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

920 篇 会议
61 册 图书
23 篇 期刊文献

馆藏范围

1,004 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

821 篇 工学
- 719 篇 计算机科学与技术...
- 375 篇 软件工程
- 336 篇 电气工程
- 108 篇 信息与通信工程
- 105 篇 光学工程
- 91 篇 生物工程
- 54 篇 生物医学工程（可授...
- 41 篇 电子科学与技术（可...
- 35 篇 化学工程与技术
- 28 篇 控制科学与工程
- 21 篇 机械工程
- 15 篇 安全科学与工程
- 12 篇 仪器科学与技术
- 10 篇 土木工程
- 8 篇 建筑学
- 8 篇 航空宇航科学与技...
- 7 篇 交通运输工程
280 篇 理学
- 126 篇 物理学
- 118 篇 数学
- 94 篇 生物学
- 39 篇 统计学（可授理学、...
- 33 篇 化学
- 11 篇 系统科学
269 篇 医学
- 269 篇 临床医学
- 25 篇 基础医学(可授医学...
- 22 篇 药学(可授医学、理...
75 篇 管理学
- 63 篇 图书情报与档案管...
- 13 篇 管理科学与工程(可...
- 8 篇 工商管理
10 篇 法学
- 9 篇 社会学
4 篇 农学
3 篇 经济学
1 篇 教育学

主题

46 篇 computer graphic...
44 篇 artificial intel...
42 篇 image processing...
33 篇 computer vision
29 篇 deep learning
27 篇 pattern recognit...
25 篇 image segmentati...
22 篇 computer imaging...
20 篇 image enhancemen...
19 篇 graphics process...
17 篇 face recognition
17 篇 image reconstruc...
15 篇 cameras
13 篇 image processing
11 篇 generative adver...
10 篇 object detection
10 篇 computer communi...
10 篇 pixels
10 篇 feature extracti...
10 篇 machine learning

机构

15 篇 indian institute...
11 篇 indian statistic...
11 篇 carnegie mellon ...
11 篇 hebrew universit...
11 篇 google research
10 篇 indian inst tech...
8 篇 indian stat inst...
8 篇 indian inst tech...
7 篇 indian institute...
7 篇 indian institute...
7 篇 indian inst tech...
7 篇 indian inst tech...
7 篇 technische unive...
7 篇 indian inst sci ...
6 篇 indian institute...
6 篇 indian institute...
6 篇 indian inst tech...
6 篇 technical univer...
6 篇 indian inst tech...
6 篇 department of co...

作者

31 篇 chaudhury santan...
26 篇 mukherjee jayant...
25 篇 chaudhuri subhas...
19 篇 das sukhendu
15 篇 babu r. venkates...
14 篇 das partha prati...
14 篇 lall brejesh
14 篇 raman shanmugana...
13 篇 harit gaurav
12 篇 mukherjee dipti ...
12 篇 chanda bhabatosh
12 篇 mishra deepak
11 篇 martial hebert
11 篇 yair weiss
11 篇 vittorio ferrari
11 篇 cristian sminchi...
11 篇 biswas prabir ku...
10 篇 banerjee biplab
10 篇 biswas soma
10 篇 sur arijit

语言

997 篇 英文
3 篇 俄文
3 篇 中文
2 篇 其他

检索条件"任意字段=15th Indian Conference on Computer Vision Graphics and Image Processing"

共 1004 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：

MoCoMER: A Self Supervised Representation Learning for Handwritten Mathematical Expression Recognition 24

MoCoMER: A Self Supervised Representation Learning for Handw...

