A novel deep learning–based framework for multi-temporal LULC classification of Al-Taif City, Saudi Arabia, using Landsat 8 imagery from 2013 to 2024 is introduced, highlighting the effectiveness of the proposed framework in delivering both high-precision classification and interpretable insights.
Abdulmajid A. Alnoamani, Tawfiq Hasanin, A. Al-Ghamdi· Scientific Reports· 0 citations
It is shown that the quality of the generated risk indicators is the main driver of zero-shot cyber threat detection performance, and that retrieval mainly benefits weaker LLMs by generating more discriminative risk indicators, whereas stronger models achieve comparable performance without retrieved context.
A. Al-Ghamdi, S. Layeghy, Marius Portmann· 0 citations
A new framework that combines hybrid encryption with saliency-based adaptive embedding to select the most effective regions for data concealment in cover images, based on the BossBase dataset is proposed.
Abdullah S. al-Malaise Alghamdi, Rana Alrawashdeh· Journal of Cyber Security an...· 0 citations
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