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This paper proposes a method to adaptively select the configuration of the hierarchical family of classifiers. Linkage statistics from overall and sub- ...
The proposed adaptive network selection framework, consisting of hierarchical models based on adaptive transfer learning, outperform single CNN models. The ...
This paper proposes a method to adaptively select the configuration of the hierarchical family of classifiers, a network of fine classifiers which solve ...
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This paper proposes a method to adaptively select the configuration of the hierarchical family of classifiers. Linkage statistics from overall and sub- ...
Jan 17, 2019 · Classification by Adaptive Networks ... Starting from some crude ideas about the structure of the human brain and the human eye an interesting ...
Deterministic down-sampling of an unordered point cloud in a deep neural network has not been rigorously studied so far. Existing methods down-sample the ...
Dec 6, 2024 · We propose a novel Center-Anchored Adaptive Hierarchical GNN (CAAH-GNN) model that integrates a center-anchored method with an adaptive hierarchical strategy.
This research focused on the development of a hierarchical approach for classification that is robust with respect to training data that are limited both in ...
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Our proposed AHRL splits the whole classification feature space into a hierarchical struc- ture and eliminates this tough problem in a coarse-to-fine way.
Nov 24, 2021 · In this work, we propose a new approach for species classification termed hierarchy-guided neural network (HGNN), which infuses hierarchical ...