引用

15th indian conference on computer vision graphics and image processing

作者： Pramanik, Sandip Mitra, Shree Das, Nibaran Jadavpur Univ Dept CSE Kolkata W Bengal India Indian Inst Informat Technol Guwahati Gauhati India

ISBN: (纸本)9798400710759

this paper presents a self-supervised learning (SSL) based framework, specifically designed for Handwritten Mathematical Expression Recognition (HMER). the proposed approach incorporates a momentum encoding technique and a non-linear projection head into the image encoder to effectively address the common issue of dimensional collapse in self-supervised learning (SSL) methods. Our approach consists of two main steps: first, we use self-supervised pre-training to train the image encoder to obtain strong feature representations from HME images. Subsequently, we fine-tune the model using a Transformer network to predict LaTeX sequences from HME images. the assessment demonstrates that our SSL framework surpasses other existing SSL frameworks as well as several supervised methods in terms of performance. the findings indicate that our approach is highly advanced, emphasizing its potential to enhance the robustness and efficiency of feature representations in HMER tasks. the integration of momentum encoding and a non-linear projection head in the image encoder is shown to enhance the durability and effectiveness of feature representations, leading to superior performance in HMER tasks. Our experiments reveal that our approaches achieve an expression recognition rate (ExpRate) of 62. 17%, 61. 03%, 64. 8% on the CROHME 2014,2016,2019 test datasets respectively. the CROHME 2019 test data achieves the highest ExpRate, which is state-of-the-art (SOTA). this success is achieved by overcoming the challenges of dimensional collapse and leveraging the advantages of both self-supervised and supervised learning.(1)

关键词： HMER SSL Contrastive Learning Momentum Contrast (MoCo) Non-linear projection head Transformer

来源：评论

学校读者我要写书评

暂无评论

OHCS: A Database for Handwritten Atomic Odia Character Recognition 5

OHCS: A Database for Handwritten Atomic Odia Character Recog...

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Mohapatra, Ramesh Kumar Mishra, Tusar Kanti Panda, Sandeep Majhi, Banshidhar Natl Inst Technol Comp Sci & Engn Rourkela 769008 India

ISBN: (纸本)9781467385640

In this paper, a complete database of handwritten atomic Odia characters is suggested. the first version of the database has been modeled and named OHCSv1.0 (Odia handwritten character set). the database comprises of 17,100 transcribed characters, each collected twice from 150 unique people at different point of time. Each character has 300 number of occurrences. the character images are standardized to a size of 6 4 x 6 4 pixels. A novel framework for perceiving transcribed Odia characters from this database has also been proposed. the character images are gathered into various groups in view of their shape components utilizing an incremental spectral clustering algorithm. During testing, affinity of probe character to a cluster is first decided. Subsequently, the trained classifier recognizes the character inside the cluster. Suitable simulation has been carried out to validate the scheme.

关键词： Character recognition

来源：评论

学校读者我要写书评

暂无评论

HSGA: A Novel Acceleration Descriptor for Human Action Recognition 5

HSGA: A Novel Acceleration Descriptor for Human Action Recog...

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Edison, Anitha Jiji, C., V Coll Engn Dept Elect & Commun Engn Trivandrum Kerala India

ISBN: (纸本)9781467385640

Tracking dense features has become one of the most popular methods for human action recognition. Proper descriptors should be used to capture the motion information contained in these trajectories and motion boundary histogram (MBH), which encodes velocity information, gives best performance among state of art action recognition descriptors. In this paper, we propose to use a new descriptor, histogram of spatial gradient of acceleration (HSGA) in combination with MBH to describe actions. Our new descriptor combination is based on studies which reveal that acceleration is as important as velocity in motion description. HSGA is computed by taking histogram of orientation of spatial gradient of optical acceleration in a 3D space-time block divided into cells around dense trajectories. Optical acceleration is obtained by taking time derivative of optical flow. this combination of descriptors gave good performance on a variety of data sets. Combining these motion descriptors with a scene descriptor like HOG further improved the recognition accuracy for realistic action datasets.

关键词： Acceleration

来源：评论

学校读者我要写书评

暂无评论

Real-Time Approximate and Exact CSG of Implicit Surfaces on the GPU

Real-Time Approximate and Exact CSG of Implicit Surfaces on ...

