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

1,343 篇 会议
46 册 图书
18 篇 期刊文献

馆藏范围

1,407 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,046 篇 工学
- 738 篇 计算机科学与技术...
- 388 篇 软件工程
- 236 篇 电气工程
- 209 篇 信息与通信工程
- 191 篇 光学工程
- 127 篇 机械工程
- 109 篇 生物工程
- 96 篇 生物医学工程（可授...
- 89 篇 控制科学与工程
- 58 篇 电子科学与技术（可...
- 40 篇 化学工程与技术
- 28 篇 仪器科学与技术
- 23 篇 安全科学与工程
- 21 篇 交通运输工程
- 16 篇 材料科学与工程（可...
- 16 篇 土木工程
- 14 篇 建筑学
399 篇 理学
- 218 篇 物理学
- 155 篇 数学
- 119 篇 生物学
- 46 篇 统计学（可授理学、...
- 37 篇 化学
- 27 篇 系统科学
135 篇 医学
- 131 篇 临床医学
- 47 篇 基础医学(可授医学...
- 41 篇 药学(可授医学、理...
101 篇 管理学
- 56 篇 图书情报与档案管...
- 47 篇 管理科学与工程(可...
- 19 篇 工商管理
17 篇 农学
- 16 篇 作物学
11 篇 法学
6 篇 教育学
5 篇 经济学
4 篇 文学
1 篇 艺术学

主题

257 篇 computer vision
125 篇 image processing
122 篇 image segmentati...
93 篇 feature extracti...
83 篇 cameras
61 篇 image color anal...
41 篇 image edge detec...
41 篇 training
39 篇 deep learning
35 篇 three-dimensiona...
33 篇 image enhancemen...
32 篇 image reconstruc...
31 篇 images
29 篇 artificial intel...
28 篇 robustness
27 篇 object detection
27 篇 machine learning
25 篇 neural networks
24 篇 computational mo...
24 篇 pattern recognit...

机构

20 篇 computer vision ...
5 篇 indian statistic...
5 篇 indian institute...
5 篇 indian institute...
5 篇 department of co...
5 篇 computer vision ...
4 篇 techno india uni...
4 篇 department of co...
4 篇 jadavpur univers...
4 篇 department of ma...
4 篇 department of co...
4 篇 department of co...
4 篇 department of co...
3 篇 kentucky imaging...
3 篇 icteam universit...
3 篇 hong kong polyte...
3 篇 department of el...
3 篇 department of ma...
3 篇 indian institute...
3 篇 department of el...

作者

17 篇 raman balasubram...
11 篇 aly a. farag
9 篇 roy partha prati...
8 篇 balasubramanian ...
8 篇 a.a. farag
7 篇 dubey shiv ram
6 篇 arivazhagan s.
6 篇 shekar b.h.
6 篇 mishra deepak
5 篇 bhuyan m.k.
5 篇 lee hyo jong
5 篇 murala subrahman...
5 篇 chaudhuri bidyut...
5 篇 dorit merhof
5 篇 kumar sanjeev
5 篇 nain neeta
5 篇 jawahar c.v.
4 篇 asem ali
4 篇 nagabhushan p.
4 篇 ojha aparajita

语言

1,393 篇 英文
9 篇 中文
3 篇 俄文
2 篇 其他

检索条件"任意字段=International Conference on Computer Vision and Image Processing, CVIP 2016"

共 1407 条记录，以下是181-190 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：

RingFIR: A Large Volume Earring Dataset for Fashion image Retrieval 1

引用

5th international conference on computer vision and image processing, cvip 2020

作者： Islam, Sk Maidul Joardar, Subhankar Sekh, Arif Ahmed Global Institute of Science and Technology Purba Medinipur India Haldia Institute of Technology Purba Medinipur India UiT The Arctic University of Norway Tromsø Norway

ISBN: (数字)9789811610929

ISBN: (纸本)9789811610912

Fashion image retrieval (FIR) is a challenging task, which involves similar item searching from a massive collection of fashion products based on a query image. FIR in different garments and shoes are popular in literature. More complex fashion products such as ornaments are getting less attention. Here, we introduce a new earring dataset, namely, RingFIR. The dataset is a collection of (∼ 2.6K) high-quality images collected from major India based jewellery chains. The dataset is labelled in 46 classes in a structured manner. We have benchmarked the dataset using state-of-the-art image retrieval methods. We believe that the dataset is challenging and will attract computer vision researchers in the future. The dataset is available publicly (https://***/skarifahmed/RingFIR ). © 2021, Springer Nature Singapore Pte Ltd.

