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

4,146 篇 会议
63 册 图书
20 篇 期刊文献

馆藏范围

4,229 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,282 篇 工学
- 2,670 篇 计算机科学与技术...
- 2,212 篇 软件工程
- 1,011 篇 信息与通信工程
- 529 篇 生物工程
- 404 篇 控制科学与工程
- 364 篇 生物医学工程（可授...
- 354 篇 电气工程
- 309 篇 光学工程
- 255 篇 电子科学与技术（可...
- 215 篇 安全科学与工程
- 194 篇 化学工程与技术
- 190 篇 仪器科学与技术
- 190 篇 交通运输工程
- 184 篇 动力工程及工程热...
- 180 篇 机械工程
- 161 篇 网络空间安全
1,689 篇 理学
- 756 篇 数学
- 566 篇 生物学
- 442 篇 物理学
- 279 篇 统计学（可授理学、...
- 273 篇 化学
- 151 篇 系统科学
1,025 篇 管理学
- 674 篇 图书情报与档案管...
- 540 篇 管理科学与工程(可...
- 282 篇 工商管理
286 篇 医学
- 271 篇 临床医学
- 267 篇 基础医学(可授医学...
- 196 篇 药学(可授医学、理...
180 篇 法学
- 129 篇 社会学
122 篇 农学
- 122 篇 作物学
104 篇 经济学
87 篇 教育学
11 篇 文学
10 篇 军事学
3 篇 艺术学

主题

110 篇 deep learning
104 篇 feature extracti...
92 篇 computer vision
73 篇 training
68 篇 accuracy
65 篇 computational mo...
65 篇 machine learning
59 篇 image processing
59 篇 artificial intel...
58 篇 data mining
57 篇 semantics
55 篇 convolutional ne...
54 篇 object detection
53 篇 computer archite...
53 篇 image segmentati...
52 篇 smart cities
49 篇 natural language...
48 篇 internet of thin...
46 篇 real-time system...
42 篇 big data

机构

15 篇 college of infor...
13 篇 school of comput...
13 篇 school of comput...
11 篇 department of co...
11 篇 xi'an university...
10 篇 key laboratory o...
10 篇 shanghai institu...
10 篇 school of inform...
9 篇 wuhan university...
9 篇 computer science...
9 篇 school of inform...
8 篇 college of compu...
8 篇 sri lanka instit...
8 篇 school of inform...
8 篇 school of inform...
8 篇 school of comput...
8 篇 peng cheng labor...
8 篇 xi'an shiyou uni...
8 篇 school of comput...
8 篇 college of compu...

作者

12 篇 wang peng
10 篇 mekruksavanich s...
9 篇 yingsong li
9 篇 temdee punnarumo...
9 篇 zhao hui
9 篇 li yingsong
9 篇 jitpattanakul an...
8 篇 gaol ford lumban
8 篇 li wei
7 篇 nikola zlatanov
7 篇 zhang chao
7 篇 wang chao
7 篇 li liping
7 篇 wang wei
7 篇 sun fuchun
7 篇 wang yang
7 篇 zlatanov nikola
7 篇 wang hao
7 篇 liping li
7 篇 zhang jian

语言

4,057 篇 英文
165 篇 其他
4 篇 中文
2 篇 俄文
2 篇 土耳其文

检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

共 4229 条记录，以下是781-790 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：

A Survey on Automated CAD System of Liver Tumor using US Images 7

A Survey on Automated CAD System of Liver Tumor using US Ima...

引用

7th international conference on Communication and Electronics Systems, ICCES 2022

作者： Uplaonkar, Deepak S. Virupakshappa Rangayya Patil, Nagabhushan International Institute of Information Technology Department of Information Technology Pune India Sharnbasva University Department of Computer Science and Engineering Kalburagi India Sharnbasva University Department of Elctronics and Telecommunication Engineering Kalburagi India Poojya Doddappa Appa College of Engineering Department of Electrical and Elctronics Engineering Kalburagi India

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

Visual analysis of human organs is currently one of the most active subjects under study in the field of computer vision. the ability of a machine to analyse human organs is a critical aspect in its development. Medical imaging is a procedure that allows clinicians to examine a part of the human body that is not naturally visible. In Medical Image processing, analysis and visualization application allows for quantitative analysis and visualization of a variety of medical imaging modalities. the objective of this survey is to present an overview of current computer-assisted diagnosis approaches for detecting tumor lesions using ultrasound images. Research papers published between 2019 and 2021 from various standard databases were considered in preparation for the survey. the paper initially discusses the various speckle reduction approaches on ultrasound images, then various segmentation approaches based on level set are discussed. Finally various approaches for discrete wavelet transformation-based feature extraction and neural network-based classification are also discussed. the review gives an insight on the work carried out so far for reduction of speckle noise in ultrasound image, level set-based segmentation methods, discrete wavelet transformation-based feature extraction methods and artificial neural network based classification methods. © 2022 IEEE.

