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

528 篇 会议
17 篇 期刊文献
7 册 图书

馆藏范围

552 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

355 篇 工学
- 283 篇 计算机科学与技术...
- 155 篇 软件工程
- 74 篇 电气工程
- 37 篇 信息与通信工程
- 20 篇 控制科学与工程
- 19 篇 光学工程
- 19 篇 生物医学工程（可授...
- 15 篇 电子科学与技术（可...
- 11 篇 仪器科学与技术
- 10 篇 机械工程
- 9 篇 生物工程
- 5 篇 测绘科学与技术
- 4 篇 建筑学
- 4 篇 土木工程
- 4 篇 化学工程与技术
- 3 篇 安全科学与工程
- 2 篇 力学（可授工学、理...
125 篇 理学
- 82 篇 物理学
- 40 篇 数学
- 13 篇 生物学
- 8 篇 统计学（可授理学、...
- 4 篇 化学
- 3 篇 系统科学
32 篇 医学
- 26 篇 临床医学
- 7 篇 特种医学
- 5 篇 基础医学(可授医学...
- 3 篇 药学(可授医学、理...
26 篇 管理学
- 21 篇 管理科学与工程(可...
- 6 篇 图书情报与档案管...
- 5 篇 工商管理
1 篇 农学

主题

53 篇 image processing
41 篇 parallel process...
26 篇 feature extracti...
25 篇 image segmentati...
23 篇 deep learning
23 篇 computer vision
21 篇 image edge detec...
20 篇 training
19 篇 image reconstruc...
17 篇 image analysis
16 篇 computer archite...
15 篇 neural networks
15 篇 computational mo...
14 篇 image color anal...
13 篇 distributed comp...
13 篇 accuracy
12 篇 image enhancemen...
12 篇 graphics process...
12 篇 parallel computi...
11 篇 algorithm design...

机构

7 篇 natl univ def te...
5 篇 national laborat...
4 篇 college of compu...
3 篇 hong kong polyte...
3 篇 univ carlos iii ...
3 篇 cnr inst biomed ...
3 篇 natl univ def te...
3 篇 sensetime res pe...
3 篇 cnr inst appl ma...
3 篇 natl univ def te...
2 篇 nanjing audit un...
2 篇 college of compu...
2 篇 school of comput...
2 篇 uni. of pisa
2 篇 univ sydney sch ...
2 篇 tsinghua univ ts...
2 篇 department of in...
2 篇 school of comput...
2 篇 univ aegean dept...
2 篇 lsi laboratory u...

作者

11 篇 dou yong
8 篇 zhigang luo
8 篇 naiyang guan
8 篇 qiao peng
8 篇 carretero jesus
6 篇 yong dou
5 篇 xiang zhang
5 篇 shi hc
5 篇 xu kele
5 篇 dacheng tao
5 篇 li hz
3 篇 ercan mf
3 篇 luo zhigang
3 篇 milanesi luciano
3 篇 garcia-blas javi...
3 篇 peng qiao
3 篇 li dongsheng
3 篇 abella monica
3 篇 xuhui huang
3 篇 huang xuhui

语言

547 篇 英文
4 篇 其他
1 篇 中文

检索条件"任意字段=Conference on Parallel and Distributed Methods for Image Processing III"

共 552 条记录，以下是241-250 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：

20th East-European conference on Advances in Databases and Information Systems, ADBIS 2016 and Workshop on 3rd International Workshop on Big Data Applications and Principles, BigDap 2016, 2nd Workshop on Data-Centered Smart Applications, DCSA 2016, Workshop on Doctoral Consortium, DC 2016

20th East-European Conference on Advances in Databases and I...

引用

20th East-European conference on Advances in Databases and Information Systems, ADBIS 2016 and Workshop on 3rd International Workshop on Big Data Applications and Principles, BigDap 2016, 2nd Workshop on Data-Centered Smart Applications, DCSA 2016, Workshop on Doctoral Consortium, DC 2016

ISBN: (纸本)9783319440651

The proceedings contain 24 *** special focus in this conference is on Short Papers, Big Data Applications and Principles, Data centered Smart Applications and ADBIS Doctoral *** topics include: Towards automated performance optimization of BPMN business processes;pixel-based analysis of information dashboard attributes;towards adaptive distributed top-k query processing;basis functions as pivots in space of users preferences;towards semi-structured JSON big data;skyline algorithms on streams of multidimensional data;canonical data model for data warehouse;a quality-based query rewriting algorithm for data integration, towards spatial crowdsourcing in vehicular networks using mobile agents;shift of image processing technologies to column-oriented databases;influence of parallelism property of streaming engines on their performance;reducing big data by means of context-aware tailoring;feature ranking and selection for big data sets;a bagged associative classifier for big data frameworks;a new parallel approximate subspace clustering algorithm;smart modeling for lightweight mobile application development methods;an implementation method of an information credibility calculation system for emergency such as natural disasters;model capsules for research and engineering networks;usage of aspect-oriented programming in adaptive application structure;short-term user behaviour changes modelling and framework for managing distinct versions of data in relational databases.

