Výsledky vyhledávání - "ALZAHEM, Ayyub"

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An Effective Weight Initialization Method for Deep Learning: Application to Satellite Image Classification

Autor: Boulila, Wadii, Alshanqiti, Eman, Alzahem, Ayyub, Koubaa, Anis, Mlaiki, Nabil

The growing interest in satellite imagery has triggered the need for efficient mechanisms to extract valuable information from these vast data sources, providing deeper insights. Even though deep learning has shown significant progress in satellite i

Externí odkaz: http://arxiv.org/abs/2406.00348

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Feature Fusion for Improved Classification: Combining Dempster-Shafer Theory and Multiple CNN Architectures

Autor: Alzahem, Ayyub, Boulila, Wadii, Driss, Maha, Koubaa, Anis

Addressing uncertainty in Deep Learning (DL) is essential, as it enables the development of models that can make reliable predictions and informed decisions in complex, real-world environments where data may be incomplete or ambiguous. This paper int

Externí odkaz: http://arxiv.org/abs/2405.20230

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Early Detection of Red Palm Weevil Infestations using Deep Learning Classification of Acoustic Signals

Autor: Boulila, Wadii, Alzahem, Ayyub, Koubaa, Anis, Benjdira, Bilel, Ammar, Adel

The Red Palm Weevil (RPW), also known as the palm weevil, is considered among the world's most damaging insect pests of palms. Current detection techniques include the detection of symptoms of RPW using visual or sound inspection and chemical detecti

Externí odkaz: http://arxiv.org/abs/2308.15829

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Sustainable Palm Tree Farming: Leveraging IoT and Multi-Modal Data for Early Detection and Mapping of Red Palm Weevil

Autor: Hajjaji, Yosra, Alzahem, Ayyub, Boulila, Wadii, Farah, Imed Riadh, Koubaa, Anis

The Red Palm Weevil (RPW) is a highly destructive insect causing economic losses and impacting palm tree farming worldwide. This paper proposes an innovative approach for sustainable palm tree farming by utilizing advanced technologies for the early

Externí odkaz: http://arxiv.org/abs/2306.16862

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Unlocking the Potential of Medical Imaging with ChatGPT's Intelligent Diagnostics

Autor: Alzahem, Ayyub, Latif, Shahid, Boulila, Wadii, Koubaa, Anis

Medical imaging is an essential tool for diagnosing various healthcare diseases and conditions. However, analyzing medical images is a complex and time-consuming task that requires expertise and experience. This article aims to design a decision supp

Externí odkaz: http://arxiv.org/abs/2305.07429

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A Deep Learning-based Approach for Real-time Facemask Detection

Autor: Boulila, Wadii, Alzahem, Ayyub, Almoudi, Aseel, Afifi, Muhanad, Alturki, Ibrahim, Driss, Maha

The COVID-19 pandemic is causing a global health crisis. Public spaces need to be safeguarded from the adverse effects of this pandemic. Wearing a facemask becomes one of the effective protection solutions adopted by many governments. Manual real-tim

Externí odkaz: http://arxiv.org/abs/2110.08732

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