关键词： Surveys

来源：评论

学校读者我要写书评

暂无评论

Adaptive detector and simulation analyses for range-spread target in structured interference plus noise 7

Adaptive detector and simulation analyses for range-spread t...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： He, Jia Jian, Tao Wei, Guangfen Huang, Xiaodong Zhang, Jian Naval Aviation University Research Institute of Information Fusion Shandong Yantai264001 China Shandong Technology and Business University School of Information and Electronic Engineering Shandong Yantai264000 China Naval Aviation University Aviation Service College Shandong Yantai264001 China Unit 91206 of Pla Shandong Qingdao266108 China

ISBN: (纸本)9781665478571

In this paper we consider the adaptive detection problem of range-spread targets embedded in structured interference plus white Gaussian noise. the target signal and interference are assumed to lie in two linearly independent subspaces with unknown coordinates. Aiming at the problem of range-spread target detection in structured interference, we design two detectors based to the criterion of Gradient test, for known or unknown noise power, respectively. Simulation results show that, compared with the existing detectors without considering interference, the proposed detectors exhibit better detection performance. Furthermore, the proposed detectors can reject the interference effectively. © 2022 IEEE.

关键词： Gaussian noise (electronic)

来源：评论

学校读者我要写书评

暂无评论

Enhanced style transfer with colorization and super-resolution 7

Enhanced style transfer with colorization and super-resoluti...

引用

7th international conference on Communication, Image and Signal processing, CCISP 2022

作者： Jinkua, Liu Chenxiang, Yang Abdalla, Hemn Barzan Wenzhou-Kean University Department of Computer Science Wenzhou China

ISBN: (数字)9781665459594

ISBN: (纸本)9781665459594

Style transfer is a novel and successful technology in the field of computer vision which allow people to create art pieces without training. this research has combined style transfer, colorization, and super-resolution algorithm to create a method to create art pieces from the black-white image as content and sketch art pieces as style with high resolution. this method could significantly lower the demand for art creation and allow people with little artistic skill to create desired artwork. Moreover, this research compares the impact of the different parameters in style transfer and the influence of the colorization in different processing stages resulting that colorizing the content image before style transfer would create a single style image that is more controllable but colorizing the generated image after style transfer would result in a more unpredictable multi-style image which depends on the training dataset of the image and the ratio of the weight in style transfer. © 2022 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Plant Disease Detection and Management Using Deep Learning Approach 7

Plant Disease Detection and Management Using Deep Learning A...

引用

7th international conference on Computing in Engineering and technology, ICCET 2022

作者： Kothawade, Prachi Varma, Satishkumar Gogate, Uttara Department of Computer Engineering School of Engineering and Applied Sciences Mumbai India Department of Information Technology Pillai College of Engineering Navi Mumbai India Department of Computer Engineering SSJCOE Mumbai India

ISBN: (纸本)9781839537042

Plant diseases impede the average growth of plants and are one of the main reasons behind the decline in production, leading to economic loss. Early detection of the diseases helps provide a cure that can restrict the spread of the diseases within the plant. this review provides a framework for classifying plants as diseased/healthy based on leaf health using various deep learning models such as ResNet50, InceptionV3, ResNet152V2, and AlexNet and implementing those models on two different datasets, namely cotton and plant village datasets, improved respective performance. the experimental results show that the proposed models for plant disease detection and management using ResNet50, InceptionV3, ResNet152V2, and AlexNet perform well to provide a feasible solution for predicting disease among various plant leaves. But with the use of ResNet152V2 as compared to other classifiers, which gives an accuracy of 100% on the cotton dataset and 94.32% with the plant village dataset in search of the healthy or diseased plant additional to that if detected leaves are diseased, the model provides information on each disease and feasible solution. the results demonstrate that the proposed prediction mechanism represents a new effective way to predict diseases with better accuracy. the models were deployed to a web application using a flask to give users a medium to interact and utilize the mechanism. © 2022 the Institution of Engineering and technology.

关键词： Cotton

来源：评论

学校读者我要写书评

暂无评论

Analyzing a Decade of Evolution: Trends in Natural Language processing 26th

Analyzing a Decade of Evolution: Trends in Natural Language ...

