VisionDES is introduced, a novel DES framework for image classification that uses deep model embeddings to estimate classifier competence and consistently outperforms static ensembles and existing uncertainty-based DES methods, improving robust accuracy under strong attacks and under distribution shifts.
Firuz Juraev, Mohammad Abuhamad, Shaker El-Sappagh et al.· Proceedings of the 32nd ACM...· 0 citations
Experimental results demonstrate the superiority of HFE-DDL over the state-of-the-art method in vulnerability detection tasks and show that HFE-DDL has potential as a tool for proactively identifying vulnerabilities during development, aiming to produce more secure Android applications.
Ahmed Abdu, Hakim A. Abdo, Mohsen Ali Alawami et al.· Cluster Computing· 0 citations
Dynamic Ensemble Selection (DES) is an adaptive ensemble learning paradigm that selects a subset of base classifiers specific to each test input, enabling more flexible predictions than static ensemble methods. Although successful in tabular settings, DES remains largely unexplored in robust vision applications. We int...
Firuz Juraev, Mohammad Abuhamad, S. El-Sappagh et al.· Proceedings of the 32nd ACM...· 0 citations
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