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

1,413 篇 会议
54 册 图书
27 篇 期刊文献

馆藏范围

1,494 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,010 篇 工学
- 901 篇 计算机科学与技术...
- 410 篇 软件工程
- 389 篇 电气工程
- 131 篇 信息与通信工程
- 122 篇 光学工程
- 90 篇 生物工程
- 65 篇 生物医学工程（可授...
- 58 篇 电子科学与技术（可...
- 38 篇 控制科学与工程
- 34 篇 化学工程与技术
- 29 篇 机械工程
- 21 篇 仪器科学与技术
- 17 篇 安全科学与工程
- 10 篇 材料科学与工程（可...
- 9 篇 建筑学
- 8 篇 土木工程
347 篇 医学
- 344 篇 临床医学
- 27 篇 基础医学(可授医学...
- 26 篇 药学(可授医学、理...
333 篇 理学
- 158 篇 物理学
- 147 篇 数学
- 93 篇 生物学
- 47 篇 统计学（可授理学、...
- 32 篇 化学
- 16 篇 系统科学
92 篇 管理学
- 69 篇 图书情报与档案管...
- 23 篇 管理科学与工程(可...
- 13 篇 工商管理
12 篇 农学
- 12 篇 作物学
10 篇 法学
- 9 篇 社会学
6 篇 经济学
3 篇 教育学
2 篇 文学
1 篇 艺术学

主题

142 篇 computer vision
80 篇 image processing
77 篇 image segmentati...
54 篇 computer graphic...
54 篇 feature extracti...
52 篇 cameras
46 篇 deep learning
38 篇 shape
35 篇 face recognition
34 篇 image reconstruc...
32 篇 artificial intel...
30 篇 robustness
28 篇 object detection
28 篇 image color anal...
25 篇 image enhancemen...
25 篇 image edge detec...
25 篇 pattern recognit...
25 篇 layout
24 篇 biometrics
23 篇 image processing...

机构

20 篇 indian statistic...
19 篇 indian institute...
17 篇 department of co...
14 篇 computer vision ...
12 篇 indian institute...
11 篇 department of el...
10 篇 indian inst tech...
9 篇 indian stat inst...
9 篇 indian institute...
9 篇 indian inst tech...
9 篇 indian institute...
8 篇 indian institute...
8 篇 department of el...
8 篇 indian institute...
8 篇 indian inst sci ...
8 篇 indian inst tech...
7 篇 indian inst tech...
7 篇 indian institute...
7 篇 indian inst tech...
7 篇 indian inst tech...

作者

40 篇 chaudhury santan...
29 篇 chaudhuri subhas...
26 篇 mukherjee jayant...
20 篇 das sukhendu
19 篇 raman shanmugana...
18 篇 santanu chaudhur...
17 篇 balasubramanian ...
16 篇 harit gaurav
16 篇 lall brejesh
15 篇 babu r. venkates...
15 篇 chanda bhabatosh
14 篇 mukherjee dipti ...
13 篇 das partha prati...
12 篇 biswas prabir ku...
12 篇 mishra deepak
11 篇 raman balasubram...
11 篇 sukhendu das
10 篇 biswas soma
10 篇 bhowmick partha
10 篇 bhavsar arnav

语言

1,484 篇 英文
7 篇 中文
3 篇 其他

检索条件"任意字段=Proceedings of the Fourteenth Indian Conference on Computer Vision, Graphics and Image Processing"

共 1494 条记录，以下是1441-1450 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：

Learning to Prevent Monocular SLAM Failure using Reinforcement Learning 18

Learning to Prevent Monocular SLAM Failure using Reinforceme...