引用

26th international conference on Data Warehousing and Knowledge Discovery (DaWaK)

作者： Jonker, Richard A. A. Almeida, Tiago Matos, Sergio Univ Aveiro LASI IEETA DETI Aveiro Portugal

ISBN: (纸本)9783031683220;9783031683237

Natural Language processing (NLP) stands at the forefront of the rapidly evolving landscape of Machine Learning, witnessing the emergence and evolution of diverse methodologies over the past decade. this study delves into the dynamic trends within the NLP domain, specifically spanning the years 2010 to 2022, through an empirical analysis of papers presented at conferences hosted by the Association for Computational Linguistics (ACL). We utilize ChatGPT in order to extract meaningful information from the data before performing an in depth analysis. Our investigation encompasses an exploration of several key aspects, namely computational trends, research trends and geographic trends. We further investigate the entry cost into NLP, the longevity of hardware and the environmental impact of NLP. the code to run our system is publicly available at https://***/ieeta-pt/nlp-trends.

关键词： Data Analytics Natural Language processing Data Extraction NLP Trends

来源：评论

学校读者我要写书评

暂无评论

Enhancing IoT-Edge Computation with Data Forwarding based Decentralized Deep Neural Networks 7

Enhancing IoT-Edge Computation with Data Forwarding based De...

引用

7th international conference on Image information processing, ICIIP 2023

作者： Prasad, B.M.G. Jopate, Rachappa Savita, Pankaj Basi Reddy, A. Shankar, B. Prabu Arunkumar, M.S. Department of Cse Andhra Pradesh Kurnool518452 India University of Technology And Applied Sciences - Al Mussanah Department of Information Technology Al Muladha Muscat Oman Sagar Institute of Science & Technology Bhopal Organization-Sagar Institute of Science & Technology Department of Cse Madhya Pradesh Bhopal India Mohan Babu University School of Computing Department of Computer Science And Engineering Andhra Pradesh Tirupati India Alliance University Alliance College of Engineering And Design Department of Computer Science And Engineering Karnataka Banglore India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science And Technology Department of Computer Science And Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350371406

the incorporation of edge computing has become essential in the big data and Internet of things age to tackle issues related to latency, real-time processing, and data scale. this paper delves into the imperative need for edge computing within the context of big data environments. Distributed deep learning methodologies are explored, encompassing a diverse array of deep learning models. Particularly, a novel paradigm named Data Forwarding based Decentralized Deep Neural Network (DF-DDNN) is introduced to achieve low latency IoT-Edge computation. In order to reduce latency in Io T ecosystems, the DF-DDNN model makes use of edge devices' processing capabilities. By strategically distributing data processing and computation at the edge, this model seeks to overcome inherent limitations of conventional Io T architectures, with a keen focus on network, processing, and overall latencies. the research provides a thorough performance evaluation that compares the DF-DDNN model's performance versus conventional IoT models in a number of areas. the outcomes demonstrate how much better the suggested DF-DDNN model is than traditional IoT systems. Notably, improvements are evident in terms of reduced network latency, accelerated processing speeds, and overall latency mitigation. this research underscores the critical importance of embracing edge computing in the context of big data and deep learning applications. the DF-DDNN model emerges as a promising avenue for advancing IoT-Edge computation, effectively addressing latency concerns and augmenting the performance of IoT-enabled systems. © 2023 IEEE.

关键词： Edge computing

来源：评论

学校读者我要写书评

暂无评论

High-Automatical and High-Accurate Pupil Location Neural Network via FRST FPL 7

High-Automatical and High-Accurate Pupil Location Neural Net...

引用

7th international conference on Machine Vision and information technology, CMVIT 2023

作者： Ma, Hongwei Shen, Ran Ye, Jing Su, Huajun Xie, Hantian Jiang, Han Zhejiang Huayun Electric Power Enterprise Service Co. Ltd Chengbei Branch Hangzhou China State Grid Zhejiang Electric Power Co. Ltd Marketing Service Center Hangzhou China State Grid Zhejiang Electric Power Co. Ltd Kaihua Power Supply Company Quzhou China State Grid Zhejiang Electric Power Co. Ltd Jinhua Power Supply Company Jinhua China Zhejiang University College of Computer Science and Technology Hangzhou China

ISBN: (纸本)9781665464857

Pupil location refers to the location of the pupil or its center in an image. To solve the problem that the pupil location method is difficult to achieve high automation and high accuracy at the same time, this paper proposes a method combining image processing and statistical learning. In this paper, an improved algorithm of the fast radial symmetry transform (FRST) based on pupil location is proposed, namely FRSTFPL (fast radial symmetry transform for pupil location), which is used to coarsely localize the pupil in the image, followed by a shallow CNN to achieve precise localization. In addition, we construct a dataset based on the CASIA-IrisV4 iris image database and then conduct a variety of experiments. the results show that the location error of the proposed method in an image with a size of 640 × 480 pixels is 8.51 pixels, which exceeds the performance of the comparing methods. In our method, not only accurate radius and complex network are unnecessary, but also highly automated, low computational complexity, and relatively high localizing accuracy can be achieved together. © 2023 IEEE.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Generative and Attentive Fusion for Multi-spectral Vehicle Re-Identification 7

