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检索条件"机构=Visualization and Computer Graphics Research Group Department of Computer Science"
95 条 记 录,以下是11-20 订阅
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SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data
SynFacePAD 2023: Competition on Face Presentation Attack Det...
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IEEE International Joint Conference on Biometrics (IJCB)
作者: Meiling Fang Marco Huber Julian Fierrez Raghavendra Ramachandra Naser Damer Alhasan Alkhaddour Maksim Kasantcev Vasiliy Pryadchenko Ziyuan Yang Huijie Huangfu Yingyu Chen Yi Zhang Yuchen Pan Junjun Jiang Xianming Liu Xianyun Sun Caiyong Wang Xingyu Liu Zhaohua Chang Guangzhe Zhao Juan Tapia Lazaro Gonzalez-Soler Carlos Aravena Daniel Schulz Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany Biometrics and Data Pattern Analytics Lab Universidad Autonoma de Madrid Spain Norwegian University of Science and Technology (NTNU) Norway ID R&D Inc New York US School of Cyber Science and Engineering Sichuan University Chengdu China School of Computer Science and Technology Harbin Institute of Technology Harbin China School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture China Biometrics and Security Research Group Hochschule Darmstadt Darmstadt Germany I+D Vision Center Santiago Chile
This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 International Joint Conference on Biometrics (IJ...
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The Unconstrained Ear Recognition Challenge 2023: Maximizing Performance and Minimizing Bias*
The Unconstrained Ear Recognition Challenge 2023: Maximizing...
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IEEE International Joint Conference on Biometrics (IJCB)
作者: Ž. Emeršić T. Ohki M. Akasaka T. Arakawa S. Maeda M. Okano Y. Sato A. George S. Marcel I. I. Ganapathi S. S. Ali S. Javed N. Werghi S. G. Işık E. Sarıtaş H. K. Ekenel V. Hudovernik J. N. Kolf F. Boutros N. Damer G. Sharma A. Kamboj A. Nigam D. K. Jain G. Cámara-Chávez P. Peer V. Štruc University of Ljubljana (UL SI) Shizuoka University (SU JP) Idiap Research Institute (IDIAP CH) Electrical Engineering and Computer Science Department Khalifa University (KU UAE) Department of Computer Engineering (ITU TR) Istanbul Technical University Microelectronic Guidance and Electro-Optical Group ASELSAN Fraunhofer Institute for Computer Graphics Research IGD (IGD DE) Technische Universität Darmstadt (TUD DE) Indian Institute of Technology Mandi (IIT IN) HCL Imaging and Robotics R&D Lab (HCL IN) School of Artificial Intelligence Dalian University of Technology (DLUT CN) Federal University of Ouro Preto (UFOP BR)
The paper provides a summary of the 2023 Unconstrained Ear Recognition Challenge (UERC), a benchmarking effort focused on ear recognition from images acquired in uncontrolled environments. The objective of the challen...
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Multipla: Multiscale Pangenomic Locus Analysis
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computer graphics Forum 2025年
作者: van den Brandt, A. Ståhlbom, E. van Workum, F.J.M. van de Wetering, H. Lundström, C. Smit, S. Vilanova, A. Department of Mathematics and Computer Science Eindhoven University of Technology Netherlands Bioinformatics Group Wageningen University & Research Netherlands Department of Science and Technology Linköping University Sweden Sectra AB Sweden Center for Medical Image Science and Visualization Linköping University Sweden
Comparing gene organization across genomic sequences reveals insights into evolutionary and functional diversity among different organisms and varieties. Performing this task across many sequences, such as from a pang... 详细信息
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EFaR 2023: Efficient Face Recognition Competition
EFaR 2023: Efficient Face Recognition Competition
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IEEE International Joint Conference on Biometrics (IJCB)
作者: Jan Niklas Kolf Fadi Boutros Jurek Elliesen Markus Theuerkauf Naser Damer Mohamad Alansari Oussama Abdul Hay Sara Alansari Sajid Javed Naoufel Werghi Klemen Grm Vitomir Štruc Fernando Alonso-Fernandez Kevin Hernandez Diaz Josef Bigun Anjith George Christophe Ecabert Hatef Otroshi Shahreza Ketan Kotwal Sébastien Marcel Iurii Medvedev Bo Jin Diogo Nunes Ahmad Hassanpour Pankaj Khatiwada Aafan Ahmad Toor Bian Yang Fraunhofer Institute for Computer Graphics Research IGD Germany TU Darmstadt Germany Department of Electrical and Computer Engineering Khalifa University Abu Dhabi United Arab Emirates Laboratory for Machine Intelligence Faculty of Electrical Engineering University of Ljubljana Slovenia Halmstad University Sweden Idiap Research Institute Martigny Switzerland École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Université de Lausanne (UNIL) Lausanne Switzerland Institute of Systems and Robotics University of Coimbra Coimbra Portugal Department of Information Security and Communication Technology eHealth and Welfare Security Group Norwegian University of Science and Technology Norway
This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different ...
