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

283 篇 会议
41 册 图书
3 篇 期刊文献

馆藏范围

327 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

171 篇 工学
- 152 篇 计算机科学与技术...
- 93 篇 软件工程
- 47 篇 光学工程
- 35 篇 信息与通信工程
- 28 篇 生物工程
- 22 篇 电气工程
- 16 篇 控制科学与工程
- 9 篇 电子科学与技术（可...
- 8 篇 化学工程与技术
- 8 篇 生物医学工程（可授...
- 6 篇 网络空间安全
- 5 篇 机械工程
- 5 篇 安全科学与工程
- 3 篇 仪器科学与技术
- 3 篇 材料科学与工程（可...
- 3 篇 建筑学
- 3 篇 农业工程
78 篇 理学
- 48 篇 物理学
- 30 篇 生物学
- 25 篇 数学
- 11 篇 统计学（可授理学、...
- 8 篇 化学
21 篇 医学
- 16 篇 临床医学
- 4 篇 公共卫生与预防医...
- 3 篇 基础医学(可授医学...
- 3 篇 特种医学
18 篇 管理学
- 10 篇 管理科学与工程(可...
- 9 篇 图书情报与档案管...
- 5 篇 工商管理
4 篇 农学
- 4 篇 作物学
2 篇 法学
2 篇 教育学

主题

37 篇 computer vision
25 篇 image processing...
21 篇 artificial intel...
20 篇 pattern recognit...
20 篇 computer imaging...
17 篇 machine learning
14 篇 computer applica...
13 篇 computer systems...
12 篇 signal, image an...
11 篇 deep learning
8 篇 image processing
6 篇 computers and ed...
5 篇 vision transform...
5 篇 low-level vision
4 篇 image enhancemen...
4 篇 object detection
4 篇 cell microscopy
4 篇 image segmentati...
4 篇 graphics process...
4 篇 stereo image pro...

机构

17 篇 microsoft resear...
17 篇 microsoft res as...
12 篇 tsinghua univers...
7 篇 university of sc...
7 篇 univ sci & techn...
6 篇 national key lab...
6 篇 shanghai collabo...
6 篇 shanghai key lab...
5 篇 university of te...
5 篇 dalian universit...
5 篇 university of sy...
5 篇 institute of aut...
5 篇 shenzhen univers...
4 篇 key laboratory o...
4 篇 national enginee...
4 篇 university of ud...
4 篇 tsinghua univ pe...
4 篇 microsoft cloud ...
4 篇 university of yo...
4 篇 vision and image...

作者

8 篇 han hu
7 篇 hu han
6 篇 zuxuan wu
6 篇 min xu
5 篇 hui huang
5 篇 jing dong
5 篇 yu-gang jiang
5 篇 jiwen lu
5 篇 risheng liu
5 篇 wanli ouyang
5 篇 huchuan lu
4 篇 gian luca forest...
4 篇 qi dai
4 篇 zhiguo cao
4 篇 dongdong chen
4 篇 edwin hancock
4 篇 boxin shi
4 篇 jean-jacques rou...
4 篇 zheng zhang
4 篇 andrea fusiello

语言

322 篇 英文
5 篇 其他
3 篇 中文

检索条件"任意字段=2023 Asia Conference on Computer Vision, Image Processing and Pattern Recognition, CVIPPR 2023"

共 327 条记录，以下是81-90 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：

TIRec: Transformer-based Invoice Text recognition 23

TIRec: Transformer-based Invoice Text Recognition

引用

2nd asia conference on Algorithms, Computing and Machine Learning (CACML)

作者： Chen, Yanlan Beijing Univ Posts & Telecommun Sch Artificial Intelligence Beijing Peoples R China

