The Impact of Resampling and Denoising Deep Learning Algorithms on Radiomics in Brain Metastases MRI

Autor: Ilyass Moummad, Cyril Jaudet, Alexis Lechervy, Samuel Valable, Charlotte Raboutet, Zamila Soilihi, Juliette Thariat, Nadia Falzone, Joëlle Lacroix, Alain Batalla, Aurélien Corroyer-Dulmont

Publikováno v: Cancers, Vol 14, Iss 36, p 36 (2022)
Cancers
Cancers; Volume 14; Issue 1; Pages: 36
Cancers, 2022, 14 (1), pp.36. ⟨10.3390/cancers14010036⟩

Simple Summary Due to the central role of magnetic resonance Imaging (MRI) in the management of patients with cancer, waiting lists exceed clinically relevant delays. For this reason, many research groups and MRI manufacturers develop algorithms as r

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1836f630cc366696cb618c2b4c6a2cfd
https://www.mdpi.com/2072-6694/14/1/36

Improving Neural Text Style Transfer by Introducing Loss Function Sequentiality

Autor: Gaël Dias, Asif Ekbal, Alexis Lechervy, Chinmay Rane

Publikováno v: 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021, Virtual, China
SIGIR
HAL

Text style transfer is an important issue for conversational agents as it may adapt utterance production to specific dialogue situations. It consists in introducing a given style within a sentence while preserving its semantics. Within this scope, di

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::914bac5e90430ee14437ac30efcb07a8
https://hal.archives-ouvertes.fr/hal-03220228

A JOINT LEARNING APPROACH FOR CROSS DOMAIN AGE ESTIMATION

Autor: Alexis Lechervy, Binod Bhattarai, Frédéric Jurie, Gaurav Sharma

Publikováno v: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Mar 2016, Shanghai, China
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ICASSP

International audience; We propose a novel joint learning method for cross domain age estimation, a domain adaptation problem. The proposed method learns a low dimensional projection along with a re-gressor, in the projection space, in a joint framew

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05b072ccecc5b747786ac1dcc97a01f7
https://hal.archives-ouvertes.fr/hal-01301390/document

Boosted kernel for image categorization

Autor: Alexis Lechervy, Frédéric Precioso, Philippe-Henri Gosselin

Publikováno v: Multimedia Tools and Applications
Multimedia Tools and Applications, Springer Verlag, 2013
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International audience; Recent machine learning techniques have demonstrated their capability for identifying image categories using image features. Among these techniques, Support Vector Machines (SVM) present good results for example in Pascal Voc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d9d5bc85e4bea029acb6a43964a7aa2
https://hal.archives-ouvertes.fr/hal-00799068

Boosting Kernel Combination for multi-class image categorization

Autor: Frédéric Precioso, Alexis Lechervy, Philippe-Henri Gosselin

Publikováno v: 2012 IEEE International Conference on Image Processing (ICIP)
2012 IEEE International Conference on Image Processing (ICIP), Sep 2012, Orlando, United States. pp.4
ICIP
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International audience; In this paper, we propose a novel algorithm to design multi- class kernel functions based on an iterative combination of weak kernels in a scheme inspired from boosting framework. The method proposed in this article aims at bu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c271a728f1d05676fe57a1fda8ae7c2c
https://hal.science/hal-00753156