Zobrazeno 1 - 10 of 69 pro vyhledávání: '"Kamal Nasreddine"'
1
Akademický článek
An efficient anchor‐free method for pig detection
Autor: Morann Mattina, Abdesslam Benzinou, Kamal Nasreddine, Francis Richard
Publikováno v: IET Image Processing, Vol 17, Iss 2, Pp 613-626 (2023)
Abstract Given the rapid growth of commercial pig farms, the need to automatically monitor pig behaviour becomes more important in order to assist farmers. Recent advances in convolutional neural networks may pave the way for new solutions. However,
Externí odkaz: https://doaj.org/article/1d2787670f5b4fd29a9213f4b26f1e54
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2
Akademický článek
Live Fish Species Classification in Underwater Images by Using Convolutional Neural Networks Based on Incremental Learning with Knowledge Distillation Loss
Autor: Abdelouahid Ben Tamou, Abdesslam Benzinou, Kamal Nasreddine
Publikováno v: Machine Learning and Knowledge Extraction, Vol 4, Iss 3, Pp 753-767 (2022)
Nowadays, underwater video systems are largely used by marine ecologists to study the biodiversity in underwater environments. These systems are non-destructive, do not perturb the environment and generate a large amount of visual data usable at any
Externí odkaz: https://doaj.org/article/37a2a773d3dd41b5b926c1bc13de25ad
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3
Akademický článek
Fuzzy Model for the Automatic Recognition of Human Dendritic Cells
Autor: Marwa Braiki, Kamal Nasreddine, Abdesslam Benzinou, Nolwenn Hymery
Publikováno v: Journal of Imaging, Vol 9, Iss 1, p 13 (2023)
Background and objective: Nowadays, foodborne illness is considered one of the most outgrowing diseases in the world, and studies show that its rate increases sharply each year. Foodborne illness is considered a public health problem which is caused
Externí odkaz: https://doaj.org/article/803ff295a11b4e189de402a70cbb5dae
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4
Akademický článek
Targeted Data Augmentation and Hierarchical Classification with Deep Learning for Fish Species Identification in Underwater Images
Autor: Abdelouahid Ben Tamou, Abdesslam Benzinou, Kamal Nasreddine
Publikováno v: Journal of Imaging, Vol 8, Iss 8, p 214 (2022)
In this paper, we address fish species identification in underwater video for marine monitoring applications such as the study of marine biodiversity. Video is the least disruptive monitoring method for fish but requires efficient techniques of image
Externí odkaz: https://doaj.org/article/761f5b993ca9405fa171371b2cbf68d5
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7
Multi-stream fish detection in unconstrained underwater videos by the fusion of two convolutional neural network detectors
Autor: Abdelouahid Ben Tamou, Abdesslam Benzinou, Kamal Nasreddine
Publikováno v: Applied Intelligence. 51:5809-5821
Recently, marine biologists have begun using underwater videos to study species diversity and fish abundance. These techniques generate a large amount of visual data. Automatic analysis using image processing is therefore necessary, since manual proc
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2606d33eba418e97d09fc586da0d7a12
https://doi.org/10.1007/s10489-020-02155-8
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