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

1,620 篇 会议
14 册 图书
12 篇 期刊文献

馆藏范围

1,646 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,160 篇 工学
- 888 篇 计算机科学与技术...
- 587 篇 软件工程
- 313 篇 光学工程
- 270 篇 信息与通信工程
- 258 篇 电气工程
- 174 篇 生物工程
- 146 篇 控制科学与工程
- 119 篇 机械工程
- 107 篇 生物医学工程（可授...
- 56 篇 电子科学与技术（可...
- 48 篇 材料科学与工程（可...
- 48 篇 化学工程与技术
- 47 篇 安全科学与工程
- 37 篇 仪器科学与技术
- 35 篇 交通运输工程
- 23 篇 建筑学
- 23 篇 网络空间安全
543 篇 理学
- 340 篇 物理学
- 194 篇 数学
- 175 篇 生物学
- 57 篇 化学
- 57 篇 统计学（可授理学、...
206 篇 医学
- 195 篇 临床医学
- 60 篇 基础医学(可授医学...
- 45 篇 药学(可授医学、理...
- 23 篇 公共卫生与预防医...
172 篇 管理学
- 96 篇 管理科学与工程(可...
- 78 篇 图书情报与档案管...
- 31 篇 工商管理
28 篇 农学
- 28 篇 作物学
19 篇 法学
17 篇 经济学
7 篇 教育学
5 篇 军事学
1 篇 文学

主题

307 篇 computer vision
228 篇 image processing
102 篇 image segmentati...
92 篇 feature extracti...
70 篇 deep learning
50 篇 object detection
42 篇 cameras
39 篇 image edge detec...
35 篇 convolutional ne...
34 篇 visualization
34 篇 image recognitio...
32 篇 machine learning
32 篇 image reconstruc...
31 篇 neural networks
30 篇 image color anal...
28 篇 computational mo...
28 篇 shape
28 篇 training
26 篇 image analysis
25 篇 face recognition

机构

6 篇 university of ch...
5 篇 comput & inf sci...
5 篇 department of co...
4 篇 chitkara univers...
4 篇 image processing...
4 篇 beijing institut...
4 篇 college of compu...
3 篇 shanghai jiao to...
3 篇 dept of electr &...
3 篇 south china univ...
3 篇 inria sophia-ant...
3 篇 school of comput...
3 篇 department of ma...
3 篇 shenyang institu...
3 篇 department of co...
3 篇 school of electr...
3 篇 school of comput...
3 篇 college of compu...
3 篇 dept of control ...
3 篇 department of in...

作者

6 篇 andayani u.
5 篇 syahputra m.f.
5 篇 mohana
5 篇 siregar b.
4 篇 yang yang
4 篇 hassan ghassemia...
4 篇 li hui
4 篇 shohreh kasaei
4 篇 e.j. delp
3 篇 luo haibo
3 篇 paul joseph sure...
3 篇 wang wei
3 篇 wang qian
3 篇 ying liu
3 篇 maryam imani
3 篇 saurav sumeet
3 篇 weickert joachim
3 篇 muchtar m.a.
3 篇 xin wang
3 篇 aggarwal j.k.

语言

1,615 篇 英文
25 篇 其他
9 篇 中文
1 篇 德文
1 篇 土耳其文

检索条件"任意字段=3rd International Conference on Computer Vision and Image Processing, CVIP 2018"

共 1646 条记录，以下是441-450 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：

Enabling Text-Line Segmentation in Run-Length Encoded Handwritten Document image Using Entropy-Driven Incremental Learning 3rd

Enabling Text-Line Segmentation in Run-Length Encoded Handwr...

引用

3rd international conference on computer vision and image processing (cvip)

作者： Amarnath, R. Nagabhushan, P. Javed, Mohammed Univ Mysore Dept Studies Comp Sci Mysore Karnataka India Indian Inst Informat Technol Dept IT Allahabad Uttar Pradesh India

ISBN: (纸本)9789813290884;9789813290877

In today's digital era, archival and transmission of document images are generally carried out in a compressed form in order to avoid wastage of storage space and bandwidth. In the case of CCITT Group 3 and Group 4, the compressed representation is a stream of white and black pixel intensity values called runs, correspondingly indicating background and foreground regions of the document image. In this research paper, we propose a novel entropy-driven incremental learning technique that directly works on the compressed stream of runs, and subsequently facilitates text-line segmentation in handwritten document images using entropy and connected component analysis. Spatial Entropy Quantifier (SEQ) is extracted from the stream of runs based on a suitable window. Further, incremental entropy and connected component analysis are carried out thus separating text and non-text regions leading to automatic text-line segmentation. The proposed method is validated with the compressed dataset of handwritten document images and performance is reported.

