681 citations
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma IIT339 papers
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525 papers
Deep Learning for Anomaly Detection in Railway Systems: A Structured Survey
Ammar Bouketta, Smail Niar, Hamza Ouarnoughi
Ensuring safe and reliable operation of modern railway systems increasingly relies on data-driven monitoring and intelligent fault detection. Deep learning has emerged as an effect…
Classification Based on Association Rules Algorithm for Breast Cancer
Ali Alsalama, Ahmed Kubba, Ghaith Jamjoum +1
Breast cancer is a significant contributor to female mortality across the world, displaying one of the highest oc currence rates among the various cancer types. In response to the…
Multimodal Cultural Heritage Architectural Style Classification for Residential Buildings in the UAE Based on CLIP Embeddings and SVM
Ahmed Ammar Kubba, Manar Abu Talib, Iman Ibrahim +1
The analysis and classification of cultural heritage architectural styles remain challenging due to the complexity of visual images of buildings, which are highly relied on in trad…
Semi-Supervised Learning-Based Genetic Biomarkers Dataset for Multiple-Stage Hepatocellular Carcinoma Prediction
Ahmed Ammar Kubba, Manar Abu Talib, Jibran Sualeh Muhammad +4
Liver cancer is a complex disease responsible for a high number of deaths across the globe each year, making automated solutions for liver cancer classification urgent. The most co…
Scalability and Performance Evaluation of Federated Learning Frameworks: A Comparative Analysis
Bassel Soudan, Sohail Abbas, Ahmed Kubba +2
This paper presents a systematic examination and experimental comparison of the prominent Federated Learning (FL) frameworks FedML, Flower, Substra, and OpenFL. The frameworks are…
Data-Aided Channel and Doppler Estimation for mMIMO LEO SatComs with Uncompensated Doppler
Abdollah Masoud Darya, Saeed Abdallah
This paper presents a framework for estimating and tracking massive multiple-input multiple-output (mMIMO) low-Earth-orbit (LEO) satellite channels under uncompensated Doppler. The…