Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Ozimek, Piotr"'
We present ongoing work to harness biological approaches to achieving highly efficient egocentric perception by combining the space-variant imaging architecture of the mammalian retina with Deep Learning methods. By pre-processing images collected by
Externí odkaz:
http://arxiv.org/abs/1809.01633
Autor:
Ozimek, Piotr Aleksander
This thesis presents a series of investigations into various active vision algorithms. An experimental method for evaluating active vision memory is proposed and used to demonstrate the benefits of a novel memory variant called the WW-LSTM network. A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b5f508bfad2e38eda3c311ac340f921
Publikováno v:
IROS2018 Workshop: Unconventional Sensing and Processing for Robotic Visual Perception, at 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems
We present an approach to efficient visual sensing and perception based on a non-uniformly sampled, biologically inspired, software retina that when combined with a DCNN classifier has enabled megapixel-sized camera input images to be processed in a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::a0c5cc72da27002616e605e36d6f1205
https://eprints.gla.ac.uk/183359/1/183359.pdf
https://eprints.gla.ac.uk/183359/1/183359.pdf
Akademický článek
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Publikováno v:
International Conference on Computer Vision 2017, ICCV 2017, Second International Workshop on Egocentric Perception, Interaction and Computing
We presented the concept of of a software retina, capable\ud of significant visual data reduction in combination with\ud scale and rotation invariance, for applications in egocentric\ud and robot vision at the first EPIC workshop in Amsterdam\ud [9].
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::b8425695d314c69609e6ec3eb2b8f51a
https://eprints.gla.ac.uk/148802/13/148802.pdf
https://eprints.gla.ac.uk/148802/13/148802.pdf
Autor:
Ozimek, Piotr, Siebert, J. Paul
Publikováno v:
BMVC 2017 Workshop on Deep Learning on Irregular Domains
We present a biologically inspired method for pre-processing images applied to CNNs\ud that reduces their memory requirements while increasing their invariance to scale and rotation\ud changes. Our method is based on the mammalian retino-cortical tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::6e7f798ca67321816796a617d7be150a
https://eprints.gla.ac.uk/148797/7/148797.pdf
https://eprints.gla.ac.uk/148797/7/148797.pdf
Akademický článek
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Autor:
Beattie, Scott, Jian, Bin, Alcock, John, Gertsvolf, Marina, Hendricks, Rich, Szymaniec, Krzysztof, Gibble, Kurt
Publikováno v:
Metrologia; Jun2020, Vol. 57 Issue 3, p1-15, 15p
Autor:
Orlof, Jerzy1 (AUTHOR) jerzy.orlof@pk.edu.pl, Ozimek, Paweł1 (AUTHOR), Łabędź, Piotr1 (AUTHOR), Widłak, Adrian1 (AUTHOR), Nytko, Mateusz1 (AUTHOR)
Publikováno v:
Symmetry (20738994). Dec2019, Vol. 11 Issue 12, p1451-1451. 1p.
Publikováno v:
IOP Conference Series: Materials Science & Engineering; 2016, Vol. 113 Issue 1, p1-1, 1p