Zobrazeno 1 - 10
of 148
pro vyhledávání: '"Stéphane Marchand-Maillet"'
Autor:
Erol Orel, Rachel Esra, Janne Estill, Amaury Thiabaud, Stéphane Marchand-Maillet, Aziza Merzouki, Olivia Keiser
Publikováno v:
PLoS ONE, Vol 17, Iss 3, p e0264429 (2022)
IntroductionHigh yield HIV testing strategies are critical to reach epidemic control in high prevalence and low-resource settings such as East and Southern Africa. In this study, we aimed to predict the HIV status of individuals living in Angola, Bur
Externí odkaz:
https://doaj.org/article/533586df7a60452081c82788e9c4b830
Autor:
Pierrick Bruneau, Etienne Brangbour, Stéphane Marchand-Maillet, Renaud Hostache, Marco Chini, Ramona-Maria Pelich, Patrick Matgen, Thomas Tamisier
Publikováno v:
Remote Sensing, Vol 13, Iss 6, p 1153 (2021)
Twitter has significant potential as a source of Volunteered Geographic Information (VGI), as its content is updated at high frequency, with high availability thanks to dedicated interfaces. However, the diversity of content types and the low average
Externí odkaz:
https://doaj.org/article/9f7d101e96b54ad4ad469bf40859a6f9
Publikováno v:
Entropy, Vol 19, Iss 3, p 122 (2017)
We describe a framework to build distances by measuring the tightness of inequalities and introduce the notion of proper statistical divergences and improper pseudo-divergences. We then consider the Hölder ordinary and reverse inequalities and prese
Externí odkaz:
https://doaj.org/article/7084000d29604539878542cd48e74ecc
Autor:
Mara Graziani, Sebastian Otalora, Stéphane Marchand-Maillet, Henning Müller, Vincent Andrearczyk
Adopting Convolutional Neural Networks (CNNs) in the daily routine of pathological diagnosis requires not only near-perfect precision, but also sufficient generalization to data shifts and transparency. Existing CNN models act as black boxes, not ens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f657a52fc8bb57f37916622896b3c09
https://doi.org/10.21203/rs.3.rs-744740/v3
https://doi.org/10.21203/rs.3.rs-744740/v3
Binary Digital Image Processing is aimed at faculty, postgraduate students and industry specialists. It is both a text reference and a textbook that reviews and analyses the research output in this field of binary image processing. It is aimed at bot
Publikováno v:
Multimedia Tools and Applications. 80:22429-22464
Highlighting important information of a network is commonly achieved by using random walks related to diffusion over such structures. Complex networks, where entities can have multiple relationships, call for a modeling based on hypergraphs. But, the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8bc39fcc854fcefeb44f9ce7a6583284
https://doi.org/10.1007/s11042-020-09176-y
https://doi.org/10.1007/s11042-020-09176-y
Autor:
Mara Graziani, Sebastian Otalora, Stéphane Marchand-Maillet, Henning Müller, Vincent Andrearczyk
Adopting Convolutional Neural Networks (CNNs) in the daily routine of primary diagnosis requires not only near-perfect precision, but also a sufficient degree of generalization to data acquisition shifts and transparency. Existing CNN models act as b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5526062ec2b389161bc2312ddced754a
https://doi.org/10.21203/rs.3.rs-744740/v2
https://doi.org/10.21203/rs.3.rs-744740/v2
Autor:
Fabrizio Falchi, Claudio Gennaro, Andrea Esuli, Nicola Messina, Giuseppe Amato, Stéphane Marchand-Maillet
Publikováno v:
ACM transactions on multimedia computing communications and applications 17 (2021). doi:10.1145/3451390
info:cnr-pdr/source/autori:Messina N.; Amato G.; Esuli A.; Falchi F.; Gennaro C.; Marchand-Maillet S./titolo:Fine-grained visual textual alignment for cross-modal retrieval using transformer encoders/doi:10.1145%2F3451390/rivista:ACM transactions on multimedia computing communications and applications/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume:17
info:cnr-pdr/source/autori:Messina N.; Amato G.; Esuli A.; Falchi F.; Gennaro C.; Marchand-Maillet S./titolo:Fine-grained visual textual alignment for cross-modal retrieval using transformer encoders/doi:10.1145%2F3451390/rivista:ACM transactions on multimedia computing communications and applications/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume:17
Despite the evolution of deep-learning-based visual-textual processing systems, precise multi-modal matching remains a challenging task. In this work, we tackle the task of cross-modal retrieval through image-sentence matching based on word-region al
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5552fe5769f26c80aa8dec00dc88b2f8
https://zenodo.org/record/6367299
https://zenodo.org/record/6367299
Autor:
Sebastian Otálora, Vincent Andrearczyk, Mara Graziani, Stéphane Marchand-Maillet, Henning Müller
Adopting Convolutional Neural Networks (CNNs) in daily routine of primary diagnosis requires not only near-perfect precision, but also a sufficient degree of transparency and explainability of the decision making. With physicians being accountable fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::512223e86307940d48a1535235b3e32d
https://doi.org/10.21203/rs.3.rs-744740/v1
https://doi.org/10.21203/rs.3.rs-744740/v1
Publikováno v:
Multimedia Tools and Applications, 80(15), 23133-23134. Springer Netherlands
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17685b82579bc4c6f0036012bd4cc07d
https://dare.uva.nl/personal/pure/en/publications/special-issue-on-contentbased-multimedia-indexing-in-the-era-of-artificial-intelligence(6c56a6cd-b81c-4ec5-8d62-69362212cc55).html
https://dare.uva.nl/personal/pure/en/publications/special-issue-on-contentbased-multimedia-indexing-in-the-era-of-artificial-intelligence(6c56a6cd-b81c-4ec5-8d62-69362212cc55).html