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

921 篇 会议
61 册 图书
23 篇 期刊文献

馆藏范围

1,005 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

822 篇 工学
- 720 篇 计算机科学与技术...
- 375 篇 软件工程
- 335 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...
- 40 篇 电子科学与技术（可...
- 35 篇 化学工程与技术
- 27 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
2 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 object detection
11 篇 generative adver...
11 篇 machine learning
11 篇 optical characte...
10 篇 computer communi...
10 篇 pixels

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

998 篇 英文
3 篇 俄文
2 篇 其他
2 篇 中文

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

共 1005 条记录，以下是511-520 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：

Event Recognition in Egocentric Videos Using a Novel Trajectory Based Feature 16

Event Recognition in Egocentric Videos Using a Novel Traject...

引用

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

作者： Buddubariki, Vinodh Tulluri, Sunitha Gowd Mukherjee, Snehasis IIIT Chittoor Sricity India

ISBN: (纸本)9781450347532

this paper proposes an approach for event recognition in Egocentric videos using dense trajectories over Gradient Flow - Space Time Interest Point (GF-STIP) feature. We focus on recognizing events of diverse categories (including indoor and outdoor activities, sports and social activities and adventures) in egocentric videos. We introduce a dataset with diverse egocentric events, as all the existing egocentric activity recognition datasets consist of indoor videos only. the dataset introduced in this paper contains 102 videos with 9 different events (containing indoor and outdoor videos with varying lighting conditions). We extract Space Time Interest Points (STIP) from each frame of the video. the interest points are taken as the lead pixels and Gradient-Weighted Optical Flow (GWOF) features are calculated on the lead pixels by multiplying the optical flow measure and the magnitude of gradient at the pixel, to obtain the GF-STIP feature. We construct pose descriptors with the GF-STIP feature. We use the GF-STIP descriptors for recognizing events in egocentric videos with three different approaches: following a Bag of Words (BoW) model, implementing Fisher Vectors and obtaining dense trajectories for the videos. We show that the dense trajectory features based on the proposed GF-STIP descriptors enhance the efficacy of the event recognition system in egocentric videos.

关键词： GWOF Dense Trajectories Event Recognition First Person Egocentric

来源：评论

学校读者我要写书评

暂无评论

Learning to Hash-tag Videos with Tag2Vec 16

Learning to Hash-tag Videos with Tag2Vec

引用

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

作者： Singh, Aditya Saini, Saurabh Shah, Rajvi Narayanan, P. J. IIIT Hyderabad KCIS CVIT Hyderabad Telangana India

ISBN: (纸本)9781450347532

User-given tags or labels are valuable resources for semantic understanding of visual media such as images and videos. Recently, a new type of labeling mechanism known as hash tags have become increasingly popular on social media sites. In this paper, we study the problem of generating relevant and useful hash-tags for short video clips. Traditional data driven approaches for tag enrichment and recommendation use direct visual similarity for label transfer and propagation. We attempt to learn a direct low-cost mapping from video to hash-tags using a two step training process. We first employ a natural language processing (NLP) technique, skip-gram models with neural network training to learn a low-dimensional vector representation of hash-tags (Tag2Vec) using a corpus of similar to 10 million hash-tags. We then train an embedding function to map video features to the low-dimensional Tag2vec space. We learn this embedding for 29 categories of short video clips with hash-tags. A query video without any tag-information can then be directly mapped to the vector space of tags using the learned embedding and relevant tags can be found by performing a simple nearest-neighbor retrieval in the Tag2Vec space. We validate the relevance of the tags suggested by our system qualitatively and quantitatively with a user study.

关键词： Tag2Vec Video Tagging Hash-tag recommendation

来源：评论

学校读者我要写书评

暂无评论

Info-graphics retrieval: A multi-kernel distance based hashing scheme 10

Info-graphics retrieval: A multi-kernel distance based hashi...