关键词：

来源：评论

学校读者我要写书评

暂无评论

International conference on Control, Automation and Systems

International Conference on Control, Automation and Systems

引用

16th International conference on Control, Automation and Systems, ICCAS 2016

ISBN: (纸本)9788993215120

The proceedings contain 231 papers. The topics discussed include: evaluation of steering model depending on gazing distance by using driving simulator;estimation problem for network model at state and measurements attacks and information cost criterion;multi-input multi-output adaptive torque control of 9-DOF hyper-redundant robotic arm;mechanism and base control of human-friendly robot with passive collision force suppression mechanism;a tension distribution algorithm for cable-driven parallel robots operating beyond their wrench-feasible workspace;a three-dimensional surface registration method using a spherical unwrapping method and HK curvature descriptors for patient-to-CT registration of image guided surgery;road roughness modelling by using spectral factorization methods;design of position and force sensors of the haptic interface for training simulation of radial artery puncture;prototype development of on-board vision processing micro air vehicle for wide-range monocular slam;nonlinear stochastic time-varying system identification based on multi-dimensional Taylor network with optimal structure;comparison of faster R-CNN models for object detection;development of micro air vehicle using aerial photography for safe rowing and coaching;resource-constrained decentralized active sensing for multi-robot systems using distributed Gaussian processes;and mechanism and neural network based on PID control of quadcopter.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Maturity and disease detection in tomato using computer vision

Maturity and disease detection in tomato using computer visi...

引用

International conference on parallel distributed and Grid Computing (PDGC)

作者： Tanvi Mehra Vinay Kumar Pragya Gupta Dept. of Electronics and Communication Engineering Thapar University Patiala India Dept. of Electronics and Communication Engineering Jaypee University of Information Technology Waknaghat Himachal Pradesh India

ISBN: (纸本)9781509036707

Our country has vast potential to come up as a cardinal exporter of agricultural produce, but lack of quick quality evaluation techniques, huge losses in processing and handling after harvesting, diseased crop etc. result in a lower contribution to global market. The tomato crop is often infected by a disease, where plant's leaves get covered with spots of colors dark brown with purple border and light grey center; termed as Septoria Leaf Spot. It causes the leaves to turn yellow, but most damage occurs due to loss of leaves by infection. In this paper, tomato maturity based on color and fungal infection in the tomato leaves is determined. Initially thresholding algorithm was performed to determine the maturity of tomato. To make the system more generalized and self-adapting a shift to k-means clustering algorithm is made. Finally a comparative analysis of both the methods was done to analyze which method is more suitable in different conditions. Also an unconventional machine vision system has been suggested that scrutinizes the leaves emerging out of the soil and depending upon leaf spots, it analyzes the nature of fungus and its depth into the stem of tomato. k-means algorithm along with thresholding is used for segmentation of image and eventually identifying fungus. The fungus part that is segmented, is then studied to derive the percentage of presence.

关键词： Decision support systems Clustering algorithms Diseases Agriculture image color analysis Algorithm design and analysis image segmentation

来源：评论

学校读者我要写书评

暂无评论

Energy Efficient Techniques using FFT for Deep Convolutional Neural Networks

Energy Efficient Techniques using FFT for Deep Convolutional...

引用

International conference on Advanced Technologies for Communications (ATC)

作者： Nhan Nguyen-Thanh Han Le-Duc Duc-Tuyen Ta Van-Tam Nguyen Univ Paris Saclay CNRS LTCI Telecom ParisTech F-75013 Paris France Stanford Univ Dept Elect Engn Stanford CA 94305 USA

ISBN: (纸本)9781509027118

Deep convolutional neural networks (CNNs) has been developed for a wide range of applications such as image recognition, nature language processing, etc. However, the deployment of deep CNNs in home and mobile devices remains challenging due to substantial requirements for computing resources and energy needed for the computation of high-dimensional convolutions. In this paper, we propose a novel approach designed to minimize energy consumption in the computation of convolutions in deep CNNs. The proposed solution includes (i) an optimal selection method for Fast Fourier Transform (FFT) configuration associated with splitting input feature maps, (ii) a reconfigurable hardware architecture for computing high-dimensional convolutions based on 2D-FFT, and (iii) an optimal pipeline data movement scheduling. The FFT size selecting method enables us to determine the optimal length of the split input for the lowest energy consumption. The hardware architecture contains a processing engine (PE) array, whose PEs are connected to form parallel flexible-length Radix-2 single-delay feedback lines, enabling the computation of variable-size 2D-FFT. The pipeline data movement scheduling optimizes the transition between row-wise FFT and column-wise FFT in a 2D-FFT process and minimizes the required data access for the element-wise accumulation across input channels. Using simulations, we demonstrated that the proposed framework improves the energy consumption by 89.7% in the inference case.