关键词： image retrieval

来源：评论

学校读者我要写书评

暂无评论

RANK-CONSTRAINED PCA FOR INTRINSIC imageS DECOMPOSITION 23

RANK-CONSTRAINED PCA FOR INTRINSIC IMAGES DECOMPOSITION

引用

23rd IEEE international conference on image processing (ICIP)

作者： Yu, Jinze Univ Tokyo Inst Ind Sci Tokyo Japan

ISBN: (纸本)9781467399616

Intrinsic image decomposition is an important topic in computer vision and computer graphics applications. However, this is a challenging problem by adopting the information of a single image. Therefore, additional priors or supplementary information such as multiply images or user interactions are necessary to address this problem. In this paper, we propose a novel scheme to use multiple images for intrinsic image decomposition, based on a similar strategy in robust principal component analysis (RPCA). RPCA utilizes the fact that the reflectance layer is common in multiple lights of a scene, and attempts to decompose the data matrix constructed from input images into a low-rank matrix and a sparse matrix. This is possible if the sparse matrix is sufficiently sparse, which is often not the case in computer vision applications. Moreover, the weighting parameter between the low-rank and sparse matrices greatly affects the accuracy of the results, and tuning this parameter can be tricky. This paper proposes a rank-constrained PCA algorithm (RCPCA) for solving background recovering problems. Fixing the rank of the low-rank matrix to be 1 allows RCPCA to better recover the low-rank matrix from the data matrix. Comprehensive tests show that RCPCA produces more stable and accurate results than RP CA.

关键词： Low-rank Intrinsic image decomposition Robust PCA Rank-constraint

来源：评论

学校读者我要写书评

暂无评论

GAN-Based Super-Resolution for Disease Detection in Aerial images: A Case Study of Potato Crop 8th

GAN-Based Super-Resolution for Disease Detection in Aerial I...

引用

8th international conference on computer vision and image processing (cvip)

作者： Pankaj, Anil Yeturu, Kalidas Badarla, Venkataramana Indian Inst Technol Tirupati Dept Comp Sci & Engn Tirupati Andhra Pradesh India

ISBN: (纸本)9783031581731;9783031581748

Precision agriculture requires high-resolution images to monitor crop growth and health effects. However, capturing such images from aerial platforms faces challenges due to altitude, motion blur, and limited resolution. Early detection and identification of these diseases can help prevent their spread and minimize the impact on crop yields. To address the challenge of capturing high-quality images, this paper relies on the new degradation model BSRGAN to enhance low-resolution aerial images of potato crops, initially sized at 750x750, to a higher resolution of 3000x3000. The experimental results indicate that the proposed BSRGAN method surpasses existing super-resolution techniques in terms of visual quality. The study utilizes the Potato Multispectral images Dataset, which has dimensions of 750 x 750. Interpolation methods are then applied to enhance the resolution, resulting in a high super-resolution dataset with dimensions of 3000 x 3000. Subsequently, the dataset is labeled using the publicly available tool *** (***: https:// ***/***), based on three categories of crop health: (a) Healthy, (b) Potato Leafroll Virus (PLRV), and (c) Verticillium wilt, as specified by the Potato Disease Identification, Agriculture, and Horticulture Development Board 2023 (AHDB). After labeling the data, we use You Only Look Once version 8 (YOLOv8) for potato crop health detection on the high-resolution dataset with dimensions of 3000x3000. The YOLOv8 algorithm has been trained on a high super-resolution dataset for object detection and classification. It achieves an impressive mAP better than without super-resolution of over 73%, specifically for healthy potato leaves, with an overall mAP of 56% across all three categories. These findings demonstrate the potential of deep learning based approaches to accurately and efficiently identify potato leaf diseases, empowering farmers to protect their crops.