引用

proceedings of the 11th indian conference on computer vision, graphics and image processing

作者： Vignesh Prasad Karmesh Yadav Rohitashva Singh Saurabh Swapnil Daga Nahas Pareekutty K. Madhava Krishna Balaraman Ravindran Brojeshwar Bhowmick Embedded Systems & Robotics TCS Research & Innovation Kolkata India Robotics Institute Carnegie Mellon University Pittsburgh USA Dept. of Robotics Engineering John Hopkins University Baltimore USA Robotics Research Center KCIS IIIT Hyderabad India Dept. of Computer Science Indian Institute of Technology Madras India

ISBN: (纸本)9781450366151

Monocular SLAM refers to using a single camera to estimate robot ego motion while building a map of the environment. While Monocular SLAM is a well studied problem, automating Monocular SLAM by integrating it with trajectory planning frameworks is particularly challenging. This paper presents a novel formulation based on Reinforcement Learning (RL) that generates fail safe trajectories wherein the SLAM generated outputs do not deviate largely from their true values. Quintessentially, the RL framework successfully learns the otherwise complex relation between perceptual inputs and motor actions and uses this knowledge to generate trajectories that do not cause failure of SLAM. We show systematically in simulations how the quality of the SLAM dramatically improves when trajectories are computed using RL. Our method scales effectively across Monocular SLAM frameworks in both simulation and in real world experiments with a mobile robot.

关键词： Monocular SLAM

来源：评论

学校读者我要写书评

暂无评论

Finding connected components in digital images

Finding connected components in digital images

引用

International conference on Information Technology: Coding and Computing (ITCC)

作者： V. Khanna P. Gupta C.J. Hwang Department of Computer Science & Engineering Indian Institute of Technology Kanpur Kanpur India Department of Computer Science Southwest Texas State University San Marcos TX USA

ISBN: (纸本)0769510620

An efficient algorithm is presented to label the connected components in an array representation of 2D images. A new data structure is suggested to maintain the equivalence table that makes use of a modified version of union-find algorithms. The operations supported by the equivalence table enable aggressive reuse of labels and (lower) bound the size of the table to [N/2]+1 for an N/spl times/N image. It is also shown that the maintenance of the table has an overall linear amortized cost.

关键词： Digital images Pixel computer science Data structures Maintenance engineering Costs computer vision image processing Application software

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning-based Model for Phase Unwrapping 2018

A Deep Learning-based Model for Phase Unwrapping

引用

proceedings of the 11th indian conference on computer vision, graphics and image processing

作者： G. E. Spoorthi Subrahmanyam Gorthi Rama Krishna Sai Gorthi Indian Institute of Technology Tirupati A.P

ISBN: (纸本)9781450366151

Phase unwrapping is an important problem in several applications that attempts to restore original phase from wrapped phase. In this paper, we propose a novel phase unwrapping model based on the deep convolutional neural network by formulating the phase unwrapping as a semantic segmentation problem. The proposed architecture consists of a convolutional encoder network and corresponding decoder network followed by a pixel-wise classification layer. One of the critical challenges in DCNN is availability of large set of labeled training data. This issue is effectively circumvented for the proposed framework through a generic simulation procedure that automatically generates large labeled data. Results from the proposed method are compared with widely used quality-guided phase unwrapping algorithm for various SNR values. It is found that the proposed method is performing well both in terms of accuracy and computational time, even in the presence strong noise. To the best of our knowledge, this is the first work that uses convolutional neural network for phase unwrapping, and this will hopefully pave the way to a new class of techniques for unwrapping the phase.

关键词： Decoder Deep Convolutional Neural Network (DCNN) Encoder Phase Unwrapping Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Alzheimer’s severity classification using Transfer Learning and Residual Separable Convolution Network 22

Alzheimer’s severity classification using Transfer Learning...

引用

proceedings of the Thirteenth indian conference on computer vision, graphics and image processing

作者： Bala Venkateswarlu Isunuri Dr Jagadeesh Kakarla CSE Indian Institute of Information Technology Design and Managment Kancheepuram India

ISBN: (纸本)9781450398220

Severity classification is the most pivotal task in Alzheimer’s disease diagnosis. Detection of brain structural changes from brain MR images is crucial for Alzheimer’s classification. In this paper, we have proposed a transfer learning and residual separable convolution network for the classification of Alzheimer’s. The proposed network includes three separable convolution layers with two average pooling layers. An upsampling has been performed to regain its spatial resolution for the residual connection. The main intuition of separable convolution is to optimize parameters with depth-wise convolution. Similarly, the residual connection has been used to reduce the vanishing gradient problem. Finally, a three-layer fully connected dense network has been used for the four-class Alzheimer’s classification. Kaggle dataset has been utilized for the experiments to report results. We have achieved an accuracy of 97.32% on the dataset with five-fold cross-validation. Our model has reported an improvement of 1% in jaccard similarity and outperforms the competing models in all vital metrics.