关键词： Computer architecture Hardware Radio frequency Pipelines Clocks Delays Neural networks Fast Fourier transform pipeline Computer Architecture Neural network Timing devices radiofrequency Computer hardware energy consumption delay piping selection methods

来源：评论

学校读者我要写书评

暂无评论

A Review on parallel Medical image processing on GPU 4

A Review on Parallel Medical Image Processing on GPU

引用

4th International conference on Software Engineering and Computer Systems (ICSECS)

作者： Khor, Hui Liang Liew, Siau-Chuin Zain, Jasni Mohd. Univ Malaysia Pahang Fac Comp Syst & Software Engn Lebuhraya Tun Razak Kuantan 26300 Pahang Darul Ma Malaysia

ISBN: (纸本)9781467367226

An efficient implementation are necessary, as most medical imaging methods are computational expensive, and the amount of medical imaging data is growing. Graphic processing units (GPUs) can solve large data parallel problems at a higher speed than the traditional CPU, while being more affordable and energy efficient than distributed systems. This review investigates the use of GPUs to accelerate medical imaging methods. A set of criteria for efficient use of GPUs are defined. The review concludes that most medical image processing methods may benefit from GPU processing due to the methods' data parallel structure and high thread count. However, factors such as synchronization, branch divergence and memory usage can limit the speedup.

关键词： parallel computing Medical image processing GPU multicores

来源：评论

学校读者我要写书评

暂无评论

Enabling factor analysis on thousand-subject neuroimaging datasets

Enabling factor analysis on thousand-subject neuroimaging da...

引用

IEEE International conference on Big Data

作者： Michael J. Anderson Mihai Capota Javier S. Turek Xia Zhu Theodore L. Willke Yida Wang Po-Hsuan Chen Jeremy R. Manning Peter J. Ramadge Kenneth A. Norman Parallel Computing Lab Intel Corporation Hillsboro Oregon Princeton University Princeton New Jersey Dartmouth College Hanover New Hampshire

ISBN: (纸本)9781467390064

The scale of functional magnetic resonance image data is rapidly increasing as large multi-subject datasets are becoming widely available and high-resolution scanners are adopted. The inherent low-dimensionality of the information in this data has led neuroscientists to consider factor analysis methods to extract and analyze the underlying brain activity. In this work, we consider two recent multi-subject factor analysis methods: the Shared Response Model and the Hierarchical Topographic Factor Analysis. We perform analytical, algorithmic, and code optimization to enable multi-node parallel implementations to scale. Single-node improvements result in 99χ and 2062x speedups on the two methods, and enables the processing of larger datasets. Our distributed implementations show strong scaling of 3.3x and 5.5χ respectively with 20 nodes on real datasets. We demonstrate weak scaling on a synthetic dataset with 1024 subjects, equivalent in size to the biggest fMRI dataset collected until now, on up to 1024 nodes and 32,768 cores.

关键词： Optimization Computational modeling Neuroimaging Brain modeling Algorithm design and analysis Data models

来源：评论

学校读者我要写书评

暂无评论

INFORMATION-ENTROPY BASED LOAD BALANCING IN parallel ADAPTIVE VOLUME RENDERING

INFORMATION-ENTROPY BASED LOAD BALANCING IN PARALLEL ADAPTIV...

引用

International conference on Interfaces and Human Computer Interaction / International conference on Game and Entertainment Technologies / International conference on Computer Graphics, Visualization, Computer Vision and image processing

作者： Wang, Huawei Ai, Zhiwei Cao, Yi Inst Appl Phys & Computat Math 2 Fenghao East Rd Beijing 100094 Peoples R China

ISBN: (纸本)9789898533388

Aiming at TB-scale time-varying scientific datasets, this paper presents a novel static load balancing scheme based on information entropy to enhance the efficiency of the parallel adaptive volume rendering algorithm. An information-theory model is proposed firstly, and then the information entropy is calculated for each data patch, which is taken as a pre-estimation of the computational amount of ray sampling. According to their computational amounts, the data patches are distributed to the processing cores balancedly, and accordingly load imbalance in parallel rendering is decreased. Compared with the existing methods such as random assignment and ray estimation, the proposed entropy-based load balancing scheme can achieve a rendering speedup ratio of 1.23 similar to 2.84. It is the best choice in interactive volume rendering due to its speedup performance and view independence.