关键词： Generative adversarial networks ESRGAN BSRGAN Precision agriculture Unmanned aerial vehicle computer vision

来源：评论

学校读者我要写书评

暂无评论

Reassigned time frequency distribution based face recognition

Reassigned time frequency distribution based face recognitio...

引用

international conference on computer vision and image processing, cvip 2016

作者： Shekar, B.H. Rajesh, D.S. Department of Computer Science Mangalore University MangalagangothriKarnataka574199 India

ISBN: (纸本)9789811021060

In this work, we have designed a local descriptor based on the reassigned Stankovic time frequency distribution. The Stankovic distribution is one of the improved extensions of the well knownWignerWille distribution. The reassignment of the Stankovic distribution allows us to obtain a more resolute distribution and hence is used to describe the region of interest in a better manner. The suitability of Stankovic distribution to describe the regions of interest is studied by considering face recognition problem. For a given face image, we have obtained key points using box filter response scale space and scale dependent regions around these key points are represented using the reassigned Stankovic time frequency distribution. Our experiments on the ORL, UMIST and YALE-B face image datasets have shown the suitability of the proposed descriptor for face recognition problem. © Springer Science+Business Media Singapore 2017.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

image aesthetics assessment using multi channel convolutional neural networks 4th

Image aesthetics assessment using multi channel convolutiona...

引用

4th international conference on computer vision and image processing, cvip 2019

作者： Doshi, Nishi Shikkenawis, Gitam Mitra, Suman K. Dhirubhai Ambani Institute of Information and Communication Technology Gandhinagar India C R Rao Advanced Institute of Mathematics Statistics and Computer Science Hyderabad India

ISBN: (纸本)9789811540172

image Aesthetics Assessment is one of the emerging domains in research. The domain deals with classification of images into categories depending on the basis of how pleasant they are for the users to watch. In this article, the focus is on categorizing the images in high quality and low quality image. Deep convolutional neural networks are used to classify the images. Instead of using just the raw image as input, different crops and saliency maps of the images are also used, as input to the proposed multi channel CNN architecture. The experiments reported on widely used AVA database show improvement in the aesthetic assessment performance over existing approaches. © Springer Nature Singapore Pte Ltd 2020.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Homogeneous and Non-homogeneous image Dehazing Using Deep Neural Network 6th

Homogeneous and Non-homogeneous Image Dehazing Using Deep N...

引用

6th international conference on computer vision and image processing, cvip 2021

作者： Gajjar, Manan Mandal, Srimanta DA-IICT Gujarat Gandhinagar India

ISBN: (纸本)9783031113451

Haze poses challenges in many vision-related applications. Thus, dehazing an image becomes popular among vision researchers. Available methods use various priors, deep learning models, or a combination of both to get plausible dehazing solutions. This paper reviews some recent advancements and their results on both homogeneous and non-homogeneous haze datasets. Intending to achieve haze removal for both types of haze, we propose a new architecture, developed on a convolutional neural network (CNN). The network is developed based on reformulating the atmospheric scattering phenomenon and estimating haze density to extract features for both types of haze. The haze-density estimation is supplemented by channel attention and pixel attention modules. The model is trained on perceptual loss. The quantitative and qualitative results demonstrate the efficacy of our approach on homogeneous as well as non-homogeneous haze as compared to the existing methods, developed for a particular type. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

An overview of image matching algorithms from two radically points of view 2

An overview of image matching algorithms from two radically ...

