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检索条件"机构=The Computer Vision And Robotics Research Laboratory"
233 条 记 录,以下是41-50 订阅
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Comprehensive parameter sweep for learning-based detector on traffic lights  12th
Comprehensive parameter sweep for learning-based detector on...
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12th International Symposium on Visual Computing, ISVC 2016
作者: Jensen, Morten B. Philipsen, Mark P. Moeslund, Thomas B. Trivedi, Mohan Visual Analysis of People Laboratory Aalborg University Aalborg Denmark Computer Vision and Robotics Research Laboratory UC San Diego La Jolla United States
Determining the optimal parameters for a given detection algorithm is not straightforward and what ends up as the final values is mostly based on experience and heuristics. In this paper we investigate the influence o... 详细信息
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Augmented Cognition via Brainwave Entrainment in Virtual Reality: An Open, Integrated Brain Augmentation in a Neuroscience System Approach
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Augmented Human research 2017年 第1期2卷 1-14页
作者: Emanuele Argento George Papagiannakis Eva Baka Michail Maniadakis Panos Trahanias Michael Sfakianakis Ioannis Nestoros Computational Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology Heraklion Greece Department of Computer Science University of Crete Heraklion Greece Department of Medicine University of Greece Heraklion Greece Department of Business Administration University of Piraeus Piraeus Greece Synchronal Amphiaraia University of Crete Snip-off Company Athens Greece
Building on augmented cognition theory and technology, our novel contribution in this work enables accelerated, certain brain functions related to task performance as well as their enhancement. We integrated in an ope...
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Detection and localization with multi-scale models
Detection and localization with multi-scale models
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International Conference on Pattern Recognition
作者: Eshed Ohn-Bar Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego
Object detection and localization in images involve a multi-scale reasoning process. First, responses of object detectors are known to vary with image scale. Second, contextual relationships on a part-level, object-le... 详细信息
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What makes an on-road object important?
What makes an on-road object important?
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International Conference on Pattern Recognition
作者: Eshed Ohn-Bar Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego
Human drivers continuously attend to important scene elements in order to safely and smoothly navigate in intricate environments and under uncertainty. This paper develops a human-centric framework for object recognit... 详细信息
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Robust face recognition using key-point descriptors  10
Robust face recognition using key-point descriptors
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10th International Conference on computer vision Theory and Applications, VISAPP 2015
作者: Klemm, Soeren Andreu, Yasmina Henriquez, Pedro Matuszewski, Bogdan J. Robotics and Computer Vision Research Laboratory School of Computing Engineering and Physical Sciences University of Central Lancashire Preston United Kingdom
Key-point based techniques have demonstrated a good performance for recognition of various objects in numerous computer vision applications. This paper investigates the use of some of the most popular key-point descri... 详细信息
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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
arXiv
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arXiv 2018年
作者: Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrot... 详细信息
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vision System and Depth Processing for DRC-HUBO+
Vision System and Depth Processing for DRC-HUBO+
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IEEE International Conference on robotics and Automation
作者: Inwook Shim Seunghak Shin Yunsu Bok Kyungdon Joo Dong-Geol Choi Joon-Young Lee Jaesik Park Jun-Ho Oh In So Kweon Robotics and Computer Vision Laboratory Dep. of EE KAIST Daejeon 305-701 Korea Adobe Research San Jose CA 95110 United States Intel Labs Santa Clara CA 95054 United States Humanoid Research Center Dep. of ME KAIST Daejeon 305-701 Korea
This paper presents a vision system and a depth processing algorithm for DRC-HUBO+, the winner of the DRC finals 2015. Our system is designed to reliably capture 3D information of a scene and objects and to be robust ... 详细信息
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Traffic Light Detection: A Learning Algorithm and Evaluations on Challenging Dataset
Traffic Light Detection: A Learning Algorithm and Evaluation...
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International Conference on Intelligent Transportation
作者: Mark Philip Philipsen Morten Bornø Jensen Andreas Møgelmose Thomas B. Moeslund Mohan M. Trivedi UC San Diego Computer Vision and Robotics Research Laboratory La Jolla CA USA Visual Analysis of People Laboratory Aalborg University Aalborg Denmark
Traffic light recognition (TLR) is an integral part of any intelligent vehicle, which must function in the existing infrastructure. Pedestrian and sign detection have recently seen great improvements due to the introd... 详细信息
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Day and night-time drive analysis using stereo vision for naturalistic driving studies
Day and night-time drive analysis using stereo vision for na...
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IEEE Symposium on Intelligent Vehicle
作者: Mark P. Philipsen Morten B. Jensen Ravi K. Satzoda Mohan M. Trivedi Andreas Møgelmose Thomas B. Moeslund Computer Vision and Robotics Research Laboratory La Jolla CA USA Visual Analysis of People Laboratory Aalborg University Aal-borg Denmark Aalborg Universitet Aalborg DK
In order to understand dangerous situations in the driving environment, naturalistic driving studies (NDS) are conducted by collecting and analyzing data from sensors looking inside and outside of the car. Manually pr... 详细信息
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Head pose tracking for immersive applications
Head pose tracking for immersive applications
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作者: Henriquez, Pedro Higuera, Oscar Matuszewski, Bogdan J. Robotics and Computer Vision Research Laboratory School of Computing Engineering and Physical Sciences University of Central Lancashire United Kingdom
The paper describes a 3D head pose tracking system designed for immersive applications. The proposed system is based on a random forest's head detection and pose regression model. The main novel contributions incl... 详细信息
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