaotic systems and satisfied Sprott's 3rd condition for publishing. © 2022 IEEE.

关键词： Hopf bifurcation

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Survey on Traffic Light Detection Sensors for Vehicle Safety and Automatic Emergency Braking Systems Using Deep Learning Techniques 3rd

A Comprehensive Survey on Traffic Light Detection Sensors fo...

引用

3rd international conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Gowri, B. Shyamala Priya, G. Vishnu Anjana, S. Arjun, V. Kodal, Devendraa Department of Computer Science and Engineering Easwari Engineering College Tamil Nadu Chennai India

ISBN: (纸本)9789819783540

The integration of Traffic Light Detection (TLD) systems with Advanced Emergency Braking Systems (AEBS) marks a critical milestone in enhancing road safety and paving the way for advanced autonomous driving. This survey paper provides a panoramic and extensive overview of the state-of-the-art TLD solutions leveraging sensors and deep learning techniques. With an increasing emphasis on accident prevention and traffic management, the intersection of TLD and AEBS has become a focal point of research and development. This survey begins by elucidating the fundamental challenges associated with TLD, including varying environmental conditions, occlusions, and complex traffic scenarios. We explore the pivotal role of sensors such as cameras, LiDAR, and radar in providing the requisite data for TLD, and delve into the intricacies of sensor fusion techniques for enhanced perception. Deep Learning has emerged as a cornerstone technology in TLD, enabling robust object detection, classification, and real-time decision-making. We meticulously analyze a spectrum of deep learning architectures including Single-Shot Detectors (SSD), Faster R-CNN, YOLO, and custom-designed networks tailored for TLD applications. Furthermore, the survey examines critical components of the TLD pipeline, encompassing data collection, preprocessing, model training, real-time inference, and integration with AEBS. Emphasis is placed on real-time constraints, multi-modal sensor fusion, and adaptability to diverse traffic light configurations. The paper also delves into the significance of accurate traffic light state prediction, going beyond mere detection to anticipate traffic light changes and optimize vehicle control actions. Human-centric interaction and privacy concerns are addressed, encompassing driver warnings, user interfaces, and data anonymization strategies. Moreover, the survey discusses the importance of safety, validation, and collaboration within the TLD and AEBS ecosystem, emphasizing compl

关键词： Road and street markings

来源：评论

学校读者我要写书评

暂无评论

Upcoming Possibilities for Data 6G: vision and Design Developments

Upcoming Possibilities for Data 6G: Vision and Design Develo...

引用

Advance Computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Daxa Vekariya Akash Kumar Bhagat Department of CSE PIET Parul University Department of Computer Science ARKA JAIN University

Internet of Thing (IoT) systems using sixth generation (6G) wireless systems, including such haptic feedback, social contact, and expanded realities, have a wide range of requirements for latencies, dependability, bit rate, and consumer performance measures. In terms of managing, run, and optimize the 6Portable wireless network and its core IoT service, it is necessary to create a new structure in order to enable IoT programs over 6G. Digital twins (DT) can serve as the foundation for this type of new 6G infrastructure. The 6G physical system is portrayed virtually by DTs, which also include the techniques, modern communications, computer processing platforms, & confidentiality and safety technicians. The primary design objectives are presented first. Firstly, we outline the essential design specifications for utilizing a DT to enable 6G. Then, design patterns and elements including edge-cloud-based twins, cloud-based twins, and advantage twins are discussed. We also give a comparative description of different twins. Lastly, we present and suggest suggestions for a number of potential future study trajectories.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Smart Irrigation System Implementing in Smart Campus

Smart Irrigation System Implementing in Smart Campus

引用

Electronic Communications, Internet of Things and Big Data (ICEIB), international conference on

作者： Shin-Hung Pan Whai-En Chen Wei-Sung Chen Department of M-Commerce and Multimedia Applications Asia University Taiwan Computer Science and Information Engineering Asia University Taiwan Office Information and Communication Technology Asia University Taiwan

Smart campus has many potential applications. As a result of advancements in various control components and network technologies, many traditional campuses that require vast labor are managed by campus intelligence to ensure effective execution and management. We integrate smart control and sensing devices into traditional manual watering operations to address issues of the traditional campuses. The campus watering operation is one of the primary goals of future smart campus and Internet of Things (IoT) development. The precision watering system contributes to the university's achievement of the Sustainable Development Goals (SDGs). The application of artificial intelligence is intended not only to replace human resources but also to preserve experience and promote professionalism.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Robust State Feedback control of DC-DC Boost Converter using Legendre Polynomials

Robust State Feedback Control of DC-DC Boost Converter using...