引用

4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Singh, Jag Mohan Qualcomm Res India Hyderabad Andhra Pradesh India

ISBN: (纸本)9781479915880

We present a simple and powerful scheme to allow CSG of implicit surfaces on the GPU. We decompose the boolean expression of surfaces into sum-of-products form. Our algorithm presented in this paper then renders each product term, sum of products can be automatically by enabling depth test. Our Approximate CSG uses adaptive marching points algorithm for finding ray-surface intersection. Once we find an interval where root exists after root-isolation, this is used for presence of intersection. We perform root-refinement only for the uncomplemented terms in the product. Exact CSG is done by using the discriminant of the ray-surface intersection for the presence of the root. Now we can simply evaluate the product expression by checking all uncomplemented terms should be true and all complemented terms should be false. If our condition is met, we find the maximum of all the roots among uncomplemented terms to be the solution. Our algorithm is linear in the number of terms O(n). We achieve real-time rates for 4-5 terms in the product for approximate CSG. We achieve more than real-time rates for Exact CSG. Our primitives are implicit surfaces so we can achieve fairly complex results with less terms.

关键词： Implicit GRAPPER PICK UP graphics processing Unit Root Approximate Intersection Crossing Exact Real time Discriminant Boolean expression

来源：评论

学校读者我要写书评

暂无评论

Recognizing Newborns using Binocular Region 5

Recognizing Newborns using Binocular Region

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Parmar, Chandani Vishwamitra, L. K. Patel Coll Sci & Technol Dept Comp Sci & Engn Bhopal India

ISBN: (纸本)9781467385640

Existing approaches on newborn identification focuses on recognizing them using face, inked footprints, and palm prints. While palm and inked footprints are intrusive modalities, face modality suffers from non-cooperative nature of newborns. In this research, we investigate utilization of binocular region for recognizing newborns, as this region is considered to be relatively stable in face biometrics literature. We collect a database consisting of 402 face images pertaining to 50 babies of less than 6 months of age. A set of experiments pertaining to various descriptors, including local binary patterns, dense scale invariant feature transform, and Gabor features, along with subspace learning using principal component analysis, linear discriminant analysis, and independent component analysis. Recognition performance of various approaches are compared with respect to face and binocular modalities. Verification results are reported in terms of Receiver operating characteristics curves respectively. the results show that binocular can outperform face as a modality for newborn recognition.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Classification of Brain MR images using Discrete Wavelet Transform and Random Forests 5

Classification of Brain MR Images using Discrete Wavelet Tra...

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Nayak, Deepak Ranjan Dash, Ratnakar Majhi, Banshidhar Natl Inst Technol Dept Comp Sci & Engn Rourkela 769008 India

ISBN: (纸本)9781467385640

Development of computer-aided diagnosis (CAD) systems for early detection of the pathological brain is essential to save medical resources. In recent years, a variety of techniques have been proposed to upgrade the system's performance. In this paper, a new automatic CAD system for brain magnetic resonance (MR) image classification is proposed. the method utilizes two-dimensional discrete wavelet transform to extract features from the MR images. the dimension of the features have been reduced using principal component analysis (PCA) and linear discriminant analysis (LDA), to obtain the more significant features. Finally, the reduced set of features are applied to the random forests classifier to determine the normal or pathological brain. A standard dataset, Dataset-255 of 255 images (35 normal and 220 pathological) is used for the validation of the proposed scheme. To improve the generalization capability of the scheme, 5-fold stratified cross-validation procedure is utilized. the results of the experiments reveal that the proposed scheme is superior to other state-of-the-art techniques in terms of classification accuracy with substantially reduced number of features.