Generative and Attentive Fusion for Multi-spectral Vehicle R...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Guo, Jinbo Zhang, Xiaojing Liu, Zhengyi Wang, Yuan Anhui University School of Computer Science and Technology Hefei China Spic Digital Technology CO. LTD Beijing China

ISBN: (纸本)9781665478571

Vehicle re-identification (Re-ID) task has far-reaching practical application value and research significance in busy traffic monitoring scenes. Most existing works are based on the single RGB modality or RGB-IR (Infrared) cross-modality. Still, it is difficult to be widely applied in multi-scene real life because of the inadequacy of a single modality at the limited daytime. Recently, multi-spectral Re-ID has been proposed to simultaneously use the RGB and IR spectral data to build a data cell that can complement each other to deal with this condition. For multi-spectral vehicle Re-ID, existing methods simply fuse features extracted from a data cell with multiple modalities, which ignores the large gap as well as the relationship between different modalities. To address this problem, in this work, we propose the Generative and Attentive Fusion Network (GAFNet) to fuse the multiple data sources for the vehicle Re-ID task. First, at the input-level, we enrich the data cell by adding the generated transitional modality images, which could involve different data distribution from the original modality images. Note that the newly generated images have high similarity with both the target modality and the source modality, therefore they would help reduce the gap between modalities and indirectly improve the consistency inside a data cell, and further enhance the weight of key information. Second, at the feature-level, we concatenate and fuse the features of the original data and the transitional modalities from different dimensions with the proposed attentive feature fusion module to further align the features and enhance their focused areas in the feature maps. Extensive experimental results on two standard benchmarks demonstrate that our method is effective and outperforms the state-of-the-art methods. © 2022 IEEE.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Research on the motor fault diagnosis method based on feature engineering and machine learning 7

Research on the motor fault diagnosis method based on featur...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Ji, Dezheng Hu, Minfei Wang, Miao Hebei University of Technology School of Electrical Engineering Tianjin China Southwest University of Science and Technology School of Information Engineering Sichuan China Zhengzhou University of Aeronautics School of Aerospace Engineering Zhengzhou China

ISBN: (纸本)9781665478571

Bearing failure is the most common type of motor failure. Decision tree algorithm is a machine learning algorithm with the advantages of insensitivity to missing values and high efficiency. this research uses the bearing failure experimental data of the Bearing Data Center of Case Western Reserve University in the United States. the result shows that feature extraction of the data using time domain, frequency domain and wavelet singular entropy can effectively reduce the data dimensionality and improve the overall accuracy by about 41.1% and training time by 7.687 seconds compared with the original data without feature engineering. In addition, two algorithms, random forest feature selection and principal component analysis (PCA), were used for feature selection after feature extraction. the results after feature selection show that the combination of random forest feature selection algorithm and decision tree classification model improves the accuracy by 2.5%. And the model training time is reduced by 2.053s. this method is an effective fault diagnosis method for motor bearings, which can diagnose faults accurately and efficiently. © 2022 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Cascaded based Adaptive R-CNN Network for Insulator Defect Detection 23

Cascaded based Adaptive R-CNN Network for Insulator Defect D...

引用

23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Yao, Nan Shan, Guangrui Pan, Jianya Wang, Zhen Zhu, Xueqiong State Grid Jiangsu Electric Power Co. Ltd. Research Institute Nanjing210000 China

ISBN: (纸本)9781665494571

Target detection is a popular direction in computer vision and digital image processing. It is widely used in robot navigation, intelligent video surveillance, industrial detection, aerospace, and many other fields. It has important practical significance to reduce the consumption of human capital through computer vision. Due to the widespread use of deep learning, target detection algorithms have developed relatively rapidly. In this paper, we propose a method for detecting insulator defects Based on Cascaded Fast R-CNN. We use RoIAlign instead of RoIPooling to get a better positioning effect and add a mask branch on the basis of Faster R-CNN to complete the pixel-level segmentation task, which can detect insulator defects in real-time with high detection accuracy. © 2021 IEEE.

关键词： Image segmentation computer vision Service robots Navigation Failure analysis Object detection Insulators

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423页 << < 75 76 77 78 79 80 81 82 83 84 > >>

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：