引用

2nd international conference on image processing, Applications and Systems (IPAS)

作者： Dhouha, Bannour Khaled, Kaaniche Hassen, Mekki Univ Sfax Natl Sch Engn Sfax CEM Lab Sfax Tunisia Univ Sousse Natl Sch Engineers Sousse Sousse Tunisia

ISBN: (纸本)9781509016457

This paper presents a study on the exploitation of visual information from two points of view radically different. computer vision is a branch of artificial intelligence that focuses on the extraction of useful information in an image. image matching is a fundamental aspect of many problems in computer vision. Several algorithms have been developed for this purpose. Based on this research, this paper present all the previous work reviewed.

关键词： image matching features dectection features extraction two radcally different points of view

来源：评论

学校读者我要写书评

暂无评论

Degraded Document image Binarization Using Active Contour Model 1

引用

5th international conference on computer vision and image processing, cvip 2020

作者： Gupta, Deepika Bag, Soumen Dhanbad826004 India

ISBN: (数字)9789811610929

ISBN: (纸本)9789811610912

Document image binarization separates the foreground from background which is a very crucial pre-processing step in OCR. Accuracy of binarization immensely influences the accuracy of OCR. Various degradations like inadequate illumination, complex background, ink bleed, smear, etc. make binarization a challenging exercise. In this paper, we propose a novel method for binarization based on Active Contour Model (ACM) which is different from current thresholding techniques. Instead of calculating a global or local threshold value, it uses the energy-minimization concept of ACM to accomplish binarization. Background of the document image is estimated adaptively and then removed to handle noises in degraded documents. Active contour model is then applied to the image to get the binary output. Comprehensive experimentation has been completed effectively with benchmark DIBCO series datasets. A comparison with other existing methods verifies the efficiency of the proposed method. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Active contour model DIBCO Document image binarization Hybrid thresholding OCR

来源：评论

学校读者我要写书评

暂无评论

Narrowing the semantic gap between real and synthetic data 16

Narrowing the semantic gap between real and synthetic data

引用

IEEE 16th international conference on Intelligent computer Communication and processing (ICCP)

作者： Beche, Radu Nedevschi, Sergiu Tech Univ Cluj Napoca Cluj Napoca Romania

ISBN: (纸本)9781728190808

image-to-image translation is an emerging method of computer vision dataset augmentation, which allows transferring the style of real life images onto synthetic ones, making them more realistic. In our work we propose an incremental improvement over the adversarial learning generator architectures used by image-to-image translation models. First, we managed to use a single network, instead of 2, thus creating a more memory-efficient model, which allowed for an end-to-end training on high resolutions. Second, inspired from recent work on semantic segmentation architectures, we enhanced our model by implying a multi-scale encoding and stylization phase, allowing for a better control over the contextual and spatial features. Given a synthetic image, our framework allows for its mullimodal translation into the real domain. Our model shows promising results at narrowing the semantic gap between synthetic and real data.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Posture recognition in HINE exercises

Posture recognition in HINE exercises

引用

international conference on computer vision and image processing, cvip 2016

作者： Ansari, Abdul Fatir Roy, Partha Pratim Dogra, Debi Prosad Department of Civil Engineering IIT Roorkee Roorkee247667 India Department of Computer Science & Engineering IIT Roorkee Roorkee247667 India School of Electrical Sciences IIT Bhubaneswar Bhubaneswar751013 India

ISBN: (纸本)9789811021060

Pattern recognition, image and video processing based automatic or semi-automatic methodologies are widely used in healthcare services. Especially, image and video guided systems have successfully replaced various medical processes including physical examinations of the patients, analyzing physiological and bio-mechanical parameters, etc. Such systems are becoming popular because of their robustness and acceptability amongst the healthcare community. In this paper, we present an efficient way of infant’s posture recognition in a given video sequence of Hammersmith Infant Neurological Examinations (HINE). Our proposed methodology can be considered as a step forward in the process of automating HINE tests through computer assisted tools. We have tested our methodology with a large set of HINE videos recorded at the neuro-development clinic of hospital. It has been found that the proposed methodology can successfully classify the postures of infants with an accuracy of 78.26 %. © Springer Science+Business Media Singapore 2017.

关键词： Hidden Markov models

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141页 << < 15 16 17 18 19 20 21 22 23 24 > >>

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：