关键词： Discrete wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

Fusion-based Skin Detection using image Distribution Model 16

Fusion-based Skin Detection using Image Distribution Model

引用

10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Chakraborty, Biplab Ketan Bhuyan, M. K. Kumar, Sunil Indian Inst Technol Guwahati Dept Elect & Elect Engn Gauhati Assam India

ISBN: (纸本)9781450347532

Skin colour detection under poor or varying illumination condition is a big challenge for various image processing and human-computer interaction applications. In this paper, a novel skin detection method utilizing image pixel distribution in a given colour space is proposed. the pixel distribution of an image can provide a better localization of the actual skin colour distribution of an image. Hence, a local skin distribution model (LSDM) is derived using the image pixel distribution model and its similarity with the global skin distribution model (GSDM). Finally, a fusion-based skin model is obtained using both the GSDM and the LSDM. Subsequently, a dynamic region growing method is employed to improve the overall detection rate. Experimental results show that proposed skin detection method can significantly improve the detection accuracy in presence of varying illumination conditions.

关键词： Skin detection Skin probability map Mixture of Gaussians Region growing

来源：评论

学校读者我要写书评

暂无评论

Unusual Activity Analysis using Video Epitomes and pLSA

Unusual Activity Analysis using Video Epitomes and pLSA

引用

6th indian conference on computer vision, graphics and image processing

作者： Choudhary, Ayesha Pal, Manish Banerjee, Subhashis Chaudhury, Santanu Indian Inst Technol Dept Comp Sci & Engn Delhi India Indian Inst Technol Dept Elect Engn Delhi India

ISBN: (纸本)9781424442195

In this paper we address the problem of unsupervised learning of usual patterns of activities in an area under surveillance and detecting deviant patterns. We use video epitomes for segmenting foreground objects from background and obtain an approximate shape, trajectory and temporal information in the form of space-time patches. We apply pLSA for finding correlations among these patches to learn usual activities in the scene. We also extend pLSA to classify a novel video as usual or unusual.

关键词： Pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Weighted Fast Dynamic Time Warping Based Multi-View Human Activity Recognition Using a RGB-D Sensor 5

Weighted Fast Dynamic Time Warping Based Multi-View Human Ac...

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Agarwal, Ishan Kushwaha, Alok Kumar Singh Srivastava, Rajeev Jaypee Inst Informat Technol Dept Comp Sc & Engn Noida UP India Indian Inst Technol BHU Dept Comp Sc & Engn Varanasi 221005 Uttar Pradesh India

ISBN: (纸本)9781467385640

In this paper, a real time multi-view human activity recognition model using a RGB-D (Red Green BlueDepth) sensor is proposed. the method receives as input RGBD data streams in real time from a Kinect for Windows V2 sensor. Initially, a skeleton-tracking algorithm is applied which gives 3D joint information of 25 unique joints. the presented approach uses a weighted version of the Fast Dynamic Time Warping that weighs the importance of each skeleton joint towards the Dynamic Time Warping (DTW) similarity cost. To recognize multi-view human activities, the weighted Dynamic TimeWarping warps a time sequence of joint positions to reference time sequences and produces a similarity value. Experimental results demonstrate that the proposed method is robust, flexible and efficient with respect to multiple views activity recognition, scale and phase variations activities at different realistic scenes.

关键词： RGB-D Sensor Skeletal Tracking Human Activity Recognition Microsoft Kinect V2

来源：评论

学校读者我要写书评

暂无评论

Alternate Formulation for Transform Learning 16

Alternate Formulation for Transform Learning

引用

10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Maggu, Jyoti Majumdar, Angshul Indraprastha Inst Informat Technol Okhla Phase 3 New Delhi 110020 India

ISBN: (纸本)9781450347532

Dictionary learning has been used to solve inverse problems in imaging and as an unsupervised feature extraction tool in vision. the main disadvantage of dictionary learning for applications in vision is the relatively long feature extraction time during testing;owing to the requirement of solving an iterative optimization problem (10-minimization). the newly developed analysis framework of transform learning does not suffer from this shortcoming;feature extraction only requires a matrix vector multiplication. this work proposes an alternate formulation for transform learning that improves the accuracy even further. Experiments on benchmark databases show that our proposed transform learning yields results better than dictionary learning, autoencoder (AE) and restricted Boltzmann machine (RBM). the feature extraction time is fast as AE and RBM.

关键词： Dictionary learning dimensionality reduction feature extraction

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101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：