咨询与建议

限定检索结果

文献类型

  • 239 篇 会议
  • 147 篇 期刊文献

馆藏范围

  • 386 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 265 篇 工学
    • 177 篇 计算机科学与技术...
    • 147 篇 软件工程
    • 48 篇 生物医学工程(可授...
    • 44 篇 光学工程
    • 39 篇 生物工程
    • 35 篇 电子科学与技术(可...
    • 33 篇 机械工程
    • 33 篇 控制科学与工程
    • 28 篇 电气工程
    • 28 篇 信息与通信工程
    • 17 篇 化学工程与技术
    • 14 篇 材料科学与工程(可...
    • 13 篇 仪器科学与技术
    • 13 篇 土木工程
    • 11 篇 动力工程及工程热...
    • 11 篇 建筑学
  • 169 篇 理学
    • 91 篇 数学
    • 59 篇 物理学
    • 42 篇 生物学
    • 18 篇 化学
    • 13 篇 统计学(可授理学、...
  • 68 篇 管理学
    • 45 篇 管理科学与工程(可...
    • 27 篇 图书情报与档案管...
    • 17 篇 工商管理
  • 33 篇 医学
    • 32 篇 临床医学
    • 29 篇 基础医学(可授医学...
    • 24 篇 药学(可授医学、理...
  • 11 篇 教育学
    • 10 篇 教育学
  • 10 篇 经济学
    • 10 篇 应用经济学
  • 10 篇 法学
    • 9 篇 社会学
  • 8 篇 农学

主题

  • 14 篇 visualization
  • 13 篇 computer graphic...
  • 12 篇 shape
  • 10 篇 cameras
  • 9 篇 image segmentati...
  • 9 篇 hardware
  • 9 篇 computer vision
  • 8 篇 face recognition
  • 8 篇 image reconstruc...
  • 7 篇 laboratories
  • 7 篇 geometry
  • 6 篇 magnetic resonan...
  • 6 篇 neural networks
  • 6 篇 data mining
  • 6 篇 computational mo...
  • 6 篇 algorithm design...
  • 6 篇 training
  • 5 篇 human computer i...
  • 5 篇 reverse engineer...
  • 5 篇 virtual reality

机构

  • 14 篇 fraunhofer insti...
  • 10 篇 institute for co...
  • 8 篇 biotechmed-graz ...
  • 8 篇 institute of gra...
  • 7 篇 institute of com...
  • 6 篇 fraunhofer insti...
  • 6 篇 department of co...
  • 6 篇 college of aeros...
  • 6 篇 school of mechan...
  • 5 篇 institute of com...
  • 5 篇 national univers...
  • 5 篇 regensburg unive...
  • 5 篇 verigram llc
  • 5 篇 faculty of elect...
  • 5 篇 university of mo...
  • 4 篇 institute of opt...
  • 4 篇 remote sensing t...
  • 4 篇 division of radi...
  • 4 篇 computer graphic...
  • 4 篇 institute for me...

作者

  • 20 篇 egger jan
  • 13 篇 damer naser
  • 13 篇 chen xiaojun
  • 9 篇 schmalstieg diet...
  • 9 篇 naser damer
  • 7 篇 gsaxner christin...
  • 7 篇 fierrez julian
  • 6 篇 pepe antonio
  • 6 篇 pock thomas
  • 6 篇 song haiyu
  • 6 篇 wallner jürgen
  • 6 篇 štruc vitomir
  • 6 篇 wang pengjie
  • 6 篇 li xiongfei
  • 5 篇 li li
  • 5 篇 hann alexander
  • 5 篇 li xing
  • 5 篇 bischof horst
  • 5 篇 gall markus
  • 4 篇 rasnayaka sanka