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Efficient MedSAMs: Segment Anything in Medical Images on Laptop
arXiv
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arXiv 2024年
作者: Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to thei... 详细信息
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A generative artificial intelligence framework based on a molecular diffusion model for the design of metal–organic frameworks for carbon capture
arXiv
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arXiv 2023年
作者: Park, Hyun Yan, Xiaoli Zhu, Ruijie Huerta, Eliu A. Chaudhuri, Santanu Cooper, Donny Foster, Ian Tajkhorshid, Emad Data Science and Learning Division Argonne National Laboratory LemontIL60439 United States Theoretical and Computational Biophysics Group NIH Resource Center for Macromolecular Modeling and Visualization Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Center for Biophysics and Quantitative Biology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Multiscale Materials and Manufacturing Lab University of Illinois Chicago ChicagoIL60607 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Computer Science University of Chicago ChicagoIL60637 United States Department of Physics University of Illinois at Urbana-Champaign UrbanaIL61801 United States Computational Science and Engineering Data Science and AI Department TotalEnergies EP Research & Technology USA LLC HoustonTX77002 United States Department of Biochemistry University of Illinois at Urbana-Champaign UrbanaIL61801 United States
Metal–organic frameworks (MOFs) exhibit great promise for CO2 capture. However, finding the best performing materials poses computational and experimental grand challenges in view of the vast chemical space of potent... 详细信息
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Guest editors' introduction: Special section on IEEE PacificVis 2019
IEEE Pacific Visualization Symposium
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IEEE Pacific visualization Symposium 2019年 2019-April卷 XIV-XV页
作者: Maciejewski, Ross Seo, Jinwook Westermann, Rüdiger School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ United States Department of Computer Science and Engineering Seoul National University Seoul Korea Republic of Computer Graphics and Visualization Group Technische Universitat Munchen Garching Germany
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Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction  1
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1st International Workshop on Graph Learning in Medical Imaging, GLMI 2019 held in conjunction with the 22nd International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2019
作者: Dzyubachyk, Oleh Koolstra, Kirsten Pezzotti, Nicola Lelieveldt, Boudewijn P. F. Webb, Andrew Börnert, Peter Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands C.J. Gorter Center for High Field MRI Department of Radiology Leiden University Medical Center Leiden Netherlands Computer Graphics and Visualization Group Delft University of Technology Delft Netherlands Philips Research Eindhoven Eindhoven Netherlands Intelligent Systems Department Delft University of Technology Delft Netherlands Philips Research Hamburg Hamburg Germany
Quality assessment of different Magnetic Resonance Fingerprinting (MRF) sequences and their corresponding dictionaries remains an unsolved problem. In this work we present a method in which we approach analysis of MRF... 详细信息
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Comparative cellular analysis of motor cortex in human, marmoset and mouse (vol 598, pg 111, 2021)
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NATURE 2022年 第7904期604卷 E8-E8页