引用

Electrical Machines and Drives (ICEMD), international conference on

作者： Soroush Sarmad Saeed Khorashadizadeh R&D Department Nian Electronic Co. Mashhad Iran Faculty of Electrical and Computer Engineering University of Birjand Birjand Iran

In this paper, a robust state feedback controller is presented to track output voltage of boost converter. According to the applications of boost converter in modern industry such as electric cars, solar inverters and DC motor drives, the ability to control output voltage is an important parameter. As the model of boost converter is a nonlinear system, the linear classical controllers may not suffice. In this paper, the model of boost converter is extracted and a simplified state feedback controller is presented which uses Legendre polynomials in order to compensate the eliminated terms. For validation of proposed method, this controller is compared with classical proportional integral controller from the view point of speed and simplicity. The simulation results prove that this controller can not only maintain stability even in occurrence of error in current sensor, but also it can track the reference voltage very fast with no steady state error.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Disease Detection in Grape Leaves Using Convolutional Neural Networks 3rd

Disease Detection in Grape Leaves Using Convolutional Neural...

引用

3rd international conference on Intelligent Systems and Applications, ICISA 2024

作者： Naik, Varsha Baraskar, Trupti Khatri, Viren Kolhe, Parimal Katyarmal, Mitheelesh School of Computer Engineering and Technology MIT World Peace University Dr. Vishwanath Karad Maharashtra Pune411038 India

ISBN: (纸本)9789819798384

Grape cultivation is vital to the global economy, but various diseases threaten grapevine health and yield. Early and accurate disease detection is crucial for implementing effective control measures. Traditional methods rely on visual inspection by experts, which is subjective and time-consuming. Automated approaches using deep learning offer a promising alternative. The goal of this study was to create a convolutional neural network (CNN) model that can identify grapevine leaf diseases reliably. The aim of the study was to train the model for distinguishing between healthy and infected leaves by three diseases that are common in them such as black rot, esca, and leaf blight. We collected a dataset of images containing healthy and diseased grape leaves. The dataset was pre-processed and augmented to increase data diversity and ensure consistency. The CNN model was developed using TensorFlow and Keras and consisted of convolutional, pooling, dense, and activation layers. Optimizations were implemented using cross-entropy loss function, adam optimizer, and Dropout layers. Model performance was evaluated using metrics such as accuracy of the model, the precision at which it cannot wrongly label a negative sample, the recall at which it can find all the positive outputs, and F1-score which is the ratio between precision and recall. The developed CNN model achieved high accuracy in disease identification. We observed significant accuracy, precision, F1-score, and recall values across all disease categories, demonstrating the model's effectiveness in distinguishing between healthy and diseased leaves. This study successfully demonstrates the potential of CNNs for automated grape leaf disease identification. The developed model offers a promising tool for viticulturists to improve early disease detection and ultimately enhance grape yield and quality. Future research could focus on expanding the model's capabilities to identify a wider range of diseases and exploring its

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

An adaptive black box attack algorithm based on improved differential evolution 3

An adaptive black box attack algorithm based on improved dif...

引用

3rd international conference on Information Science, Parallel and Distributed Systems, ISPDS 2022

作者： Zhang, Ran Wang, Yifan Yin, Yifeng College of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou China

ISBN: (数字)9781665487474

ISBN: (纸本)9781665487474

As an important part of artificial intelligence technology, deep learning is widely used in various fields of contemporary society. The security of deep learning directly affects the effectiveness of its application in different fields. Effective attack algorithms can evaluate the security of deep learning models, and black box attacks are one of the important methods for testing the security of deep learning algorithms. An adaptive black box attack algorithm based on improved differential evolution is proposed to solve the problems of many queries, difficult selection of attack points that may cause higher attack costs in applications. The algorithm sets the variation factor as a linear decreasing function, uses the fitness function to adaptively control the change of the cross probability factor to improve the global search ability and accelerate the convergence rate, proposes a new variation strategy to enhance the ability of global search and local exploitation and the accuracy of searching attack points, and optimizes the loss function and the calculation method of gradient for defining decisions in deep learning models to improve the effectiveness and efficiency of black box attacks. The results of the comparison experiments show that the attack success rate is effectively improved and the average time and the average number of queries are reduced with the same attack success rate. © 2022 IEEE.

关键词： Learning algorithms

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 << < 430 431 432 433 434 435 436 437 438 439 > >>

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：