语言

  • 372 篇 英文
  • 9 篇 其他
  • 4 篇 中文
  • 1 篇 法文
检索条件"机构=Institute of Engineering and Computer Graphics"
386 条 记 录,以下是121-130 订阅
排序:
Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data
arXiv
收藏 引用
arXiv 2019年
作者: Gsaxner, Christina Roth, Peter M. Wallner, Jürgen Egger, Jan Institute for Computer Graphics and Vision Faculty of Computer Science and Biomedical Engineering Graz University of Technology Graz Austria Computer Algorithms for Medicine Laboratory Graz Austria Department of Oral & Maxillofacial Surgery Medical University of Graz Auenbruggerplatz Styria Austria
We present an approach for fully automatic urinary bladder segmentation in CT images with artificial neural networks in this study. Automatic medical image analysis has become an invaluable tool in the different treat... 详细信息
来源: 评论
Evaluation of the thermal processes and simulation methods for additive manufacturing based on the geometry voxel representation
收藏 引用
Key engineering Materials 2018年 第1期771卷 91-96页
作者: Ripetskiy, Andrey Zelenov, Sergey Kuznetsova, Ekaterina Rabinskiy, Lev Department of Engineering and Computer Graphics Moscow Aviation Institute National Research University 4 Volokolamskoe highway Moscow125993 Russia Department of Engineering Graphics Moscow Aviation Institute National Research University 4 Volokolamskoe highway Moscow125993 Russia Faculty of Applied Mechanics Moscow Aviation Institute National Research University 4 Volokolamskoe highway Moscow125993 Russia Department of Advanced Materials and Technologies for Aerospace Application Moscow Aviation Institute National Research University 4 Volokolamskoe highway Moscow125993 Russia
Currently, the technological and hardware base additive production technologies are actively developing. The emergence of new developments in the field of materials science and their possibilities for the creation of ... 详细信息
来源: 评论
Deep learning - A first meta-survey of selected reviews across scientific disciplines, their commonalities, challenges and research impact
arXiv
收藏 引用
arXiv 2020年
作者: Egger, Jan Pepe, Antonio Gsaxner, Christina Jin, Yuan Li, Jianning Kern, Roman Institute of Computer Graphics and Vision Faculty of Computer Science and Biomedical Engineering Graz University of Technology Graz Austria Computer Algorithms for Medicine Laboratory Graz Austria Department of Oral and Maxillofacial Surgery Medical University of Graz Graz Austria University Medicine Essen Essen Germany Research Center for Connected Healthcare Big Data Zhejiang Lab Zhejiang Hangzhou China Research Unit Experimental Neurotraumatology Department of Neurosurgery Medical University of Graz Graz Austria Knowledge Discovery Know-Center Graz Austria Institute of Interactive Systems and Data Science Graz University of Technology Graz Austria
Deep learning belongs to the field of artificial intelligence, where machines perform tasks that typically require some kind of human intelligence. Deep learning tries to achieve this by drawing inspiration from the l... 详细信息
来源: 评论
Medical deep learning-A systematic meta-review
arXiv
收藏 引用
arXiv 2020年
作者: Egger, Jan Gsaxner, Christina Pepe, Antonio Pomykala, Kelsey L. Jonske, Frederic Kurz, Manuel Li, Jianning Kleesiek, Jens Institute of Computer Graphics and Vision Faculty of Computer Science and Biomedical Engineering Graz University of Technology Inffeldgasse 16 Styria Graz8010 Austria Department of Oral & Maxillofacial Surgery Medical University of Graz Auenbruggerplatz 5/1 Styria Graz8036 Austria Computer Algorithms for Medicine Laboratory Styria Graz Austria University Medicine Essen Girardetstraße 2 Essen45131 Germany University Medicine Essen Hufelandstraße 55 Essen45147 Germany Partner Site Essen Hufelandstraße 55 Essen45147 Germany
Deep learning has remarkably impacted several different scientific disciplines over the last few years. For example, in image processing and analysis, deep learning algorithms were able to outperform other cutting-edg... 详细信息
来源: 评论
CG-SENSE revisited: Results from the first ISMRM reproducibility challenge
arXiv
收藏 引用
arXiv 2020年