关键词： Compressed document Compressed stream CCITT Group 3 Group 4 Entropy Incremental learning Text-line segmentation

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Framework for Detection of an Illicit Drug Abuser Using Facial image 3rd

Deep Learning Framework for Detection of an Illicit Drug Abu...

引用

3rd international conference on computer vision and image processing (cvip)

作者： Gupta, Tanu Goyal, Meghna Kumar, Goutam Raman, Balasubramanian Indian Inst Technol Roorkee Roorkee Uttar Pradesh India

ISBN: (纸本)9789813290884;9789813290877

The detection of an illicit drug abuser by analyzing the subject's facial image has been an active topic in the field of machine learning research. The big question here is up to what extent and with what accuracy can a computer model help us to identify if a person is an illicit drug abuser only by analyzing the subject's facial image. The main objective of this paper is to propose a framework which can identify an illicit drug abuser just by giving an image of the subject as an input. The paper proposes a framework which relies on Deep Convolutional Neural Network (DCNN) in combination with Support Vector Machine (SVM) classifier for detecting an illicit drug abuser's face. We have created dataset consisting of 221 illicit drug abusers' facial images which present various expressions, aging effects, and orientations. We have taken random 221 non-abusers' facial images from available dataset named as, Labeled Faces in the Wild (LFW). The experiments are performed using both datasets to attain the objective. The proposed model can predict if the person in an image is an illicit drug abuser or not with an accuracy of 98.5%. The final results show the importance of the proposed model by comparing the accuracies obtained in the experiments performed.

关键词： Deep learning Convolutional neural network Face recognition

来源：评论

学校读者我要写书评

暂无评论

On Real-Time Object Recognition by Single image Dehazing Method Using Deep Learning Approach

On Real-Time Object Recognition by Single Image Dehazing Met...

引用

Advancement in Electronics & Communication Engineering (AECE), international conference on

作者： Shruti Pathak Amit Doegar Department of Computer Science National Institute of Technical Teachers Training and Research Chandigarh India

In the past decade, various haze removal techniques have been widely reported for object recognition. But hitherto little has been identified on the use of single image dehazing using transfer learning approach for object detection. Single image dehazing is an emerging computer vision technology which offers some of the extreme benefits over the existing techniques such as consumes less processing time, requires less space for real time dehaze purpose, etc. In this study, we combine both the object detection and image dehazing methods for real time applications such as-remote sensing, video surveillances, driverless automatic vehicles, etc. This paper presents an effective and efficient image dehazing method using transfer learning which helps to recognize objects in real time with more clarity and that can automatically detect objects with a high recognition rate and lesser probability of error. Our tests show that object detection becomes less accurate as the haze intensity increases; yet, under all haze circumstances (low, medium, or heavy), our jointly trained model AOD-net +YOLO v3 consistently outperforms non-joint and naïve YOLO v3 techniques.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards Mask-robust Face Recognition 18

Towards Mask-robust Face Recognition

引用

18th IEEE/CVF international conference on computer vision (ICCV)

作者： Feng, Tao Xu, Liangpeng Yuan, Hangjie Zhao, Yongfei Tang, Mingqian Wang, Mang Alibaba Grp Hangzhou Peoples R China Zhejiang Univ Hangzhou Peoples R China

ISBN: (纸本)9781665401913

In this paper, we focus on the problem of mask-robust face recognition. Facial mask usually covers a major part of face, causing a significant reduction in extracting effective features. Due to such restriction, even the most advanced face recognition models are confronted with significant challenges. In light of this, this paper attempts to provide a reliable solution. Specifically, we introduce a maskto-face image blending approach based on UV texture mapping, and a self-learning based cleaning pipeline for processing noisy training datasets. Then, considering the impacts of the long-tail distribution and hard faces samples, a loss function named Balanced Curricular Loss is introduced. Together with a bag of tricks is briefly presented. Experimental results show that the proposed solution separately achieved 84.528% @ Mask and 88.355% @ MR-ALL in InsightFace ms1m Track, which ranks 3rd when the paper submitted.

关键词： Training computer vision Face recognition conferences Computational modeling Pipelines Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Investigating Salient Object Detection Methods Tailored for Edge Computing Infrastructure 3rd

Investigating Salient Object Detection Methods Tailored for...