关键词： Load Balancing Information Entropy parallel Volume Rendering View Independence

来源：评论

学校读者我要写书评

暂无评论

Map-Reduce Based Framework for Instrument Detection in Large-Scale Surgical Videos

Map-Reduce Based Framework for Instrument Detection in Large...

引用

International conference on Control Communication & Computing India (ICCC)

作者： Sunny, Basil C. Ramesh, R. Varghese, Abraham Vazhayil, Vikas ASIET Dept CSE Ernakulam Kerala India NIMHANS Dept Neurosurg Bangalore Karnataka India

ISBN: (纸本)9781467373494

Modern digital world produces massive amount of data generally refereed as Big Data, which play important roles in dictating the quality of our lives. Relationships among such data have high value, but extremely complex task to establish. Medical Field is one of the major big data sources which produces big volume of data. Modern surgical tools have the capability to record High Definition(HD) videos during the surgical procedure which enables post surgical reviews. Such tools produces giga bytes(GB) of video footage after every surgery which needs mass storage and complex processing. A major solution for this problem is parallel distributed processing using Hadoop based Map Reduce Framework. This paper proposes a Surgical Video Analysis Framework using Hadoop to analyze large surgical videos, for identifying surgical instruments used. Framework first converts videos into large number of frames and using Hadoop image Process Interface (HIPI) it is converted to HIB image bundles. parallel processing of images in the bundle is done by mappers and identified instrument frame information's are logged. Three different feature extraction methods: Scale-Invariant Feature Transform(SIFT), Speeded Up Robust Features(SURF) with Support Vector Machines(SVM) and Haralick Texture Descriptor with Support Vector Machines(SVM) is used in mappers for local image processing.

关键词： Hadoop Mapreduce HIPI Big data distributed processing

来源：评论

学校读者我要写书评

暂无评论

FANet: Factor Analysis Neural Network 22nd

FANet: Factor Analysis Neural Network

引用

22nd International conference on Neural Information processing (ICONIP)

作者： Huang, Jiawen Yuan, Chun Tsinghua Univ Shenzhen Grad Sch Shenzhen Shenzhen 518055 Guangdong Peoples R China

ISBN: (纸本)9783319265551;9783319265544

A cascaded factor analysis network is proposed in this paper, which is suitable for extracting distributed semantic representations to various problems ranging from digit recognition and image classification to face recognition. There are two key points in this novel model: 1. simplify and accelerate the deep convolution networks with competitive accuracy even state-of-the-art for many general image tasks;2. combine a statistical methodfactor analysis with neural networks for excellent automatically learning ability and abundant semantic information. Experiments on many benchmark visual datasets demonstrate that this simple network performs efficiently and effectively while attaining competitive accuracy to the current state-of-the-art methods.

关键词： Convolutional neural network Factor analysis image classification

来源：评论

学校读者我要写书评

暂无评论

CLASSIFICATION OF TIANGONG-1 HYPERSPECTRAL REMOTE SENSING image VIA CONTEXTUAL SPARSE CODING 14

CLASSIFICATION OF TIANGONG-1 HYPERSPECTRAL REMOTE SENSING IM...

引用

International conference on Machine Learning and Cybernetics (ICMLC)

作者： Lv, Qi Dou, Yong Niu, Xin Xu, Jiaqing Xu, Jinbo Natl Univ Def Technol Sch Comp Sci & Technol Parallel & Distributed Proc Lab Changsha 410073 Hunan Peoples R China Natl Univ Def Technol Sch Comp Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781467372206

The hyperspectral remote sensing is one of the frontier techniques in the remote sensing research fields. Applying the sparse coding model to the hyperspectral remote sensing image processing is a hot topic in hyperspectral information processing. To improve the accuracy of hyperspectral image classification, we propose a classification method based on the spatial-spectral joint contextual sparse coding. Firstly, a dictionary is obtained by training using samples selected from the ground-truth reference data. Then, the sparse coefficients of each pixel are calculated based on the learned dictionary. Afterward, the sparse coefficients are input to the classifier and the final classification result is obtained. The visible and near-infrared hyperspectral remote sensing image collected by Tiangong-1 in Chaoyang District of Beijing is used to evaluate the performance of the proposed approach. Experimental results show that the proposed method yields the best classification performance with the overall accuracy of 95.74% and the Kappa coefficient of 0.9476 in comparison with other classification methods.

关键词： Hyperspectral image Remote sensing Sparse coding

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56页 << < 21 22 23 24 25 26 27 28 29 30 > >>

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：