作者: Maier, Oliver Baete, Steven H. Fyrdahl, Alexander Hammernik, Kerstin Harrevelt, Seb Kasper, Lars Karakuzu, Agah Loecher, Michael Patzig, Franz Tian, Ye Wang, Ke Gallichan, Daniel Uecker, Martin Knoll, Florian Institute of Medical Engineering Graz University of Technology Graz Austria Center for Biomedical Imaging New York University School of Medicine New YorkNY United States Department of Clinical Physiology Karolinska University Hospital Karolinska Institutet Stockholm Sweden Department of Computing Imperial College London London United Kingdom Institute of Computer Graphics and Vision Graz University of Technology Graz Austria Department of Biomedical Engineering Eindhoven University of Technology Eindhoven Netherlands Institute for Biomedical Engineering ETH Zurich University of Zurich Zurich Switzerland Translational Neuromodeling Unit Institute for Biomedical Engineering University of Zurich ETH Zurich Zurich Switzerland NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montréal Montréal Canada Department of Radiology Stanford University StanfordCA United States Department of Radiology and Imaging Sciences University of Utah Salt Lake CityUT United States Ming Hsieh Department of Electrical and Computer Engineering Viterbi School of Engineering University of Southern California Los AngelesCA United States Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA United States Cardiff University Brain Research Imaging Centre Cardiff United Kingdom Institute for Diagnostic and Interventional Radiology University Medical Center Göttingen Göttingen Germany Germany University of Göttingen Germany University of Göttingen Germany
Purpose The aim of this work is to shed light on the issue of reproducibility in MR image reconstruction in the context of a challenge. Participants had to recreate the results of "Advances in sensitivity encodin... 详细信息
来源: 评论
Towards the generation of digital twins for facility management based on 3D point clouds  34
Towards the generation of digital twins for facility managem...
收藏 引用
34th Annual Association of Researchers in Construction Management Conference, ARCOM 2018
作者: Stojanovic, Vladeta Trapp, Matthias Richter, Rico Hagedorn, Benjamin Döllner, Jürgen Computer Graphics Systems Group Hasso Plattner Institute Faculty of Digital Engineering University of Potsdam Prof.-Dr.-Helmert-Straße 2-3 Potsdam14482 Germany
Advances versus adaptation of Industry 4.0 practices in Facility Management (FM) have created usage demand for up-to-date digitized building assets. The use of Building Information Modelling (BIM) for FM in the Operat... 详细信息
来源: 评论
Graph-based parallel large scale structure from motion
arXiv
收藏 引用
arXiv 2019年
作者: Chen, Yu Shen, Shuhan Chen, Yisong Wang, Guoping Graphics and Interactive Lab Department of Computer Science and Technology School of Electronic Engineering and Computer Science Peking University National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China
While Structure from Motion (SfM) achieves great success in 3D reconstruction, it still meets challenges on large scale scenes. In this work, large scale SfM is deemed as a graph problem, and we tackle it in a divide-... 详细信息
来源: 评论
Dualism for CAD-system creation based on natural- intellectual representation
收藏 引用
IOP Conference Series: Materials Science and engineering 2020年 第4期709卷
作者: A I Razumowsky M A Loktev Laboratory of Computer Graphics V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences 65 Profsoyuznaya street Moscow 117997 Russia Department of Engineering Graphics Moscow State Technological University 'STANKIN' Vadkovsky Pereulok 3a. 127055 Moscow Russia
When developing difficultly deterministic software solutions of automated systems, control over the algorithmization and structurization of the task should lie outside the control of the formal interconnection of oper...
来源: 评论
Memorizing all for implicit discourse relation recognition
arXiv
收藏 引用
arXiv 2019年
作者: Bai, Hongxiao Zhao, Hai Zhao, Junhan Department of Computer Science and Engineering Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence Ai Institute Shanghai Jiao Tong University Computer Graphics Technology Purdue University West LafayetteIN United States
Implicit discourse relation recognition is a challenging task due to the absence of the nec-essary informative clue from explicit connec-tives. The prediction of relations requires a deep understanding of the semantic... 详细信息
来源: 评论
Deep learning methods for parallel magnetic resonance image reconstruction
arXiv
收藏 引用
arXiv 2019年
作者: Knoll, Florian Hammernik, Kerstin Zhang, Chi Moeller, Steen Pock, Thomas Sodickson, Daniel K. Akçakaya, Mehmet Center for Biomedical Imaging Department of Radiology New York University Institute of Computer Vision and Graphics Graz University of Technology Department of Electrical and Computer Engineering Center for Magnetic Resonance Research University of Minnesota MinneapolisMN United States Center for Magnetic Resonance Research University of Minnesota MinneapolisMN United States
Following the success of deep learning in a wide range of applications, neural network-based machine learning techniques have received interest as a means of accelerating magnetic resonance imaging (MRI). A number of ... 详细信息
来源: 评论