Graham Taylor
Graham Taylor
University of Guelph and Vector Institute for Artificial Intelligence
Verified email at uoguelph.ca - Homepage
TitleCited byYear
Deconvolutional networks
MD Zeiler, D Krishnan, GW Taylor, R Fergus
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on …, 2010
10312010
Adaptive deconvolutional networks for mid and high level feature learning.
MD Zeiler, GW Taylor, R Fergus
ICCV 1 (2), 6, 2011
8102011
Modeling human motion using binary latent variables
GW Taylor, GE Hinton, ST Roweis
Advances in neural information processing systems, 1345-1352, 2007
7272007
Convolutional learning of spatio-temporal features
GW Taylor, R Fergus, Y LeCun, C Bregler
European conference on computer vision, 140-153, 2010
5672010
The recurrent temporal restricted boltzmann machine
I Sutskever, GE Hinton, GW Taylor
Advances in neural information processing systems, 1601-1608, 2009
3722009
Factored conditional restricted Boltzmann machines for modeling motion style
GW Taylor, GE Hinton
Proceedings of the 26th annual international conference on machine learning …, 2009
3512009
Improved regularization of convolutional neural networks with cutout
T DeVries, GW Taylor
arXiv preprint arXiv:1708.04552, 2017
2812017
Multi-scale deep learning for gesture detection and localization
N Neverova, C Wolf, GW Taylor, F Nebout
European Conference on Computer Vision, 474-490, 2014
1732014
Moddrop: adaptive multi-modal gesture recognition
N Neverova, C Wolf, G Taylor, F Nebout
IEEE Transactions on Pattern Analysis and Machine Intelligence 38 (8), 1692-1706, 2015
1672015
Dynamical binary latent variable models for 3d human pose tracking
GW Taylor, L Sigal, DJ Fleet, GE Hinton
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
1432010
Learning human pose estimation features with convolutional networks
A Jain, J Tompson, M Andriluka, GW Taylor, C Bregler
arXiv preprint arXiv:1312.7302, 2013
1372013
Two distributed-state models for generating high-dimensional time series
GW Taylor, GE Hinton, ST Roweis
Journal of Machine Learning Research 12 (Mar), 1025-1068, 2011
1082011
Deep learning on fpgas: Past, present, and future
G Lacey, GW Taylor, S Areibi
arXiv preprint arXiv:1602.04283, 2016
982016
Learning human identity from motion patterns
N Neverova, C Wolf, G Lacey, L Fridman, D Chandra, B Barbello, G Taylor
IEEE Access 4, 1810-1820, 2016
942016
Automatic moth detection from trap images for pest management
W Ding, G Taylor
Computers and Electronics in Agriculture 123, 17-28, 2016
912016
Dataset augmentation in feature space
T DeVries, GW Taylor
arXiv preprint arXiv:1702.05538, 2017
892017
Deep multimodal learning: A survey on recent advances and trends
D Ramachandram, GW Taylor
IEEE Signal Processing Magazine 34 (6), 96-108, 2017
682017
Learning confidence for out-of-distribution detection in neural networks
T DeVries, GW Taylor
arXiv preprint arXiv:1802.04865, 2018
672018
Caffeinated FPGAs: FPGA framework for convolutional neural networks
R DiCecco, G Lacey, J Vasiljevic, P Chow, G Taylor, S Areibi
2016 International Conference on Field-Programmable Technology (FPT), 265-268, 2016
572016
A multi-scale approach to gesture detection and recognition
N Neverova, C Wolf, G Paci, G Sommavilla, G Taylor, F Nebout
Proceedings of the IEEE International Conference on Computer Vision …, 2013
562013
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Articles 1–20