Existing hyperspectral image classification (HSIC) methods primarily learn discriminative spectral–spatial representations and directly map them to semantic labels, often overlooking the underlying material composition, scene organization, and physical characteristics of hyperspectral observations. To address this limi...
Muhammad Ahmad, A. Maslovskaya, Manuel Mazzara· IEEE Geoscience and Remote S...· 1 citation
Hyperspectral image (HSI) classification remains challenging under extreme label scarcity and spatially disjoint supervision, where models must generalize across heterogeneous materials while producing spatially consistent maps at scale. This article proposes RGMamba (RGM), a relational graph-guided selective state-spa...
Muhammad Ahmad, Hamzah Luqman, Manuel Mazzara· IEEE Transactions on Geoscie...· 0 citations
Autoscaling of microservice applications in containerized cloud environments remains a challenging problem due to complex inter-service dependencies, hierarchical deployment structures, and highly dynamic workloads. Existing autoscaling approaches are predominantly reactive or rely on homogeneous representations of sys...
M. Filippov, Manuel Mazzara· IEEE Access· 0 citations
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