Historical Text Line Segmentation Using Deep Learning Algorithms: Mask-RCNN against U-Net Networks

Autor: Florian Côme Fizaine, Patrick Bard, Michel Paindavoine, Cécile Robin, Edouard Bouyé, Raphaël Lefèvre, Annie Vinter

Publikováno v: Journal of Imaging, Vol 10, Iss 3, p 65 (2024)

Text line segmentation is a necessary preliminary step before most text transcription algorithms are applied. The leading deep learning networks used in this context (ARU-Net, dhSegment, and Doc-UFCN) are based on the U-Net architecture. They are eff

Externí odkaz: https://doaj.org/article/16debf92d3ea4e53b5b970858096f199

What breaks the flow of reading? A study on characteristics of attentional disruption during digital reading

Autor: Guillaume Chevet, Thierry Baccino, Annie Vinter, Véronique Drai-Zerbib

Publikováno v: Frontiers in Psychology, Vol 13 (2022)

Reading is increasingly taking place on digital media, which are vectors of attentional disruption. This manuscript aims to characterize attentional disruption during reading on a computer screen in an ecological environment. To this end, we collecte

Externí odkaz: https://doaj.org/article/09da929438384074bec6f8e140a2cf58

Identification of Textured Tactile Pictures in Visually Impaired and Blindfolded Sighted Children

Autor: Annie Vinter, Oriana Orlandi, Pascal Morgan

Publikováno v: Frontiers in Psychology, Vol 11 (2020)

A high level of variability in the capacity of visually impaired children to accurately identify tactile images is reported in the literature, with on average rather low percentages of correct naming responses. However, most of these studies used rai

Externí odkaz: https://doaj.org/article/a906c4d7c14441c389a88aff98e8333c

The effect of response-to-stimulus interval on children’s implicit sequence learning

Autor: Arnaud Witt, Bénédicte Poulin-Charronnat, Patrick Bard, Annie Vinter

Publikováno v: Journal of Experimental Child Psychology. 232:105668

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d78e01140d3562e6c8747a429a15f95b
https://doi.org/10.1016/j.jecp.2023.105668

Validation of the Intention Attribution Test for Children (IAC)

Autor: Annie Vinter, Raphaële Miljkovitch, Alyssa Counsell, Stéphanie Vanwalleghem, Leslie Atkinson

Publikováno v: Assessment
Assessment, SAGE Publications, 2020, 27 (7), pp.1619-1632. ⟨10.1177/1073191119831781⟩
Assessment, 2020, 27 (7), pp.1619-1632. ⟨10.1177/1073191119831781⟩

International audience; The Intention Attribution Test for Children (IAC) was created to assess hostile attribution bias in preschool- and early school-aged children. It comprises 16 cartoon strips presenting situations in which one character (either

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d55e1c720733b74a35099f97cff9144d
https://doi.org/10.1177/1073191119831781