Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Afef Kacem-Echi"'
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 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
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
Publikováno v:
Arabian Journal for Science and Engineering. 44:9301-9319
In this paper, the ability of Bayesian and convolutional neural networks (CNNs), as two different machine learning methods, to recognize Arabic handwritten words is analyzed. Our contribution is threefold. First, we describe the main highlights of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b56ed21a590a5b780c22b2838bf32da
https://doi.org/10.1007/s13369-019-03939-y
https://doi.org/10.1007/s13369-019-03939-y
Publikováno v:
Pattern Recognition and Artificial Intelligence ISBN: 9783030718039
MedPRAI
MedPRAI
Real scientific challenge, handwritten math formula recognition is an attractive field of pattern recognition leading to practical applications. Hundreds of alphanumeric and math symbols need to be recognized, many are so similar in appearance that s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a159215c69aa667ef18864e4adcfc5b
https://doi.org/10.1007/978-3-030-71804-6_15
https://doi.org/10.1007/978-3-030-71804-6_15
Autor:
Afef Kacem Echi, Takwa Ben Aicha Gader
Publikováno v:
ICFHR
Text-lines are hard to segment in the context of Arabic manuscripts, because of the narrowly spaced text-lines with touching or overlapping components, the varying spaces between words, the ascendant or descendant letters, special marks, and dots, ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60965f8526962d6a621c4ca2c103f882
https://doi.org/10.1109/icfhr2020.2020.00070
https://doi.org/10.1109/icfhr2020.2020.00070
Publikováno v:
ASAR
ASAR, Sep 2019, Sydney, Australia
ASAR@ICDAR
ASAR, Sep 2019, Sydney, Australia
ASAR@ICDAR
International audience; One of the most important steps in a handwriting recognition system is text-line and word segmentation. But, this step is made difficult by the differences in handwriting styles, problems of skewness, overlapping and touching
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a4150032d5881361d4f873a3696a56e
https://hal.inria.fr/hal-02460880
https://hal.inria.fr/hal-02460880