关键词： Alxheimer’s disease Severity classification Transfer Learning Residual Separable Convolution Network

来源：评论

学校读者我要写书评

暂无评论

Moving Average Recurrent Neural Network Model for Video-based Person Re-Identification 2018

Moving Average Recurrent Neural Network Model for Video-base...

引用

proceedings of the 11th indian conference on computer vision, graphics and image processing

作者： Muhammed Fasil C. Subhasis Chaudhuri Dept. of Electrical Engineering Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)9781450366151

Person re-identification has great applications in video surveillance. It can be viewed as recognizing the same person across non-overlapping cameras. Video-based person re-identification methods are gaining increased attention due to the better discriminative nature of spatio-temporal feature representations. Current video-based methods make use of RNN to extract temporal information. In this paper, we propose a novel Moving Average Recurrent Neural Network (MA-RNN) model that can build a strong feature representation by taking both previous and present inputs at each time stamp. Specifically, here the recurrent layer produces a better sequential information by looking back directly in to the past values where as general RNNs has only an indirect dependence on the previous values in the form of hidden-state information. The proposed model is tested on two publicly available datasets: iLIDS-VID and PRID-2011 and it performed better in comparison with the state-of-the-art methods with a significant margin. We also analyze the effect of the depth of previous input dependence of the MA-RNN model on the matching accuracy.

关键词： MA-RNN RNN person re-identification

来源：评论

学校读者我要写书评

暂无评论

Towards Automated Floorplan Generation 18

Towards Automated Floorplan Generation

引用

proceedings of the 11th indian conference on computer vision, graphics and image processing

作者： Kunal Chelani Chitturi Sidhartha Venu Madhav Govindu Indian Institute of Science Bengaluru India

ISBN: (纸本)9781450366151

In this paper, we propose a pipeline for generating a 2D floorplan using depth cameras. In our pipeline we use an existing approach to recovering the camera motion trajectories from the depth and RGB sequences. Given these motion estimates we construct a full 3D representation of the scanned indoor spaces. For generating a floorplan we need to abstract the large volumes of registered 3D data into a simplified rectilinear representation. We evaluate two approaches to solve this problem, viz slicing the reconstructed volume at a given height and direct segmentation of the 3D point cloud representation into individual planar segments. We also note that the fidelity of our estimated floorplan crucially depends on the accuracy of the estimation of the ground plane orientation. We examine the comparative accuracies of two ground plane estimation methods for each of the above mentioned approaches to rectilinear abstraction. Given the line drawing abstractions of the individual rooms, we merge them into a consistent floorplan. We present results on a real-world floorplan estimation problem and demonstrate its accuracy. Additionally, the implications of errors in the individual components of our pipeline are also studied.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multiple Kernel Fisher Discriminant Metric Learning for Person Re-identification 2018

Multiple Kernel Fisher Discriminant Metric Learning for Pers...

引用

proceedings of the 11th indian conference on computer vision, graphics and image processing

作者： T. M. Feroz Ali Rajbabu Velmurugan Kalpesh K. Patel Subhasis Chaudhuri Dept. of Electrical Engineering Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)9781450366151

Person re-identification addresses the problem of matching pedestrian images across disjoint camera views. Design of feature descriptor and distance metric learning are the two fundamental tasks in person re-identification. In this paper, we propose a metric learning framework for person re-identification, where the discriminative metric space is learned using Kernel Fisher Discriminant Analysis (KFDA), to simultaneously maximize the inter-class variance as well as minimize the intra-class variance. We derive a Mahalanobis metric induced by KFDA and argue that KFDA is efficient to be applied for metric learning in person re-identification. We also show how the efficiency of KFDA in metric learning can be further enhanced for person re-identification by using two simple yet efficient multiple kernel learning methods. We conduct extensive experiments on three benchmark datasets for person re-identification and demonstrate that the proposed approaches have competitive performance with state-of-the-art methods.