ISBN: (纸本)9781450399449

A novel invoice text recognition model is proposed. In the past few years, researchers have explored text recognition methods with RNN-like structures to model semantic information. However, RNN-based approaches have some obvious drawbacks, such as the level-by-level decoding approach and the one-way serial transmission of semantic information, which greatly limit semantic information's effectiveness and computational efficiency. In contrast, invoice text has obvious contextual relationships due to its fixed text pattern, the text font in the invoice is more fixed and the complexity of the background is much lower than that of natural scenes. To further exploit these contextual relationships and adapt to the characteristics of invoice text, we propose a new text recognition framework inspired by Transformer [1]. Self-attention-based architectures, in particular Transformer, have been successful in natural language processing (NLP). It has demonstrated powerful semantic information modeling capabilities in NLP. Inspired by its success, we try to apply Transformer to invoice text recognition. Unlike the RNN-based approach, we reduce the parameters of the vision network used to extract image features, use the Convolutional vision Transformer Attention module to capture the semantic information, and use the Transformer decoding module to decode all characters in parallel. We hope that this Transformer-based architecture can better model the semantic information in invoices while remaining lightweight. Meanwhile, we collected text images of more than 40,000 train invoices, VAT invoices, rolled invoices, and cab invoices. Experiments on the collected invoice text recognition dataset show that our approach outperforms previous methods in terms of accuracy and speed.

关键词： Text recognition Invoice Convolutional vision Transformer

来源：评论

学校读者我要写书评

暂无评论

Intelligent medical waste detection and classification system based on machine vision

Intelligent medical waste detection and classification syste...

引用

2023 International conference on image, Signal processing, and pattern recognition, ISPP 2023

作者： Cai, Zhaoxin Bian, Tianhu Bai, Chunyu Li, Pengxu Sun, Changping School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781510666351

Since the global eruption of COVID-19, there have been issues with the global medical management system. The classification and treatment of medical waste has brought a huge burden to medical staff. Traditional manual classification has problems such as the heavy workload, difficult identification, and susceptibility to infection. This paper designs an intelligent medical waste detection and classification system based on machine vision. Based on deep learning models such as YOLOv5 and YOLO-resnet18, the data is trained and optimized to obtain a target detection model suitable for medical waste. Through experimental tests, the system has fast detection speed and high accuracy, and the accuracy of medical waste detection and classification reaches 90% and 99% respectively. © 2023 SPIE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Pyramid image defogging network based on attention fusion 6

Pyramid image defogging network based on attention fusion

引用

6th International conference on Artificial Intelligence and pattern recognition, AIPR 2023

作者： Meng, Caixia Gao, Yuxue Hou, Qin Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9798400707674

image information captured under foggy conditions is severely degraded, which has an impact on the performance of computer vision tasks. image defogging has become a critical problem in computer vision. Deep learning-based image defogging methods have made significant progress, but treating different features and pixels equally during deep convolution leads to incomplete defogging and loss of important feature information. Therefore, an end-to-end image defogging network is proposed. The pre-defogging module is first used to generate intermediate results, which contain clear structures, and the feature fusion stage is first learned using channel attention and pixel attention processing to give greater weights to the basic features. Finally the clear image is recovered by compressing the connections with the pyramid full residual module. Extensive experimental results show that the algorithm has good performance on widely used defogging benchmark datasets as well as on real haze images. © 2023 ACM.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

English and Spanish Bilinguals' Language processing: An ALE-Based Meta-analysis of Neuroimaging Studies 6th

English and Spanish Bilinguals' Language Processing: An ALE-...

引用

6th Chinese conference on pattern recognition and computer vision (PRCV)

作者： Liu, Linqiao He, Yan Zheng, Aoke Xian Int Studies Univ Coll English Studies Xian 710128 Peoples R China Xian Int Studies Univ Key Lab Artificial Intelligence & Cognit Neurosci Xian 710128 Peoples R China

ISBN: (纸本)9789819985395;9789819985401

The neural mechanisms underlying language processing in English and Spanish bilinguals remain a topic of intense investigation. No neuroimaging meta-analyses about English and Spanish bilinguals' language processing, nevertheless, appeared in the past. In this meta-analysis, Activation Likelihood Estimation (ALE) technique was used to synthesize findings from 13 neuroimaging studies of total 231 Spanish-English or English-Spanish bilinguals. Results showed that there existed 6 peaks in 4 activated brain regions during Spanish processing and 13 peaks in 11 activated brain regions during English processing. In addition, results revealed two distinct peaks of two brain regions commonly activated during language processing across both languages: right insula and left precentral gyrus which may become potential markers for individuals who are bilingual in both English and Spanish. In addition, we found no significant difference in activation between English and Spanish, indicating that these two languages may engage similar neural pathways during language processing.

