Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Ouiem Bchir"'
Publikováno v:
Applied Sciences, Vol 13, Iss 19, p 10994 (2023)
The effectiveness of deep learning models depends on their architecture and topology. Thus, it is essential to determine the optimal depth of the network. In this paper, we propose a novel approach to learn the optimal depth of a stacked AutoEncoder,
Externí odkaz:
https://doaj.org/article/3debeac4e9684c6a955fa31b02cacd2f
Publikováno v:
Applied Sciences, Vol 13, Iss 17, p 9673 (2023)
Semi-supervised clustering typically relies on both labeled and unlabeled data to guide the learning process towards the optimal data partition and to prevent falling into local minima. However, researchers’ efforts made to improve existing semi-su
Externí odkaz:
https://doaj.org/article/c797660076d84f008e3a47cc3dc44cf5
Publikováno v:
Applied Sciences, Vol 13, Iss 1, p 398 (2022)
In this paper, we propose two novel Adaptive Neural Network Approaches (ANNAs), which are intended to automatically learn the optimal network depth. In particular, the proposed class-independent and class-dependent ANNAs address two main challenges f
Externí odkaz:
https://doaj.org/article/af6c2e2671d54f85b834ca0f441f9002
Publikováno v:
Applied Sciences, Vol 12, Iss 22, p 11742 (2022)
Automatic speaker verification (ASV) systems play a prominent role in the security field due to the usability of voice biometrics compared to alternative biometric authentication modalities. Nevertheless, ASV systems are susceptible to malicious voic
Externí odkaz:
https://doaj.org/article/a9e2642439214459920ab9c9edda6674
Autor:
Md Saiful Islam, Mohamed Maher Ben Ismail, Ouiem Bchir, Mohammed Zakariah, Yousef Ajami Alotaibi
Publikováno v:
IEEE Access, Vol 7, Pp 110012-110022 (2019)
Atrial fibrillation (AF) is the most common cardiac arrhythmia. It increases the risk of stroke, dementia, and death; therefore, its timely diagnosis at an initial stage is crucial. Often wearable mobile devices are recommended for the primary detect
Externí odkaz:
https://doaj.org/article/3fae730ccba644fda977885c4e41b73b
Publikováno v:
Journal of Imaging, Vol 6, Iss 1, p 2 (2020)
We propose a novel multiple query retrieval approach, named weight-learner, which relies on visual feature discrimination to estimate the distances between the query images and images in the database. For each query image, this discrimination consist
Externí odkaz:
https://doaj.org/article/ab78595441434f118b93f99bbd2eba35
Publikováno v:
Journal on Artificial Intelligence. 4:167-187
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ceca1758fb70ed9cbc62615d31640bae
https://doi.org/10.32604/jai.2022.032974
https://doi.org/10.32604/jai.2022.032974
Autor:
Mohamed Maher Ben Ismail, Norah M. Asiri, Yousef Ajami Alotaibi, Mohammed Zakariah, Ouiem Bchir
Publikováno v:
Soft Computing. 25:3665-3674
Typically, image-based smoke detection is formulated as a frame classification task that aims to automatically assign the captured frames to the predefined “smoke” or “smoke-free” classes. This classification is based on the visual content of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d77a3ae5cf9f1222a496db89eb79ea0
https://doi.org/10.1007/s00500-020-05396-4
https://doi.org/10.1007/s00500-020-05396-4
Publikováno v:
International Journal of Injury Control and Safety Promotion. 27:546-557
The common classifiers usually used to detect fall incidents depend on building and maintaining complex feature extraction for accurate machine learning tasks. However, these efforts have not succeeded in determining an ideal classifier or feature ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::edf3aa1a9fe57771b158c9bc58b12adf
https://doi.org/10.1080/17457300.2020.1819341
https://doi.org/10.1080/17457300.2020.1819341
Publikováno v:
INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS. 20:156-167
Semi-supervised clustering relies on both labeled and unlabeled data to steer the clustering process towards optimal categorization and escape from local minima. In this paper, we propose a novel fuzzy relational semi-supervised clustering algorithm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42b13fb00f23faf3de42231ea85284dc
https://doi.org/10.5391/ijfis.2020.20.2.156
https://doi.org/10.5391/ijfis.2020.20.2.156