Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Abdelkhalak Bahri"'
Publikováno v:
Радіоелектронні і комп'ютерні системи, Vol 2024, Iss 1, Pp 17-35 (2024)
In the digital age, efficient digitization of administrative documents is a real challenge, particularly for languages with complex scripts such as those used in Moroccan documents. The subject matter of this article is the digitization of Moroccan a
Externí odkaz:
https://doaj.org/article/7dfc10906c034f7e8d52418b58da044f
Publikováno v:
Data in Brief, Vol 52, Iss , Pp 109953- (2024)
This article focuses on the construction of a dataset for multilingual character recognition in Moroccan official documents. The dataset covers languages such as Arabic, French, and Tamazight and are built programmatically to ensure data diversity. I
Externí odkaz:
https://doaj.org/article/907705077b414894a303124ff6b0db7d
Autor:
Abdelkhalak, Bahri, Zouaki, Hamid
In this paper we propose a new descriptor for birds search. First, our work was carried on the choice of a descriptor. This choice is usually driven by the application requirements such as robustness to noise, stability with respect to bias, the inva
Externí odkaz:
http://arxiv.org/abs/1503.07816
Publikováno v:
Artificial Intelligence and Smart Environment ISBN: 9783031262531
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6fbff3a35dad90116d122fbfd202fc7f
https://doi.org/10.1007/978-3-031-26254-8_2
https://doi.org/10.1007/978-3-031-26254-8_2
Publikováno v:
2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a06cbd4cdcacd8fc84b0b35f254090e7
https://doi.org/10.1109/iraset52964.2022.9738376
https://doi.org/10.1109/iraset52964.2022.9738376
Publikováno v:
ITM Web of Conferences. 43:01008
The most efficient and beneficial mechanism to the feature of extracting data from an image, has been the Convolutional Neural Network (CNN) and it is used in many fields (Optical character recognition, image classification, object recognition and Fa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f64f1378651a62d8023d512936f8a85a
https://doi.org/10.1051/itmconf/20224301008
https://doi.org/10.1051/itmconf/20224301008
Publikováno v:
International Journal of Multimedia and Ubiquitous Engineering. 12:1-14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44ec9fa66bd047d5590c5ea9eb13e3eb
https://doi.org/10.14257/ijmue.2017.12.10.01
https://doi.org/10.14257/ijmue.2017.12.10.01
Publikováno v:
BDIoT
The number of plants in the world is very important, to distinguish between them in a reasonable time can be problematic. Recent works has shown that convolutional neural network (CNN) models have great potential in the field of classification. The a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d2769492038b2b2710fe8d24fb6d570
https://doi.org/10.1145/3372938.3372974
https://doi.org/10.1145/3372938.3372974
Autor:
Abdelkhalak Bahri, Hamid Zouaki
Publikováno v:
International Journal of Computer Network and Information Security. 8:18-26
In this work, we propose an image search method by visual content (CBIR), which is based on the color descriptor. The proposed method take account the spatial distribution of colors and make the signature partially invariant under rotation. The basic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b47f86338bdba700c825e3f3fd87f670
https://doi.org/10.5815/ijcnis.2016.01.03
https://doi.org/10.5815/ijcnis.2016.01.03
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789812879899
UNet
UNet
Today, mass production multimedia is observed with high variability of form and content, which complicates the management of databases. The use the research techniques based on content has become increasingly necessary rather than the metadata, such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba3e4dbd492d5c93e59ba0f2c0b6dd9b
https://doi.org/10.1007/978-981-287-990-5_29
https://doi.org/10.1007/978-981-287-990-5_29