关键词： Spanish English Bilinguals Meta-analysis ALE

来源：评论

学校读者我要写书评

暂无评论

The Effect of Variance-Based Patch Selection on No-Reference image Quality Assessment 6

The Effect of Variance-Based Patch Selection on No-Reference...

引用

6th International conference on pattern recognition and image Analysis (IPRIA)

作者： Hosseini-Benvidi, S. Farhad Mansouri, Azadeh Kharazmi Univ Dept Elect & Comp Engn Fac Engn Tehran Iran

ISBN: (纸本)9798350314557

The objective of the No-Reference image Quality Assessment (NR-IQA) is to evaluate the perceived image quality subjectively. Since there is no reference image, this is a challenging and unresolved issue. Convolutional neural networks (CNNs) have gained popularity in recent years and have outperformed many traditional techniques in the field of image processing. In order to overcome overfitting, a large percentage of deep learning based IQA methods work with tiny image patches and assess the quality of the entire image based on the average scores of patches. Patch extraction is one of the most crucial elements of CNN-based methods in quality assessment problems. Assuming that visual perception in humans is well suited to extract structural details from a scene, we analyzed the effect of feeding informative and structural patches to the quality framework. In this paper, a method for structural patch extraction is presented, which is based on the variance values of each patch. The obtained results show that the presented method has an acceptable improvement compared to the random patch selection. The proposed model has also performed well in cross-dataset experiments on common distortions, indicating the model's high generalizability. Additionally, the test was run on the flipped images, and the outcomes are satisfactory.

关键词： computer vision image quality assessment Deep learning

来源：评论

学校读者我要写书评

暂无评论

Proceedings - 2023 asia-Pacific conference on image processing, Electronics and computers, IPEC 2023

Proceedings - 2023 Asia-Pacific Conference on Image Processi...

引用

2023 asia-Pacific conference on image processing, Electronics and computers, IPEC 2023

ISBN: (纸本)9781665457033

The proceedings contain 86 papers. The topics discussed include: study of 6-pulse bridge rectification control strategy considering the influence of PID control parameters;research on automatic generation of social short text based on backtracking pattern;simulation of process decision model for die and mold parts based on BP neural network algorithm;multi-terminal optical fiber tuning method for distribution network relay protection based on reinforcement learning algorithm;design and implementation of HTML5-based mobile sales management system;an end-to-end convolutional neural network model for autonomous driving;design of embedded measurement and control system for aircraft maintenance simulator based on genetic algorithm;research on speech recognition algorithm based on embedded system architecture;monocular vision aided inertial positioning method based on centroid extraction applicable to GNSS denied environments;and a multi-core verification method of vector instructions based on spike.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on computer vision in Object Detection

Research on Computer Vision in Object Detection

引用

2022 International conference on Mathematics, Modeling, and computer Science, MMCS 2022

作者： Wei, Xiang Ren, Youli Huang, Mian Yunnan Land and Resources Vocational College Yunnan China

ISBN: (纸本)9781510664593

Object detection is a hot topic in the field of machine vision. In the innovation and development of modern technology, the integration of machine learning, pattern recognition, image processing and other multidisciplinary knowledge can effectively solve the image problem. In computer vision and digital image processing technology in the development of innovation, target detection theory research and practical application has achieved excellent results, although there are many problems need to solve, but a lot of new technology and new method has yet to be developed, so countries scholars gradually strengthen the scientific research strength, strong adaptability are put forword technique, high precision and good robustness. In this paper, based on the understanding of the research status of object detection, according to the basic theory of image processing, the application of computer vision in object detection is analyzed. The final experimental results show that shadow detection, image enhancement and filtering methods can effectively improve the application effect. © 2023 SPIE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Masked vision Transformers for Hyperspectral image Classification

Masked Vision Transformers for Hyperspectral Image Classific...