关键词： Kernel Fisher Discriminant Analysis Multiple Kernel Fisher Discriminant Analysis Person Re-identification Metric Learning

来源：评论

学校读者我要写书评

暂无评论

Intelligent Computing Theories and Applications 2012

引用

丛书名： Lecture Notes in computer Science

2012年

作者： De-Shuang Huang Jianhua Ma Kang-Hyun Jo M. Michael Gromiha

ISBN: (数字)9783642315763

ISBN: (纸本)9783642315756

This book constitutes the refereed proceedings of the 8th International conference on Intelligent Computing, ICIC 2012, held in Huangshan, China, in July 2012. The 85 revised full papers presented were carefully reviewed and selected from 753 submissions. The papers are organized in topical sections on neural networks, evolutionar learning and genetic algorithms, granular computing and rough sets, biology inspired computing and optimization, nature inspired computing and optimization, cognitive science and computational neuroscience, knowledge discovery and data mining, quantum computing, machine learning theory and methods, healthcare informatics theory and methods, biomedical informatics theory and methods, complex systems theory and methods, intelligent computing in signal processing, intelligent computing in image processing, intelligent computing in robotics, intelligent computing in computer vision, intelligent agent and web applications, special session on advances in information security 2012.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Zero-shot Learning using Graph Regularized Latent Discriminative Cross-domain Triplets 2018

Zero-shot Learning using Graph Regularized Latent Discrimina...

引用

proceedings of the 11th indian conference on computer vision, graphics and image processing

作者： Omkar Gune Meet Vora Biplab Banerjee Subhasis Chaudhuri Indian Institute of Technology Bombay India Indian Institute of Technology Roorkee India

ISBN: (纸本)9781450366151

Zero-shot learning (ZSL) for visual recognition aims at identifying the previously unseen class samples given a trained model on the labeled visual samples of seen classes and additional class-level semantic side information for all classes. Often ZSL is tackled by learning an embedding function from the visual to semantic space or vice-versa. However, learning this mapping often results in loss of discriminative property of learned embedding space, thus severely compromising the recognition performance on the test samples. In order to ensure improved discrimination in the embedding space, we introduce a ZSL framework by leveraging the intuitive idea of cross-domain triplets based metric learning for learning such a space. Additionally, we introduce a novel graph Laplacian based regularizer which aligns the graph structures of the visual and semantic spaces in the learned embedding space. Simultaneously optimizing both the criteria results in a compact, discriminative, and meaningful embedding space, which is experimentally found to be superior to most of its existing counterparts on both the standard ZSL (AwA and CUB) and the challenging generalized ZSL (AwA1, AwA2, CUB) settings.

关键词： Zero-shot learning cross-domain alignment

来源：评论

学校读者我要写书评

暂无评论

Edge detection using scale space knowledge

Edge detection using scale space knowledge

引用

IEEE Region 10 International conference TENCON

作者： A. Kulkarni R. Shevgaonkar S.C. Sahasrabudhe Department of Electrical Engineering Indian Institute of Technology Bombay India

Edge detection has acquired enormous importance in computer vision research: gaussian filter has been widely used in the past to accomplish this task. Although the gaussian filter has nice scaling behaviour and is computationally elegant, it suffers from the disadvantage of delocalisation of edges when operated at higher scales. Multi-scale processing of an image is thus required. In this paper, the process of edge detection has been looked upon as a reasoning problem. In the past, knowledge handling and reasoning have been attributed to high level vision routines, but from the results presented here, it can be argued that reasoning does play an important role in the process of edge detection. The knowledge base required for this is formed out of the theory of scale space. Particular emphasis is laid on the behaviour of delocalised, missing and false or spurious edges in the scale space. The scale space is formed by operating the LoG filter of different sizes on the input image. The dissimilarity among the zero crossings is measured across the scales. It is useful in the removal of false edges. A compatibility measure relates the zero-crossing contour with the current scale parameter, /spl sigma/. The rules are coded in NEXPERT OBJECT 2.0. The results are compared with Canny's multiple edge detection algorithm (J.F. Canny, 1986).< >

关键词： image edge detection Low pass filters image representation Space technology computer vision Band pass filters Smoothing methods Current measurement Layout image analysis

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150页 << < 141 142 143 144 145 146 147 148 149 150 > >>

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：