Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Dimitrios Korkinof"'
Publikováno v:
Argument & Computation, Vol 8, Iss 1, Pp 89-89 (2017)
Externí odkaz:
https://doaj.org/article/6285313a6d754514a7dc5f04fb3923eb
Autor:
Tobias Rijken, Christopher Austin, Galvin Khara, Dimitrios Korkinof, Hugh Harvey, Annie Ng, Edith Karpati, Peter Kecskemethy
Publikováno v:
Current Breast Cancer Reports. 11:17-22
To review research on deep learning models and their potential application within breast screening. The greatest issue in breast screening is a workforce crisis across the UK, much of Europe and even Japan. Traditional computer-aided detection (CAD)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54dce9f8684e56b4f8d64c3ef91feff8
https://doi.org/10.1007/s12609-019-0301-7
https://doi.org/10.1007/s12609-019-0301-7
Autor:
Edith Karpati, Hugh Harvey, Ben Glocker, Dimitrios Korkinof, Tobias Rijken, Andreas Heindl, Gareth Williams, Peter Kecskemethy
Publikováno v:
Radiol Artif Intell
PURPOSE: To explore whether generative adversarial networks (GANs) can enable synthesis of realistic medical images that are indiscernible from real images, even by domain experts. MATERIALS AND METHODS: In this retrospective study, progressive growi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e171435f96caba09321fcdb86ed9b358
https://europepmc.org/articles/PMC8043361/
https://europepmc.org/articles/PMC8043361/
Autor:
Hugh Harvey, Galvin Khara, Andreas Heindl, Joseph Yearsley, Edith Karpati, Gabor Forrai, Peter Kecskemethy, Michael O’Neill, Tobias Rijken, Dimitrios Korkinof
Publikováno v:
Artificial Intelligence in Medical Imaging ISBN: 9783319948775
Traditional computer aided detection (CAD) systems for breast cancer screening relied on machine learning with human-coded feature-engineering. They have largely failed to fulfill the promise of improving screening accuracy and workflow efficiency, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::587472915f83f449130c384a75251a04
https://doi.org/10.1007/978-3-319-94878-2_14
https://doi.org/10.1007/978-3-319-94878-2_14
Publikováno v:
Argument & Computation. 6:178-218
Probabilistic argumentation and neuro-argumentative systems offer new computational perspectives for the theory and applications of argumentation, but their principled construction involves two entangled problems. On the one hand, probabilistic argum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e700ec59fb666401640c2fa680838d9
https://doi.org/10.1080/19462166.2015.1107134
https://doi.org/10.1080/19462166.2015.1107134
Autor:
Dimitrios Korkinof, Yiannis Demiris
In this work, we propose a novel method for rectifying damaged motion sequences in an unsupervised manner. In order to achieve maximal accuracy, the proposed model takes advantage of three key properties of the data: their sequential nature, the redu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87dcb15622585cc4d65d21a5b1abc8fa
http://hdl.handle.net/10044/1/43499
http://hdl.handle.net/10044/1/43499
Publikováno v:
Expert Systems with Applications
In this work, we propose a novel nonparametric Bayesian method for clustering of data with spatial interdependencies. Specifically, we devise a novel normalized Gamma process, regulated by a simplified (pointwise) Markov random field (Gibbsian) distr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7d922a5004786e0ea26521066695276
https://doi.org/10.1016/j.eswa.2012.05.097
https://doi.org/10.1016/j.eswa.2012.05.097
Autor:
Dimitrios Korkinof, Yiannis Demiris
Publikováno v:
IROS
International Conference on Intelligent Systems and Robots (IROS)
Tokyo, Japan.
International Conference on Intelligent Systems and Robots (IROS)
Tokyo, Japan.
In this work, we present the online Quantum Mixture Model (oQMM), which combines the merits of quantum mechanics and stochastic optimization. More specifically it allows for quantum effects on the mixture states, which in turn become a superposition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac7efe8e447c719fa9fd3c70eb152a78
https://doi.org/10.1109/iros.2013.6696814
https://doi.org/10.1109/iros.2013.6696814
In the past years, many authors have considered application of machine learning methodologies to effect robot learning by demonstration. Gaussian mixture regression (GMR) is one of the most successful methodologies used for this purpose. A major limi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65712f84d5f350f9c4dc962481abbfa5
http://hdl.handle.net/10044/1/12610
http://hdl.handle.net/10044/1/12610
Publikováno v:
IFIP Advances in Information and Communication Technology ISBN: 9783642334085
AIAI (1)
AIAI (1)
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, vol. 381). In this work, we propose a novel nonparametric Bayesian method for clustering of data with spatial interdependencies. Specifically, we devise a no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e8e4f083eb8cc0da4e09a354c4b91c6
https://hdl.handle.net/20.500.14279/4272
https://hdl.handle.net/20.500.14279/4272