引用

3rd international conference on Computing, Communication and Learning, CoCoLe 2024

作者： Sebastian, Elsa Martin, John Paul Department of Computer Science and Engineering Indian Institute of Information Technology Kottayam Kottayam686635 India

ISBN: (纸本)9783031790409

Salient object detection aims in identifying the most significant parts of a scene as viewed by the human eye and plays a vital role in a variety of applications, including object detection, video compression, and augmented reality. Saliency detection has emerged as a fundamental preprocessing step in many computer vision and image processing tasks. Implementing saliency detection in edge computing platforms is challenging, however it promises enhanced real-time responsiveness, reduced bandwidth usage, and improved privacy. This paper examines the most advanced techniques for adapting saliency detection techniques to edge computing and discusses encountered challenges. The paper also gives insights into the evaluation metrics that can be utilized for performance assessment, investigates primary application domain and proposes potential directions for future research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Face Anti-spoofing Based on Specular Feature Projections 3rd

Face Anti-spoofing Based on Specular Feature Projections

引用

3rd international conference on computer vision and image processing (cvip)

作者： Katika, Balaji Rao Karthik, Kannan Indian Inst Technol Guwahati Dept Elect & Elect Engn Gauhati 781039 Assam India

ISBN: (纸本)9789813290884;9789813290877

The need for facial anti-spoofing has emerged to counter the usage of facial prosthetics and other forms of spoofing at unmanned surveillance stations. While some part of literature recognizes the difference in texture associated with a prosthetic in comparison with a genuine face, the solutions presented are largely prosthetic model specific and rely on two-sided calibration and training. In this paper, we focus on the specular component associated with genuine faces and claim that on account of the natural depth variation, its feature diversity is expected to be much larger as compared to prosthetics or even printed photo impersonations. In our work concerning one-sided calibration, we first characterize the specular feature space corresponding to genuine images and learn the projections of genuine and spoof data onto this basis. The trained SVM corresponding to genuine projections, 3D mask projections, and printed photo projections is then used as an anti-spoofing model for detecting impersonations.

关键词： Face Anti-spoofing Specular feature Eigenspace Printed photos 3D Mask Low-rank component Sparse component SVM classifier

来源：评论

学校读者我要写书评

暂无评论

A Rapid image Semantic Segment Method Based on Deeplab V3+ 3rd

A Rapid Image Semantic Segment Method Based on Deeplab V3+

引用

3rd international conference on Artificial Intelligence, 2022

作者： Zhang, Hailong Luo, Hanwu Li, Wenzhen Qin, Ruofeng Wuhan NARI Limited Liability Company State Grid Electric Power Research Institute Wuhan China East Inner Mongolia Electric Power Co. Ltd. Erdos China

ISBN: (纸本)9789811694226

As one of research directions in the fields of image processing and computer vision, image semantic segmentation classifies images by pixel for semantic comprehension. Due to the lack of a general theory of segmentation, conventional image semantic segmentation algorithms are mostly on the strength of specific image models, so a variety of methods develope with their respective range for using and relative merits. What’s more, it’s a pity that most of them can only use the underlying features to generate simple segmentation results of foreground and background. Since the breakthrough in deep learning at the imageNet competition in 2012, convolutional neural networks have taken every field of computer vision by storm. image semantic segmentation has broken through the limits of traditional methods rapidly after the integration of deep learning. After making use of convolutional neural networks, its accuracy for segmentation has been improved effectively so that image semantic segmentation at present can further meet the requirements of segmentation technology in different application scenarios. In recent years, it has developed rapidly and gradually become a research hotspot. This paper mainly studies the image semantic segmentation methods about Deeplab series based on deep learning and raises a lightweight model for semantic segmentation based on Deeplab v3+. Regarding MobileNet as backbone to extract features, it makes use of atrous spatial pyramid pooing to gain global multi-scale features. Then the decoder structure concatenates multi-scale features and low-level features to enhance the expression for spatial features and improve its performance. After sufficient experiments on PASCAL VOC using the fast semantic segmentation model, the result reveals that it obtains a good balance between accuracy and speed. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Diagnosis and Degree of Evolution in a Keratoconus-Type Corneal Ectasia from image processing 3rd

Diagnosis and Degree of Evolution in a Keratoconus-Type Corn...

引用

3rd international conference on Smart Technologies, Systems and Applications, SmartTech-IC 2022

作者： Otuna-Hernández, Diego Espinoza-Castro, Leslie Yánez-Contreras, Paula Villalba-Meneses, Fernando Cadena-Morejón, Carolina Guevara, César Cruz-Varela, Jonathan Tirado-Espín, Andrés Almeida-Galárraga, Diego School of Biological Sciences and Engineering Universidad Yachay Tech San Miguel de Urcuquí Urcuqui100119 Ecuador Department of Human Development Universidad Yachay Tech San Miguel de Urcuquí Urcuqui100119 Ecuador Centro de Mecatrónica y Sistemas Interactivos - MIST Universidad Indoamérica Quito Ecuador Instituto de Ciencias Matemáticas ICMAT-CSIC Madrid28049 Spain Universidad de Otavalo Av. De los Sarances y Av. Los Pendoneros Otavalo Ecuador Facultad de Ingeniería - Sistemas de Información Pontificia Universidad Católica del Ecuador Quito Ecuador

