Zobrazeno 1 - 6
of 6
pro vyhledávání: '"takwa Ben Aïcha"'
Autor:
Afef Kacem Echi, Takwa Ben Aïcha Gader
Publikováno v:
ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 23, Iss 1 (2024)
In this work, we present two advanced models for identifying script writers, leveraging the power of deep learning. The proposed systems utilize the new vision Swin Transformer and ResNeSt-50. Swin Transformer is known for its robustness to variation
Externí odkaz:
https://doaj.org/article/fe5fe13215e54a8294706804aafbe22a
Publikováno v:
ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 22, Iss 1 (2023)
Prostate Cancer (PCa) is one of the most common diseases in adult males. Currently, mp-MRI imaging represents the most promising technique for screening, diagnosing, and managing this cancer. However, the multiple mp-MRI sequences' visual interpretat
Externí odkaz:
https://doaj.org/article/e63ccd2640a04cd8ab0625aabedc7727
Autor:
Takwa Ben Aïcha Gader, Afef Kacem Echi
Publikováno v:
Machine Graphics and Vision. 31:49-73
This work proposes a segmentation-free approach to Arabic Handwritten Text Recognition (AHTR): an attention-based Convolutional Neural Network - Recurrent Neural Network - Connectionist Temporal Classification (CNN-RNN-CTC) deep learning architecture
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d775aeff3d2b404fd5f52259863e6e5
https://doi.org/10.22630/mgv.2022.31.1.3
https://doi.org/10.22630/mgv.2022.31.1.3
Autor:
Khalil Barbouchi, Dhekra El Hamdi, Ines Elouedi, Takwa Ben Aïcha, Afef Kacem Echi, Ihsen Slim
Publikováno v:
International Journal of Imaging Systems and Technology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09ddde01bb39cdaf78f685d13388228e
https://doi.org/10.1002/ima.22858
https://doi.org/10.1002/ima.22858
Autor:
Takwa Ben Aïcha Gader, Afef Kacem Echi
Publikováno v:
Communications in Computer and Information Science ISBN: 9783031082764
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aeef7452817d5b9772b0bdb0e12be237
https://doi.org/10.1007/978-3-031-08277-1_8
https://doi.org/10.1007/978-3-031-08277-1_8
Autor:
takwa Ben Aicha, Afef Kacem Echi
Publikováno v:
ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 21, Iss 1 (2022)
Word extraction is one of the most critical steps in handwritten recognition systems. It is challenging for many reasons, such as the variability of handwritten writing styles, touching and overlapping characters, skewness problems, diacritics, ascen
Externí odkaz:
https://doaj.org/article/93c043474d1b4e3388aecd8f96653b8e