Fatih Porikli

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Oncel TuzelAppleDirección de correo verificada de apple.com
Salman KhanMBZUAI, Australian National UniversityDirección de correo verificada de anu.edu.au
Shubhankar BorseQualcomm AI ResearchDirección de correo verificada de qti.qualcomm.com
Jianbing ShenProfessor, University of MacauDirección de correo verificada de um.edu.mo
Hong (Herbert) CaiQualcomm AI ResearchDirección de correo verificada de qti.qualcomm.com
Peter MeerRutgers UniversityDirección de correo verificada de soe.rutgers.edu
Ling Shao, Fellow of IEEE/IAPRGeneral Terminus Technologies; Founder/Initiator of IIAI/MBZUAIDirección de correo verificada de inceptioniai.org
Mehrtash HarandiDepartment of Electrical and Computer Systems Engineering, Monash UniversityDirección de correo verificada de monash.edu
Saeed AnwarAustralian National UniversityDirección de correo verificada de anu.edu.au
Xin YuThe University of QueenslandDirección de correo verificada de uq.edu.au
Matej KristanFull Professor at Faculty of computer and information science, University of LjubljanaDirección de correo verificada de fri.uni-lj.si
Jiri MatasProfessor, Czech Technical UniversityDirección de correo verificada de cmp.felk.cvut.cz
Ales LeonardisProfessor of Computer ScienceDirección de correo verificada de cs.bham.ac.uk
Roman PflugfelderMarie Curie Fellow at TUM/TechnionDirección de correo verificada de tum.de
Georg NebehayFormer PhD Student at AIT Austrian Institute of TechnologyDirección de correo verificada de ait.ac.at
Muzammal NaseerAsst. Professor, Khalifa UniversityDirección de correo verificada de ku.ac.ae
Tomáš VojířCenter for Machine Perception, Czech Technical University in PragueDirección de correo verificada de cmp.felk.cvut.cz
Debasmit DasAI Researcher, QualcommDirección de correo verificada de qti.qualcomm.com
Ajay J JoshiUniversity of Minnesota, Twin CitiesDirección de correo verificada de cs.umn.edu
Munawar HayatQualcommDirección de correo verificada de qti.qualcomm.com

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Fatih Porikli

Qualcomm, Australian National University

Dirección de correo verificada de anu.edu.au - Página principal

Computer Vision Image Processing Manifold Learning Dictionary Learning Deep Learning


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Image segmentation using deep learning: A survey S Minaee, Y Boykov, F Porikli, A Plaza, N Kehtarnavaz, D Terzopoulos IEEE transactions on pattern analysis and machine intelligence 44 (7), 3523-3542, 2021	4037	2021
The visual object tracking vot2015 challenge results M Kristan, J Matas, A Leonardis, M Felsberg, L Cehovin, G Fernandez, ... Proceedings of the IEEE international conference on computer vision …, 2015	2188	2015
Region covariance: A fast descriptor for detection and classification O Tuzel, F Porikli, P Meer Computer Vision–ECCV 2006: 9th European Conference on Computer Vision, Graz …, 2006	1854	2006
Pedestrian detection via classification on riemannian manifolds O Tuzel, F Porikli, P Meer IEEE transactions on pattern analysis and machine intelligence 30 (10), 1713 …, 2008	1305	2008
Changedetection. net: A new change detection benchmark dataset N Goyette, PM Jodoin, F Porikli, J Konrad, P Ishwar 2012 IEEE computer society conference on computer vision and pattern …, 2012	1109	2012
Integral histogram: A fast way to extract histograms in cartesian spaces F Porikli 2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005	1102	2005
CDnet 2014: An expanded change detection benchmark dataset Y Wang, PM Jodoin, F Porikli, J Konrad, Y Benezeth, P Ishwar Proceedings of the IEEE conference on computer vision and pattern …, 2014	1095	2014
Saliency-aware geodesic video object segmentation W Wang, J Shen, F Porikli Proceedings of the IEEE conference on computer vision and pattern …, 2015	1042	2015
Multi-class active learning for image classification AJ Joshi, F Porikli, N Papanikolopoulos 2009 ieee conference on computer vision and pattern recognition, 2372-2379, 2009	935	2009
Underwater scene prior inspired deep underwater image and video enhancement C Li, S Anwar, F Porikli Pattern Recognition 98, 107038, 2020	883	2020
Covariance tracking using model update based on lie algebra F Porikli, O Tuzel, P Meer 2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006	859	2006
Going deeper into action recognition: A survey S Herath, M Harandi, F Porikli Image and vision computing 60, 4-21, 2017	821	2017
A novel performance evaluation methodology for single-target trackers M Kristan, J Matas, A Leonardis, T Vojíř, R Pflugfelder, G Fernandez, ... IEEE transactions on pattern analysis and machine intelligence 38 (11), 2137 …, 2016	748	2016
Support vector machines: Theory and applications T Evgeniou, M Pontil Advanced course on artificial intelligence, 249-257, 1999	743	1999
Human detection via classification on riemannian manifolds O Tuzel, F Porikli, P Meer 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007	675	2007
See more, know more: Unsupervised video object segmentation with co-attention siamese networks X Lu, W Wang, C Ma, J Shen, L Shao, F Porikli Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019	581	2019
Constant time O (1) bilateral filtering F Porikli 2008 IEEE conference on computer vision and pattern recognition, 1-8, 2008	476	2008
LightenNet: A convolutional neural network for weakly illuminated image enhancement C Li, J Guo, F Porikli, Y Pang Pattern recognition letters 104, 15-22, 2018	475	2018
Less is more: Towards compact cnns H Zhou, JM Alvarez, F Porikli Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016	408	2016
Ultra-resolving face images by discriminative generative networks X Yu, F Porikli European conference on computer vision, 318-333, 2016	343	2016

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