ISBN: (纸本)9783031322129

Keratoconus is a degenerative ocular pathology characterized by the thinning of the cornea, thus affecting many people around the world since this corneal ectasia causes a deformation of the corneal curvature that leads to astigmatism and, in more severe cases, to blindness. Treating physicians use non-invasive instruments, such is the case of Pentacam®, which takes images of the cornea, both the topography and the profile of the cornea, which allows them to diagnose, evaluate and treat this disease;this is known as morphological characterization of the cornea. On the other hand, Berlin/Ambrosio analysis helps in the identification and subsequent diagnosis since this analysis uses a mathematical model of linear progression, which identifies the different curves with the severity of the disease. Therefore, the aim of this study is to use the images provided by Pentacam®, Berlin/Ambrosio analysis, and vision parameters in a convolutional neural network to evaluate if this disparity could be used to help with the diagnosis of keratoconus and, consequently, generate a more precise and optimal method in the diagnosis of keratoconus. As a result, the processing and comparison of the images and the parameters allowed a 10% increase in the results of specificity and sensitivity of the mean and severe stages when combining tools (corneal profile and vision parameters) in the CNN reaching ranges of 90 to 95%. Furthermore, it is important to highlight that in the early-stage study, its improvement was around 20% in specificity, sensitivity, and accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Automated Denoising of Diabetic Retinopathy images for Enhanced Medical Diagnosis

Automated Denoising of Diabetic Retinopathy Images for Enhan...

引用

Applied Artificial Intelligence and Computing (ICAAIC), international conference on

作者： G.V. Suresh Gokavarapu Pavani Naga Pranathi Sri Krishna Sai Angidi Tumma Sai Dheeraj Goda Naga Venkata Snehitha Department of Computer Science and Engineering Lakireddy Bali Reddy College of Engineering(Autonomous) Mylavaram India

ISBN: (数字)9798350375190

ISBN: (纸本)9798350375206

Globally, diabetic retinopathy (DR) continues to be a major cause of vision impairment. Early diagnosis and detection of DR are essential to preventing blindness and vision loss. But the traditional manual method of screening retinal pictures takes a lot of time and is prone to human mistake. Using image processing to apply automated denoising techniques can increase image quality, make DR lesions more visible, and help with correct diagnosis. In order to improve the quality of images of diabetic retinopathy, this study investigates the ability of four image denoising filters: guided image filtering, Gaussian-bilateral filtering, Gabor filtering, and Haar Wavelet filtering. AGAR300 (IEEE DataPort), Diabetic Retinopathy Detection, Stare, Indian Diabetic Retinopathy image Dataset, and APTOS 2019 Blindness Detection are the five datasets used to evaluate the efficacy of these filters. The findings demonstrate that noise in DR images may be efficiently reduced by all four filters. The one that shows the biggest overall improvement in lesion visibility and image quality among them is guided image filtering.

关键词： image quality Diabetic retinopathy Noise reduction Visual impairment Blindness Feature extraction Retina

来源：评论

学校读者我要写书评

暂无评论

Research on image Caption Based on Multiple Word Embedding Representations 3

Research on Image Caption Based on Multiple Word Embedding R...

引用

3rd international conference on Natural Language processing, ICNLP 2021

作者： Lin, Zhen-Xian Qu, Jia-Xin Yang, Xiao-Bao Hou, Zhi-Qiang Ding, Chen Xi'An University of Posts and Telecommunications School of Science Xi'an China Xi'An University of Posts and Telecommunications School of Telecommunication and Information Engineering Xi'an China Northwestern Polytechnical University School of Computer Science and Technology Xi'an China Xi'An University of Posts and Telecommunications Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Shaanxi Xi'an China

ISBN: (纸本)9781665414111

Word embedding representation has been a research hot spot in the field of computer vision and natural language processing. The semantic quality of representation severely affects the effects of machine translation and image caption. The key factors affecting the quality of word embedding representation are capture of contextual semantics and solution of the problem of polysemy. In this paper, the principles of the current mainstream word embedding representation methods were explored, such as sparse representation (One-Hot), static representation (Word2Vec, GloVe), dynamic representation (ELMo, BERT) representation and based on position information (***-Position Embedding). The impact of those word embedding representations on image caption task was researched attentively. And those representations methods were compared experimentally using the MSCOCO data based on the same image caption model. The pros and cons of these methods were judged according to the accuracy and richness of the extracted label data. Experimental results show that the BERT model representation with dynamic bidirectional semantics has the best performance in image caption tasks, but it requires longer training time. The *** representation has the second best image semantic description effect, and its training speed is the fastest. © 2021 IEEE.

关键词： Embeddings

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165页 << < 41 42 43 44 45 46 47 48 49 50 > >>

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：