作者: Bakken, Trygve E. Jorstad, Nikolas L. Hu, Qiwen Lake, Blue B. Tian, Wei Kalmbach, Brian E. Crow, Megan Hodge, Rebecca D. Krienen, Fenna M. Sorensen, Staci A. Eggermont, Jeroen Yao, Zizhen Aevermann, Brian D. Aldridge, Andrew I. Bartlett, Anna Bertagnolli, Darren Casper, Tamara Castanon, Rosa G. Crichton, Kirsten Daigle, Tanya L. Dalley, Rachel Dee, Nick Dembrow, Nikolai Diep, Dinh Ding, Song-Lin Dong, Weixiu Fang, Rongxin Fischer, Stephan Goldman, Melissa Goldy, Jeff Graybuck, Lucas T. Herb, Brian R. Hou, Xiaomeng Kancherla, Jayaram Kroll, Matthew Lathia, Kanan van Lew, Baldur Li, Yang Eric Liu, Christine S. Liu, Hanqing Lucero, Jacinta D. Mahurkar, Anup McMillen, Delissa Miller, Jeremy A. Moussa, Marmar Nery, Joseph R. Nicovich, Philip R. Niu, Sheng-Yong Orvis, Joshua Osteen, Julia K. Owen, Scott Palmer, Carter R. Pham, Thanh Plongthongkum, Nongluk Poirion, Olivier Reed, Nora M. Rimorin, Christine Rivkin, Angeline Romanow, William J. Sedeno-Cortes, Adriana E. Siletti, Kimberly Somasundaram, Saroja Sulc, Josef Tieu, Michael Torkelson, Amy Tung, Herman Wang, Xinxin Xie, Fangming Yanny, Anna Marie Zhang, Renee Ament, Seth A. Behrens, M. Margarita Bravo, Hector Corrada Chun, Jerold Dobin, Alexander Gillis, Jesse Hertzano, Ronna Hof, Patrick R. Hollt, Thomas Horwitz, Gregory D. Keene, C. Dirk Kharchenko, Peter V. Ko, Andrew L. Lelieveldt, Boudewijn P. Luo, Chongyuan Mukamel, Eran A. Pinto-Duarte, Antonio Preiss, Sebastian Regev, Aviv Ren, Bing Scheuermann, Richard H. Smith, Kimberly Spain, William J. White, Owen R. Koch, Christof Hawrylycz, Michael Tasic, Bosiljka Macosko, Evan Z. McCarroll, Steven A. Ting, Jonathan T. Zeng, Hongkui Zhang, Kun Feng, Guoping Ecker, Joseph R. Linnarsson, Sten Lein, Ed S. Allen Institute for Brain Science Seattle WA USA Department of Physiology and Biophysics University of Washington Seattle WA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Bioengineering University of California San Diego La Jolla CA USA The Salk Institute for Biological Studies La Jolla CA USA Epilepsy Center of Excellence Department of Veterans Affairs Medical Center Seattle WA USA Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory Cold Spring Harbor NY USA Department of Genetics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA LKEB Department of Radiology Leiden University Medical Center Leiden The Netherlands Pattern Recognition and Bioinformatics group Delft University of Technology Delft The Netherlands J. Craig Venter Institute La Jolla CA USA Department of Pathology University of California San Diego CA USA Division of Vaccine Discovery La Jolla Institute for Immunology La Jolla CA USA Genomic Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA Computer Science and Engineering Program University of California San Diego La Jolla CA USA Howard Hughes Medical Institute The Salk Institute for Biological Studies La Jolla CA USA Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA Institute for Genomes Sciences University of Maryland School of Medicine Baltimore MD USA Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA Ludwig Institute for Cancer Research La Jolla CA USA Department of Computer Science University of Maryland College Park College Park MD USA Sanford Burnham Prebys Medical Discovery Institute La Jolla CA USA Biomedical Sciences Program School of Medicine University of California San Diego La Jolla CA USA University of Connecticut Storrs CT USA Department
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Exploring Uncertainty in Image Segmentation Ensembles
Exploring Uncertainty in Image Segmentation Ensembles
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20th Eurographics/IEEE VGTC Conference on visualization, EuroVis 2018
作者: Fröhler, B. Möller, T. Weissenböck, J. Hege, H.-C. Kastner, J. Heinzl, C. Research Group Computed Tomography University of Applied Sciences Upper Austria Austria Visualization and Data Analysis Research Group Faculty of Computer Science University of Vienna Austria Visual Data Analysis Department Zuse Institute Berlin Germany
Finding the most accurate image segmentation involves analyzing results from different algorithms or parameterizations. In this work, we identify different types of uncertainty in this analysis that are represented by...
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