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Garg, Ritu Chaudhury, Santanu Department of Electrical Engineering Indian Institute of Technology Delhi Delhi India

Information retrieval research has shown significant improvement and provided techniques that retrieve documents in image or text form. However, retrieval of multi-modal documents has been given very less attention. We aim to build a system for retrieval of documents with embedded information graphics (Info-graphics). Info-graphics are images of bar charts and line graphs appearing with textual components in magazines, newspapers, and journals. In this paper, we present multi-modal document image retrieval framework by learning an optimal fusion of information from text and info-graphics regions. the evaluation of the proposed concept is demonstrated on documents collected from various sources such as magazines and journals. © Springer International Publishing AG 2017.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

Autoregressive Hidden Markov Model with Missing Data for Modelling Functional MR Imaging Data 16

Autoregressive Hidden Markov Model with Missing Data for Mod...

引用

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

作者： Dang, Shilpa Chaudhury, Santanu Lall, Brejesh Roy, Prasun Kumar Indian Inst Technol Delhi New Delhi India Cent Elect Engn Res Inst Pilani Rajasthan India Natl Brain Res Ctr Gurgaon Haryana India

ISBN: (纸本)9781450347532

Functional Magnetic Resonance Imaging (fMRI) has opened ways to look inside active human brain. However, fMRI signal is an indirect indicator of underlying neuronal activity and has low-temporal resolution due to acquisition process. this paper proposes autoregressive hidden Markov model with missing data (AR-HMM-md) framework which aims at addressing aforementioned issues while allowing accurate capturing of fMRI time series characteristics. the proposed work models unobserved neuronal activity over time as sequence of discrete hidden states, and shows how exact inference can be obtained with missing fMRI data under the "Missing not at Random" (MNAR) mechanism. this mechanism requires explicit modelling of the missing data along with the observed data. the performance is evaluated by observing convergence characteristic of log-likelihoods and classification capability of the proposed model over existing models for two fMRI datasets. the classification is performed between real fMRI time series from a task-based experiment and randomly-generated time series. Another classification experiment is performed between children and elder subjects using fMRI time series from resting-state data. the proposed model captured the fMRI characteristics efficiently and thus converged to better posterior probability resulting into higher classification accuracy over existing models for both the datasets.

关键词： Activation detection autoregressive hidden Markov model connectivity detection fMRI missing data

来源：评论

学校读者我要写书评

暂无评论

Supervised Deep Segmentation Network for Brain Extraction 16

Supervised Deep Segmentation Network for Brain Extraction

引用

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

作者： Sikka, Apoorva Mittal, Gaurav Bathula, Deepti R. Krishnan, Narayanan C. IIT Ropar Rupnagar Punjab India

ISBN: (纸本)9781450347532

Recent past has seen an inexorable shift towards the use of deep learning techniques to solve a myriad of problems in the field of medical imaging. In this paper, a novel segmentation method involving a fully-connected deep neural network called Deep Segmentation Network (DSN) is proposed to perform supervised regression for brain extraction from T1-weighted magnetic resonance (MR) images. In contrast to the existing patch-based feature learning techniques, DSN works on full 3D volumes, simplifying pre- and post processing operations, to efficiently provide a voxel-wise binary mask delineating the brain region. the model is evaluated using three publicly available datasets and is observed to either outdo or perform comparably to the state-of-the-art methods. DSN is able to achieve a maximum and minimum Dice Similarity Coefficient (DSC) of 97.57 and 92.82 respectively across all the datasets. Experiments conducted in this paper highlight the ability of the DSN model to automatically learn feature representations;making it a simple yet highly effective approach for brain segmentation. Preliminary experiments also suggest that the proposed model has the potential to segment sub-cortical structures accurately.

关键词： brain extraction segmentation deep learning supervised neural network

来源：评论

学校读者我要写书评

暂无评论

Deep fusion of visual signatures for client-server facial analysis 16

Deep fusion of visual signatures for client-server facial an...

