5 citations · 7 across the 8 of their papers we have counts for
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cs.LG2024
Select High-Level Features: Efficient Experts from a Hierarchical Classification Network
André Kelm, Niels Hannemann, Bruno Heberle +5
This study introduces a novel expert generation method that dynamically reduces task and computational complexity without compromising predictive performance. It is based on a new…
cs.LG2020
Person Re-identification: Implicitly Defining the Receptive Fields of Deep Learning Classification Frameworks
Ehsan Yaghoubi, Diana Borza, Aruna Kumar +1
The \emph{receptive fields} of deep learning classification models determine the regions of the input data that have the most significance for providing correct decisions. The prim…