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of 69
pro vyhledávání: '"Epperlein, Jonathan P."'
Autor:
Boschi, Tobia, Bonin, Francesca, Ordonez-Hurtado, Rodrigo, Pascale, Alessandra, Epperlein, Jonathan
Publikováno v:
ICML 2024: https://openreview.net/forum?id=a7MW5kFFOf
This paper introduces a novel methodology for Feature Selection for Functional Classification, FSFC, that addresses the challenge of jointly performing feature selection and classification of functional data in scenarios with categorical responses an
Externí odkaz:
http://arxiv.org/abs/2401.05765
In this work, we devise robust and efficient learning protocols for orchestrating a Federated Learning (FL) process for the Federated Tumor Segmentation Challenge (FeTS 2022). Enabling FL for FeTS setup is challenging mainly due to data heterogeneity
Externí odkaz:
http://arxiv.org/abs/2212.08290
Publikováno v:
2022 IEEE International Conference on Digital Health (ICDH), 2022, pp. 7-12
Intraoperative assessment of tissue can be guided through fluorescence imaging which involves systemic dosing with a fluorophore and subsequent examination of the tissue region of interest with a near-infrared camera. This typically involves administ
Externí odkaz:
http://arxiv.org/abs/2211.05153
Autor:
Epperlein, Jonathan P., Zhuk, Sergiy
With a video data source, such as multispectral video acquired during administration of fluorescent tracers, extraction of time-resolved data typically requires the compensation of motion. While this can be done manually, which is arduous, or using o
Externí odkaz:
http://arxiv.org/abs/2203.08858
Autor:
Epperlein, Jonathan P., Overko, Roman, Zhuk, Sergiy, King, Christopher, Bouneffouf, Djallel, Cullen, Andrew, Shorten, Robert
Reinforcement learning (RL) algorithms aim to learn optimal decisions in unknown environments through experience of taking actions and observing the rewards gained. In some cases, the environment is not influenced by the actions of the RL agent, in w
Externí odkaz:
http://arxiv.org/abs/2103.08241
Autor:
Zhuk, Sergiy, Epperlein, Jonathan P., Nair, Rahul, Thirupati, Seshu, Mac Aonghusa, Pol, Cahill, Ronan, O'Shea, Donal
Intra-operative identification of malignant versus benign or healthy tissue is a major challenge in fluorescence guided cancer surgery. We propose a perfusion quantification method for computer-aided interpretation of subtle differences in dynamic pe
Externí odkaz:
http://arxiv.org/abs/2006.14321
Akademický článek
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Autor:
Epperlein, Jonathan P., Monteil, Julien, Liu, Mingming, Gu, Yingqi, Zhuk, Sergiy, Shorten, Robert
We present here a general framework and a specific algorithm for predicting the destination, route, or more generally a pattern, of an ongoing journey, building on the recent work of [Y. Lassoued, J. Monteil, Y. Gu, G. Russo, R. Shorten, and M. Mevis
Externí odkaz:
http://arxiv.org/abs/1808.10705
We consider the applicability of the data from operators of cellular systems to modelling demand for transportation. While individual-level data may contain precise paths of movement, stringent privacy rules prohibit their use without consent. Presen
Externí odkaz:
http://arxiv.org/abs/1802.03734
Autor:
Epperlein, Jonathan P., Overko, Roman, Zhuk, Sergiy, King, Christopher, Bouneffouf, Djallel, Cullen, Andrew, Shorten, Robert
Publikováno v:
In Automatica October 2022 144