引用

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

作者： Bhattarai, Binod Sharma, Gaurav Jurie, Frederic Normandie Univ UNICAEN ENSICAEN CNRSGREYC Caen France IIT Kanpur Comp Sci & Engn Kanpur Uttar Pradesh India

ISBN: (纸本)9781450347532

Facial analysis is a key technology for enabling humanmachine interaction. In this context, we present a client-server framework, where a client transmits the signature of a face to be analyzed to the server, and, in return, the server sends back various information describing the face e.g. is the person male or female, is she/he bald, does he have a mustache, etc. We assume that a client can compute one (or a combination) of visual features;from very simple and efficient features, like Local Binary Patterns, to more complex and computationally heavy, like Fisher Vectors and CNN based, depending on the computing resources available. the challenge addressed in this paper is to design a common universal representation such that a single merged signature is transmitted to the server, whatever be the type and number of features computed by the client, ensuring nonetheless an optimal performance. Our solution is based on learning of a common optimal subspace for aligning the different face features and merging them into a universal signature. We have validated the proposed method on the challenging CelebA dataset, on which our method outperforms existing state-of-art methods when rich representation is available at test time, while giving competitive performance when only simple signatures (like LBP) are available at test time due to resource constraints on the client.

关键词： Local binary pattern

来源：评论

学校读者我要写书评

暂无评论

Improving Person Re-Identification Systems: A Novel Score Fusion Framework for Rank-n Recognition 16

Improving Person Re-Identification Systems: A Novel Score Fu...

引用

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

作者： Barman, Arko Shah, Shishir K. Univ Houston 4800 Calhoun Rd Houston TX 77004 USA

ISBN: (纸本)9781450347532

Person re-identification is an essential technique for video surveillance applications. Most existing algorithms for person re-identification deal with feature extraction, metric learning or a combination of both. Combining successful state-ofthe-art methods using score fusion from the perspective of person re-identification has not yet been widely explored. In this paper, we endeavor to boost the performance of existing systems by combining them using a novel score fusion framework which requires no training or dataset-dependent tuning of parameters. We develop a robust and efficient method called Unsupervised Posterior Probability-based Score Fusion (UPPSF) for combination of raw scores obtained from multiple existing person re-identification algorithms in order to achieve superior recognition rates. We propose two novel generalized linear models for estimating the posterior probabilities of a given probe image matching each of the gallery images. Normalization and combination of these posterior probability values computed from each of the existing algorithms individually, yields a set of unified scores, which is then used for ranking the gallery images. Our score fusion framework is inherently capable of dealing with different ranges and distributions of matching scores emanating from existing algorithms, without requiring any prior knowledge about the algorithms themselves, effectively treating them as "black-box" methods. Experiments on widely-used challenging datasets like VIPeR, CUHK01, CUHK03, EthZ1 and EthZ2 demonstrate the efficiency of UPPSF in combining multiple algorithms at the score level.

关键词： Person Re-identification Score Fusion Posterior Probability Estimation

来源：评论

学校读者我要写书评

暂无评论

Unsupervised domain adaptation without source domain training samples - a maximum margin clustering based approach 16

Unsupervised domain adaptation without source domain trainin...

引用

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

作者： Saha, Sudipan Banerjee, Biplab Merchant, Shabbir N. Indian Inst Technol Dept Elect Engn Bombay Maharashtra India Indian Inst Technol Dept Comp Sci Roorkee Uttar Pradesh India

ISBN: (纸本)9781450347532

Unsupervised domain adaptation (DA) techniques inherently assume the presence of ample amount of source domain training samples in addition to the target domain test data. the domains are characterized by domain-specific probability distributions governing the data which are substantially different from each other. the goal is to build a task oriented classifier model that performs proportionately in both the domains. In contrary to the standard unsupervised DA setup, we propose a maximum-margin clustering (MMC) based framework for the same which does not consider source domain labeled samples. Instead we formulate it as a joint clustering problem of all the samples from both the domains in a common feature subspace. the Geodesic Flow Kernel (GFK) based subspace projection technique in the Grassmannian manifold is adopted to cast the samples in a domain invariant space. Further, the MMC stage is followed to simultaneously group the data based on the maximization of margins and a classifier is learned for each group. the data overlapping problem is taken care of by specifically learning a SVM-KNN classifier for the potentially unreliable samples per group. We validate the framework on a pair of remote sensing images of different modalities for the purpose of land-cover classification and a generic object dataset for recognition. We observe that the proposed method exhibits performances at par with the fully supervised case for both the tasks but without the requirement of costly annotations.

