Zobrazeno 1 - 10
of 1 669
pro vyhledávání: '"Heutte,"'
Publikováno v:
Stat Comput 34, 9 (2024)
High dimension, low sample size (HDLSS) problems are numerous among real-world applications of machine learning. From medical images to text processing, traditional machine learning algorithms are usually unsuccessful in learning the best possible co
Externí odkaz:
http://arxiv.org/abs/2310.14710
Dynamic Time Wrapping (DTW) is a widely used algorithm for measuring similarities between two time series. It is especially valuable in a wide variety of applications, such as clustering, anomaly detection, classification, or video segmentation, wher
Externí odkaz:
http://arxiv.org/abs/2301.12873
Autor:
Siem Buseyne, Amelie Vrijdags, Sameh Said-Metwaly, Thierry Danquigny, Jean Heutte, Fien Depaepe, Annelies Raes
Publikováno v:
Frontiers in Psychology, Vol 15 (2024)
The objective of this study is to explore the relationship between personality and peer-rated team role behavior on the one hand and team role behavior and verbal behavior on the other hand. To achieve this, different data types were collected in fif
Externí odkaz:
https://doaj.org/article/ae403a03534c4c4fb4719e6a6c455a49
Autor:
Dias, Caio da S., Britto Jr., Alceu de S., Barddal, Jean P., Heutte, Laurent, Koerich, Alessandro L.
This paper presents a deep learning approach for image retrieval and pattern spotting in digital collections of historical documents. First, a region proposal algorithm detects object candidates in the document page images. Next, deep learning models
Externí odkaz:
http://arxiv.org/abs/2208.02397
Publikováno v:
In Médecine Palliative Soins de Support - Accompagnement - Ethique September 2024 23(5):242-252
Autor:
Géry, Antoine, Sévin, Corinne, Séguin, Virginie, Merlin, Aurélie, Briot, Laurie, Duquesne, Fabien, Grandchamp-Renard, Gwenaelle, Lalo, Emeline, Petry, Sandrine, Tapprest, Jackie, Bernez-Romand, Maud, Heutte, Natacha, Garon, David
Publikováno v:
In Atmospheric Pollution Research August 2024 15(8)
Autor:
Benjamin Heutte, Nora Bergner, Ivo Beck, Hélène Angot, Lubna Dada, Lauriane L. J. Quéléver, Tiia Laurila, Matthew Boyer, Zoé Brasseur, Kaspar R. Daellenbach, Silvia Henning, Chongai Kuang, Markku Kulmala, Janne Lampilahti, Markus Lampimäki, Tuukka Petäjä, Matthew D. Shupe, Mikko Sipilä, Janek Uin, Tuija Jokinen, Julia Schmale
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-16 (2023)
Abstract The Arctic environment is transforming rapidly due to climate change. Aerosols’ abundance and physicochemical characteristics play a crucial, yet uncertain, role in these changes due to their influence on the surface energy budget through
Externí odkaz:
https://doaj.org/article/f7e980187f164f3db5c64c6f7376cb48
Autor:
Bayen, S., Heutte, J., Vanderbecken, J.-C., Moreau, C., Defebvre, L., Billot, R., Guiton, V., Lemey, C., Lingner, H., Messaadi, W., Devos, D., Messaadi, N.
Publikováno v:
In Revue Neurologique January-February 2024 180(1-2):24-32
Mining data streams is a challenge per se. It must be ready to deal with an enormous amount of data and with problems not present in batch machine learning, such as concept drift. Therefore, applying a batch-designed technique, such as dynamic select
Externí odkaz:
http://arxiv.org/abs/2008.08920
Many classification problems are naturally multi-view in the sense their data are described through multiple heterogeneous descriptions. For such tasks, dissimilarity strategies are effective ways to make the different descriptions comparable and to
Externí odkaz:
http://arxiv.org/abs/2007.08377