引用

2023 IEEE/CVF conference on computer vision and pattern recognition Workshops, CVPRW 2023

作者： Scheibenreif, Linus Mommert, Michael Borth, Damian University of St. Gallen Aiml Lab School of Computer Science Switzerland

ISBN: (纸本)9798350302493

Transformer architectures have become state-of-the-art models in computer vision and natural language processing. To a significant degree, their success can be attributed to self-supervised pre-training on large scale unlabeled datasets. This work investigates the use of self-supervised masked image reconstruction to advance transformer models for hyperspectral remote sensing imagery. To facilitate self-supervised pre-training, we build a large dataset of unlabeled hyperspectral observations from the EnMAP satellite and systematically investigate modifications of the vision transformer architecture to optimally leverage the characteristics of hyperspectral data. We find significant improvements in accuracy on different land cover classification tasks over both standard vision and sequence transformers using (i) blockwise patch embeddings, (ii) spatialspectral self-attention, (iii) spectral positional embeddings and (iv) masked self-supervised pre-training1. The resulting model outperforms standard transformer architectures by +5% accuracy on a labeled subset of our EnMAP data and by +15% on Houston2018 hyperspectral dataset, making it competitive with a strong 3D convolutional neural network baseline. In an ablation study on label-efficiency based on the Houston2018 dataset, self-supervised pre-training significantly improves transformer accuracy when little labeled training data is available. The self-supervised model outperforms randomly initialized transformers and the 3D convolutional neural network by +7-8% when only 0.1-10% of the training labels are available. © 2023 IEEE.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Application of Band Combination in Landslide Identification of Remote Sensing images Driven by Deep Learning 2

Application of Band Combination in Landslide Identification ...

引用

2nd International conference on image processing, computer vision and Machine Learning, ICICML 2023

作者： Yang, Tianyu Xu, Weijie Hua, Yu Chengdu University of Technology College of Computer Science and Cyber Security Oxford Brookes College Chengdu China

ISBN: (纸本)9798350331417

With the frequent occurrence of geological disasters, landslide identification has become an important research problem. In recent years, with the application and research of deep learning in the fields of computer vision and remote sensing image analysis, deep learning has become a popular method for landslide identification research because of its excellent feature extraction and pattern recognition capabilities. In this paper, we add new bands reflecting vegetation and water of landslide factors to the original bands of remote sensing image samples by linear combination of bands, and conduct two sets of comparison experiments on Unet and Swin-Unet to verify that adding band features can help improve landslide identification accuracy. The experimental results show that the experimental group with additional band features has a numerical improvement in landslide identification accuracy, with F1-score as the evaluation index, the Unet experimental group has a 2.29% improvement and the Swin-Unet experimental group has a 1.78% improvement. The results of this paper have implications for the subsequent application of bands combination of landslide factor features in remote sensing landslide identification driven by deep learning methods. © 2023 IEEE.

关键词： deep learning landslide identification linear combination of bands remote sensing

来源：评论

学校读者我要写书评

暂无评论

The Virtual Air Canvas Using image processing

The Virtual Air Canvas Using Image Processing

引用

2023 International conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Pavithra, K. Geetha, A. Chinnaiyan, R. Alliance University Department of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350317060

One of the most interesting and challenging research focuses on pattern recognition and image processing has emerged in recent days is writing in the air. In many different applications, it can improve the interface between a machine and a human and offers a substantial contribution to the development of automated operations. In the field of computer vision, object tracking is considered a key challenge. The method of analyzing a video usually consists of three primary steps: recognizing the object, tracking its movement from frame to frame, and finally evaluating its behavior. Choosing an adequate object representation, selecting tracking features, identifying objects, and tracking them are the four problems taken into consideration for object tracking. Object tracking algorithms are widely used in many real-world applications, including autonomous surveillance, video indexing, and vehicle navigation. This work exploits this gap by developing a motion-to-text converter that may be used as software for wearable intelligent devices that allow writing in the air. The proposed work acts as a recorder of rare gestures. computer vision will be utilized to track the finger's path. With the generated text, messages, emails, and other kinds of correspondence can all be sent. It will enable effective communication for the deaf. Keywords - object, emoji's, image color, camera © 2023 IEEE.

关键词： computer vision

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33页 << < 5 6 7 8 9 10 11 12 13 14 > >>

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：