关键词： Domain adaptation Max-margin clustering Geodesic Flow Kernel

来源：评论

学校读者我要写书评

暂无评论

Fast and High-Quality Bilateral Filtering Using Gauss-Chebyshev Approximation 11

Fast and High-Quality Bilateral Filtering Using Gauss-Chebys...

引用

11th International conference on Signal processing and Communications (SPCOM)

作者： Ghosh, Sanjay Chaudhury, Kunal N. Indian Inst Sci Dept Elect Engn Bangalore Karnataka India

ISBN: (纸本)9781509017461

the bilateral filter is an edge-preserving smoother that has diverse applications in image processing, computer vision, computer graphics, and computational photography. the filter uses a spatial kernel along with a range kernel to perform edge-preserving smoothing. In this paper, we consider the Gaussian bilateral filter where both the kernels are Gaussian. A direct implementation of the Gaussian bilateral filter requires O (sigma(2)(s)) operations per pixel, where sigma(s) is the standard deviation of the spatial Gaussian. In fact, it is well-known that the direct implementation is slow in practice. We present an approximation of the Gaussian bilateral filter, whereby we can cut down the number of operations to O (1) per pixel for any arbitrary sigma(s), and yet achieve very high-quality filtering that is almost indistinguishable from the output of the original filter. We demonstrate that the proposed approximation is few orders faster in practice compared to the direct implementation. We also demonstrate that the approximation is competitive with existing fast algorithms in terms of speed and accuracy.

关键词： Fast algorithm bilateral filter Gaussian kernel Chebyshev polynomial minimax approximation

来源：评论

学校读者我要写书评

暂无评论

DeepFly: Towards Complete Autonomous Navigation of MAVs with Monocular Camera 16

DeepFly: Towards Complete Autonomous Navigation of MAVs with...

引用

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

作者： Shah, Utsav Khawad, Rishabh Krishna, K. Madhava IIIT Hyderabad KCIS Robot Res Ctr Hyderabad Andhra Pradesh India

ISBN: (纸本)9781450347532

Recently, the interest in Micro Aerial Vehicles (MAVs) and their autonomous flights has increased tremendously and significant advances have been made. the monocular camera has turned out to be most popular sensing modality for MAVs as it is light-weight, does not consume more power, and encodes rich information about the environment around. In this paper, we present DeepFly, our framework for autonomous navigation of a quadcopter equipped with monocular camera. the navigable space detection and waypoint selection are fundamental components of autonomous navigation system. they have broader meaning than just detecting and avoiding immediate obstacles. Finding the navigable space emphasizes equally on avoiding obstacles and detecting ideal regions to move next to. the ideal region can be defined by two properties: 1) All the points in the region have approximately same high depth value and 2) the area covered by the points of the region in the disparity map is considerably large. the waypoints selected from these navigable spaces assure collision-free path which is safer than path obtained from other waypoint selection methods which do not consider neighboring information. In our approach, we obtain a dense disparity map by performing a translation maneuver. this disparity map is input to a deep neural network which predicts bounding boxes for multiple navigable regions. Our deep convolutional neural network with shortcut connections regresses variable number of outputs without any complex architectural add on. Our autonomous navigation approach has been successfully tested in both indoors and outdoors environment and in range of lighting conditions.

关键词： Micro Aerial Vehicles Autonomous Navigation Deep Learning

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 << < 48 49 50 51 52 53 54 55 56 57 > >>

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：